Status and Challenges of Density Functional Theory

Machine learning for accuracy in density functional approximations

Machine learning techniques have found their way into computational chemistry as indispensable tools to accelerate atomistic simulations and materials design. In addition, machine learning approaches hold the potential to boost the predictive power of computationally efficient electronic structure methods, such as density functional theory, to chemical accuracy and to correct for fundamental errors in density functional approaches. Here, recent progress in applying machine learning to improve the accuracy of density functional and related approximations is reviewed. Promises and challenges in devising machine learning models transferable between different chemistries and materials classes are discussed with the help of examples applying promising models to systems far outside their training sets.

Multi-combined QSAR, molecular docking, molecular dynamics simulation, and ADMET of Flavonoid derivatives as potent cholinesterase inhibitors

In searching for a new and efficient therapeutic agent against Alzheimer's disease, a Quantitative structure-activity relationship (QSAR) was derived for 45 Flavonoid derivatives recently synthesized and evaluated as cholinesterase inhibitors. The multiple linear regression method (MLR) was adopted to develop an adequate mathematical model that describes the relationship between a variety of molecular descriptors of the studied compounds and their biological activities (cholinesterase inhibitors). Golbraikh and Tropsha criteria were applied to verify the validity of the built model. The built MLR model was statistically reliable, robust, and predictive (R2 = 0.801, Q2cv = 0.876, R2test = 0.824). Dreiding energy and Molar Refractivity were the major factors that govern the Anti-cholinesterase activity. These results were further exploited to design a new series of Flavonoid derivatives with higher Anti-cholinesterase activities than the existing ones. Thereafter, molecular docking and molecular dynamic studies were performed to predict the binding types of the designed compounds and to investigate their stability at the active site of the Butyrylcholinestérase BuChE protein. The negative and low binding affinity calculated for all designed compounds shows that designed compound 1 has a favorable affinity for the 4TPK. Moreover, molecular dynamics simulation studies confirmed the stability of designed compound 1 in the active pocket of 4TPK over 100 ns. Finally, the ADMET analysis was incorporated to analyze the pharmacokinetics and toxicity parameters. The designed compounds were found to meet the ADMET descriptor criteria at an acceptable level having respectable intestinal permeability and water solubility and can reach the intended destinations.Communicated by Ramaswamy H. Sarma.

Inverse Design of Low-Resistivity Ternary Gold Alloys via Interpretable Machine Learning and Proactive Search Progress

Ternary gold alloys (TGAs) are highly regarded for their excellent electrical properties. Electrical resistivity is a crucial indicator for evaluating the electrical performance of TGAs. To explore new promising TGAs with lower resistivity, we developed a reverse design approach integrating machine learning techniques and proactive searching progress (PSP) method. Compared with other models, the support vector regression (SVR) was determined to be the most optimal model for resistivity prediction. The training and test sets yielded R2 values of 0.73 and 0.77, respectively. The model interpretation indicated that lower electrical resistivity was associated with the following conditions: a van der Waals Radius (Vrt) of 0, a Vr (another van der Waals Radius) of less than 217, and a mass attenuation coefficient of MoKα (Macm) greater than 77.5 cm2g-1. Applying the PSP method, we successfully identified eight candidates whose resistivity was lower than that of the sample with the lowest resistivity in the dataset by more than 53-60%, e.g., Au1.000Cu4.406Pt1.833 and Au1.000Pt2.232In1.502. Finally, the candidates were validated to possess low resistivity through the pattern recognition method.

Advancements and Challenges in the Integration of Indium Arsenide and Van der Waals Heterostructures

The strategic integration of low-dimensional InAs-based materials and emerging van der Waals systems is advancing in various scientific fields, including electronics, optics, and magnetics. With their unique properties, these InAs-based van der Waals materials and devices promise further miniaturization of semiconductor devices in line with Moore's Law. However, progress in this area lags behind other 2D materials like graphene and boron nitride. Challenges include synthesizing pure crystalline phase InAs nanostructures and single-atomic-layer 2D InAs films, both vital for advanced van der Waals heterostructures. Also, diverse surface state effects on InAs-based van der Waals devices complicate their performance evaluation. This review discusses the experimental advances in the van der Waals epitaxy of InAs-based materials and the working principles of InAs-based van der Waals devices. Theoretical achievements in understanding and guiding the design of InAs-based van der Waals systems are highlighted. Focusing on advancing novel selective area growth and remote epitaxy, exploring multi-functional applications, and incorporating deep learning into first-principles calculations are proposed. These initiatives aim to overcome existing bottlenecks and accelerate transformative advancements in integrating InAs and van der Waals heterostructures.

Low-temperature subcritical water dechlorination composites of waste PVC/coal fly ash with powerful sensing activity for chemiluminescent detection of acetamiprid and imidacloprid

Pesticide residues in agricultural products are serious threat to people's health. Real-time monitoring of pesticides residues in the environment and agricultural products posed challenges to sustainable methods with high analytical performance for pesticide detection. Herein, waste PVC/coal fly ash (the mass ratio of PVC and coal fly ash was 4:1) was dechlorinated in subcritical water at low temperature to achieve nearly 100 % dechlorination of PVC and obtain carbon-based composite materials (CM-Fe/Al/Si-dPVC) with strong sening activity. For CM-Fe/Al/Si-dPVC, CFe bonding resulted in strong electron migration, and nano/μm SiO2 and Al2O3 doping in the layered polyene C matrix provided large specific surface area, and silicon hydroxyl created good heterogeneous catalytic interfaces. CM-Fe/Al/Si-dPVC could strongly trigger luminol chemiluminescence (CL) reaction and produce intense CL signals. Neonicotinoid pesticides (acetamiprid and imidacloprid) bonded with CM-Fe/Al/Si-dPVC through coordination chelation and hydrogen bonding, which shielded the catalytic active site and increased the Fermi level of system, thus quenching CL reaction. Inspired by these, a cheap CL assay was constructed for detecting neonicotinoids combinations of acetamiprid and imidacloprid (NICs). The detection limits of NICs were 0.7 ng/L. Satisfactory recoveries were obtained for real agricultural products and environmental samples. The results of life cycle evaluation (LCA) revealed that the strategy had significantly small global warming potential (GWP). This work presented a sustainable method with environmental benefits for the detection of neonicotinoids, and also opened up new way for the recycling of organic solid wastes.

Energetics of the OH radical H-abstraction reactions from simple aldehydes and their geminal diol forms

CONTEXT

Carbonyl compounds, especially aldehydes, emitted to the atmosphere, may suffer hydration in aerosols or water droplets in clouds. At the same time, they can react with hydroxyl radicals which may add or abstract hydrogen atoms from these species. The interplay between hydration and hydrogen abstraction is studied using density functional and quantum composite theoretical methods, both in the gas phase and in simulated bulk water. The H-abstraction from the aldehydic and geminal diol forms of formaldehyde, acetaldehyde, glycolaldehyde, glyoxal, methylglyoxal, and acrolein is studied to determine whether the substituent has any noticeable effect in the preference for the abstraction of one form or another. It is found that abstraction of the H-atom adjacent to the carbonyl group gives a more stable radical than same abstraction from the geminal diol in the case of formaldehyde, acetaldehyde, and glycolaldehyde. The presence of a delocalizing group in the Cα (a carbonyl group in glyoxal and methylglyoxal, and a vinyl group in acrolein), reverts this trend, and now the abstraction of the H-atom from the geminal diol gives more stable radicals. A further study was conducted abstracting hydrogen atoms from the other different positions in the species considered, both in the aldehydic and geminal diol forms. Only in the case of glycolaldehyde, the radical formed by H-abstraction from the -CH2OH group is more stable than any of the other radical species. Abstraction of the hydrogen atom in one of the hydroxyl groups in the geminal diol is equivalent to the addition of the •OH radical to the aldehyde. It leads, in some cases, to decomposition into a smaller radical and a neutral molecule. In these cases, some interesting theoretical differences are observed between the results in gas phase and (simulated) bulk solvent, as well as with respect to the method of calculation chosen.

METHODS

DFT (M06-2X, B2PLYP, PW6B95), CCSD(T), and composite (CBS-QB3, jun-ChS, SCVECV-f12) methods using Dunning basis sets and extrapolation to the CBS limit were used to study the energetics of closed shell aldehydes in their keto and geminal-diol forms, as well as the radical derived from them by hydrogen abstraction. Both gas phase and simulated bulk solvent calculations were performed, in the last case using the Polarizable Continuum Model.

Nitrile Imine Cyclizations and Rearrangements: N-Phenyl-C-styrylnitrile Imine and N-Phenyl-C-phenylethynylnitrile Imine

The formation and rearrangements of nitrile imines are of ongoing synthetic and theoretical interest. In this paper, we report a computational investigation at the M06/6-311 + G(d,p) level of the formation and rearrangement of propargylic N-phenyl-C-styrylnitrile imine 3 from 2-phenyl-5-styryltetrazole 1 by flash vacuum pyrolysis (FVP). Nitrile imine 3 cyclizes to 3aH-3-styrylindazole 4, which is also generated by H-shifts in the FVP of 3-styrylindazole 8. Tautomerization of 4 and N2-elimination afford cyclohexadienylidene 14, which by cyclization followed by H-shifts yields the primary pyrolysis product, 3-phenylindene 5. An alternate path via 7aH-3-styrylindazole, phenyl(styryl)diazomethane, and phenyl(styryl)carbene is potentially possible. The analogous pyrolysis of 2-phenyl-5-phenylethynyltetrazole 1' afforded cyclopenta[fg]fluorene and cyclopenta[def]phenanthrene via N-phenyl-C-phenylethynylnitrile imine 3' and 3aH-3-phenylethynylindazole 4'. In both cases, 3 and 3', rearrangement to diazocyclohexadienes and cyclohexadienylidenes (e.g., 14) is energetically preferred over alternate aryldiazomethane and arylcarbene intermediates.

Progress in the Computer-Aided Analysis in Multiple Aspects of Nanocatalysis Research

Making the utmost of the differences and advantages of multiple disciplines, interdisciplinary integration breaks the science boundaries and accelerates the progress in mutual quests. As an organic connection of material science, enzymology, and biomedicine, nanozyme-related research is further supported by computer technology, which injects in new vitality, and contributes to in-depth understanding, unprecedented insights, and broadened application possibilities. Utilizing computer-aided first-principles method, high-speed and high-throughput mathematic, physic, and chemic models are introduced to perform atomic-level kinetic analysis for nanocatalytic reaction process, and theoretically illustrate the underlying nanozymetic mechanism and structure-function relationship. On this basis, nanozymes with desirable properties can be designed and demand-oriented synthesized without repeated trial-and-error experiments. Besides that, computational analysis and device also play an indispensable role in nanozyme-based detecting methods to realize automatic readouts with improved accuracy and reproducibility. Here, this work focuses on the crossing of nanocatalysis research and computational technology, to inspire the research in computer-aided analysis in nanozyme field to a greater extent.

Simulation of Linear and Cyclic Alkanes with Second-Order Møller-Plesset Perturbation Theory through Adaptive Force Matching

Predicting ensemble properties, such as density and heat of vaporization, of small hydrocarbons is challenging due to the dispersion-dominated weak interactions between these molecules. With the adaptive force matching (AFM) method, the bonded and short-range nonbonded interactions are fitted to second-order Møller-Plesset perturbation theory (MP2) references computed with the def2-TZVP basis set. The dispersion is modeled using symmetry adapted perturbation theory (SAPT) at MP4 accuracy using the def2-TZVPD basis set. A new charge matrix decomposition technique is described to obtain partial charges in AFM. Although the models developed do not have any empirical parameters, several properties of the resulting models are compared with experiments as validations. The density, heat of vaporization, pressure dependence of density, diffusion constants, and surface tensions all show quantitative agreement with experiments. Although the density shows a very small systematic error, which could be due to missing three-body dispersion, the heat of vaporization agrees with experiments of within 0.5%. The paper shows that AFM can be used as a reliable tool to enable simulations at post-Hartree-Fock quality at the cost of molecular mechanics force fields.

Origins of the unphysical noncovalent interaction energy curves obtained with the 2011 and 2012 Minnesota density functionals

With the noncovalent interaction energy curves of the methane dimer [(CH4)2], we have clarified two different origins of the unphysical noncovalent interaction energy curves obtained with the Minnesota density functionals of M11-L, MN12-L, and MN12-SX. For the M11-L functional, the unphysical inflection point on the (CH4)2 interaction energy curve originates from the inclusion of the long-range exchange. As to the MN12-L and MN12-SX functionals, the lack of smoothness restraints results in unphysical inflection points on the corresponding (CH4)2 interaction energy curves. As a result, exchange functionals are as important as dispersion corrections for density functionals to map noncovalent interaction energy surfaces reasonably. Moreover, very highly parameterized functionals with smoothness restraints are suggested for investigating noncovalent interaction energy surfaces.

Enhancing the charge transport and luminescence properties of ethyl 4-[(E)-(2-hydroxy-4-methoxyphenyl)methyleneamino]benzoate through complexation: a DFT and TD-DFT study

Organic light emitting diode (OLED) and organic solar cell (OSC) properties of ethyl 4-[(E)-(2-hydroxy-4-methoxyphenyl)methyleneamino]benzoate (EMAB) and its Pt2+, Pd2+, Ni2+, Ir3+, Rh3+, and Zn2+ complexes have been theoretically studied herein. Geometry optimizations have been performed via the r2SCAN-3c composite method while single-point calculations have been carried out at the PBE0-D3(BJ)/def2-TZVP level of theory. Results have shown that complexation with selected metal ions improves hole and electron transfer rates in Pt[EMAB]2 and Rh[EMAB]2 +. Specifically, the hole transport rate of Pt[EMAB]2, (k ct(h) = 6.15 × 1014 s-1), is found to be 44 times greater than that of [EMAB], (k ct(h) = 1.42 × 1013 s-1), whereas electron transport rate of Pt[EMAB]2, (k ct(e) = 4.6 × 1013 s-1) is 4 times that of EMAB (k ct(e) = 1.1 × 1013 s-1). Charge mobility for holes and electrons are equal to 19.182 cm2 V-1 s-1 and 1.431 cm2 V-1 s-1 respectively for Pt[EMAB]2, and equal to 4.11 × 10-1 cm2 V-1 s-1 and 3.43 × 10-1 cm2 V-1 s-1 for EMAB respectively. These results show that, charge transport in EMAB can be tuned for better performance through complexation with transition metals such as Pt2+. OSC properties of the complexes were also studied by comparing their HOMO/LUMO energies with those of (6,6)-phenyl-C61-butyric acid methyl ester (PCBM) and poly(3-hexylthiophene) (P3HT). It turned out that the energy gap of EMAB reduced significantly upon complexation from 2.904 eV to 0.56 eV in [Rh(EMAB)2]+ and to a lesser extent in the other complexes. The energy values of the HOMOs remained higher than those of PCBM while those of the LUMOs were found to be greater than that of P3HT with the exception of [Rh(EMAB)2]+. These findings show that the aforementioned species are good electron donors to PCBM. The open circuit voltage, V OC, of the compounds ranged between 0.705 × 10-19 V and 6.617 × 10-19 V, values that are good enough for practical usage in OSC applications. The UV-visible absorption spectra revealed absorption maxima well below 900 nm in all compounds, vital in the efficient functioning of solar cells. In general, this study has shown that platinoid complexation of EMAB can successfully modify both its OLED and OSC properties, making them better precursors in the electronic industry.

Identification of extracellular polymeric substances layer barrier in chloroquine phosphate-disturbed anammox consortia and mechanism dissection on cytotoxic behavior by computational chemistry

The over-dosing use of chloroquine phosphate (CQ) poses severe threats to human beings and ecosystem due to the high persistence and biotoxicity. The discharge of CQ into wastewater would affect the biomass activity and process stability during the biological processes, e.g., anammox. However, the response mechanism of anammox consortia to CQ remain unknown. In this study, the accurate role of extracellular polymeric substances barrier in attenuating the negative effects of CQ, and the mechanism on cytotoxic behavior were dissected by molecular spectroscopy and computational chemistry. Low concentrations (≤6.0 mg/L) of CQ hardly affected the nitrogen removal performance due to the adaptive evolution of EPS barrier and anammox bacteria. Compact protein of EPS barrier can bind more CQ (0.24 mg) by hydrogen bond and van der Waals force, among which O-H and amide II region respond CQ binding preferentially. Importantly, EPS contributes to the microbiota reshape with selectively enriching Candidatus_Kuenenia for self-protection. Furthermore, the macroscopical cytotoxic behavior was dissected at a molecular level by CQ fate/distribution and computational chemistry, suggesting that the toxicity was ascribed to attack of CQ on functional proteins of anammox bacteria with atom N17 (f-=0.1209) and C2 (f+=0.1034) as the most active electrophilic and nucleophilic sites. This work would shed the light on the fate and risk of non-antibiotics in anammox process.

Nuclear Magnetic Resonance Chemical Shift as a Probe for Single-Molecule Charge Transport

Existing modelling tools, developed to aid the design of efficient molecular wires and to better understand their charge-transport behaviour and mechanism, have limitations in accuracy and computational cost. Further research is required to develop faster and more precise methods that can yield information on how charge transport properties are impacted by changes in the chemical structure of a molecular wire. In this study, we report a clear semilogarithmic correlation between charge transport efficiency and nuclear magnetic resonance chemical shifts in multiple series of molecular wires, also accounting for the presence of chemical substituents. The NMR data was used to inform a simple tight-binding model that accurately captures the experimental single-molecule conductance values, especially useful in this case as more sophisticated density functional theory calculations fail due to inherent limitations. Our study demonstrates the potential of NMR spectroscopy as a valuable tool for characterising, rationalising, and gaining additional insights on the charge transport properties of single-molecule junctions.

Data Cleansing and Sub-Unit-Based Molecular Description Enable Accurate Prediction of The Energy Levels of Non-Fullerene Acceptors Used in Organic Solar Cells

Non-fullerene acceptors (NFAs) have recently emerged as pivotal materials for enhancing the efficiency of organic solar cells (OSCs). To further advance OSC efficiency, precise control over the energy levels of NFAs is imperative, necessitating the development of a robust computational method for accurate energy level predictions. Unfortunately, conventional computational techniques often yield relatively large errors, typically ranging from 0.2 to 0.5 electronvolts (eV), when predicting energy levels. In this study, the authors present a novel method that not only expedites energy level predictions but also significantly improves accuracy , reducing the error margin to 0.06 eV. The method comprises two essential components. The first component involves data cleansing, which systematically eliminates problematic experimental data and thereby minimizes input data errors. The second component introduces a molecular description method based on the electronic properties of the sub-units comprising NFAs. The approach simplifies the intricacies of molecular computation and demonstrates markedly enhanced prediction performance compared to the conventional density functional theory (DFT) method. Our methodology will expedite research in the field of NFAs, serving as a catalyst for the development of similar computational approaches to address challenges in other areas of material science and molecular research.

Highly efficient molecular film for inhibiting volatilization of hazardous nitric acid

Nitric acid, an important basic chemical raw material, plays an important role in promoting the development of national economy. However, such liquid hazardous chemicals are easy to cause accidental leakage during production, transportation, storage and use. The high concentration and corrosive toxic gas generated from decomposition shows tremendous harm to the surrounding environment and human life safety. Therefore, how to inhibit the volatilization of nitric acid and effectively control and block the generation of the toxic gas in the first time are the key to deal with the nitric acid leakage accident. Herein, a new method of molecular film obstruction is proposed to inhibit the nitric acid volatilization. The molecular film inhibitor spontaneously spread and form an insoluble molecular film on the gas-liquid interface, changing the state of nitric acid liquid surface and inhibiting the volatilization on the molecular scale. The inhibition rate up to 96% can be achieved below 45 °C within 400 min. Cluster structure simulation and energy barrier calculation is performed to elucidate the inhibition mechanism. Theoretical analysis of energy barrier shows that the specific resistance of the inhibitor significantly increased to 460 s·cm-1 at 45 °C, and the generated energy barrier is about 17,000 kJ·mol-1, which is much higher than the maximum energy required for nitric acid volatilization of 107.97 kJ·mol-1. The molecular film obstruction strategy can effectively inhibit the volatilization of nitric acid. This strategy paves the way for preventing the volatilization of liquid hazardous chemicals in accidental leakage treatment.

Mechanism of thermal oxidation into volatile compounds from (E)-4-decenal: A density functional theory study

Unsaturated aliphatic aldehyde oxidation plays a significant role in the deep oxidation of fatty acids to produce volatile chemicals. Exposing the oxidation process of unsaturated aliphatic aldehydes is crucial to completely comprehend how food flavor forms. In this study, thermal desorption cryo-trapping in conjunction with gas chromatography-mass spectrometry was used to examine the volatile profile of (E)-4-decenal during heating, and 32 volatile compounds in all were detected and identified. Meanwhile, density functional theory (DFT) calculations were used, and 43 reactions were obtained in the 24 pathways, which were summarized into the peroxide reaction mechanism (ROOH), the peroxyl radical reaction mechanism (ROO·) and the alkoxy radical reaction mechanism (RO·). Moreover, the priority of these three oxidative mechanisms was the RO· mechanism > ROOH mechanism > ROO· mechanism. Furthermore, the DFT results and experimental results agreed well, and the oxidative mechanism of (E)-4-decenal was finally illuminated.

The role and potential of computer-aided drug discovery strategies in the discovery of novel antimicrobials

Antimicrobial resistance (AMR) has become more of a concern in recent decades, particularly in infections associated with global public health threats. The development of new antibiotics is crucial to ensuring infection control and eradicating AMR. Although drug discovery and development are essential processes in the transformation of a drug candidate from the laboratory to the bedside, they are often very complicated, expensive, and time-consuming. The pharmaceutical sector is continuously innovating strategies to reduce research costs and accelerate the development of new drug candidates. Computer-aided drug discovery (CADD) has emerged as a powerful and promising technology that renews the hope of researchers for the faster identification, design, and development of cheaper, less resource-intensive, and more efficient drug candidates. In this review, we discuss an overview of AMR, the potential, and limitations of CADD in AMR drug discovery, and case studies of the successful application of this technique in the rapid identification of various drug candidates. This review will aid in achieving a better understanding of available CADD techniques in the discovery of novel drug candidates against resistant pathogens and other infectious agents.

A Critical Assessment on Calculating Vibrational Spectra in Nanostructured Materials

Vibrational spectroscopy is an omnipresent spectroscopic technique to characterize functional nanostructured materials such as zeolites, metal-organic frameworks (MOFs), and metal-halide perovskites (MHPs). The resulting experimental spectra are usually complex, with both low-frequency framework modes and high-frequency functional group vibrations. Therefore, theoretically calculated spectra are often an essential element to elucidate the vibrational fingerprint. In principle, there are two possible approaches to calculate vibrational spectra: (i) a static approach that approximates the potential energy surface (PES) as a set of independent harmonic oscillators and (ii) a dynamic approach that explicitly samples the PES around equilibrium by integrating Newton's equations of motions. The dynamic approach considers anharmonic and temperature effects and provides a more genuine representation of materials at true operating conditions; however, such simulations come at a substantially increased computational cost. This is certainly true when forces and energy evaluations are performed at the quantum mechanical level. Molecular dynamics (MD) techniques have become more established within the field of computational chemistry. Yet, for the prediction of infrared (IR) and Raman spectra of nanostructured materials, their usage has been less explored and remain restricted to some isolated successes. Therefore, it is currently not a priori clear which methodology should be used to accurately predict vibrational spectra for a given system. A comprehensive comparative study between various theoretical methods and experimental spectra for a broad set of nanostructured materials is so far lacking. To fill this gap, we herein present a concise overview on which methodology is suited to accurately predict vibrational spectra for a broad range of nanostructured materials and formulate a series of theoretical guidelines to this purpose. To this end, four different case studies are considered, each treating a particular material aspect, namely breathing in flexible MOFs, characterization of defects in the rigid MOF UiO-66, anharmonic vibrations in the metal-halide perovskite CsPbBr3, and guest adsorption on the pores of the zeolite H-SSZ-13. For all four materials, in their guest- and defect-free state and at sufficiently low temperatures, both the static and dynamic approach yield qualitatively similar spectra in agreement with experimental results. When the temperature is increased, the harmonic approximation starts to fail for CsPbBr3 due to the presence of anharmonic phonon modes. Also, the spectroscopic fingerprints of defects and guest species are insufficiently well predicted by a simple harmonic model. Both phenomena flatten the potential energy surface (PES), which facilitates the transitions between metastable states, necessitating dynamic sampling. On the basis of the four case studies treated in this Review, we can propose the following theoretical guidelines to simulate accurate vibrational spectra of functional solid-state materials: (i) For nanostructured crystalline framework materials at low temperature, insights into the lattice dynamics can be obtained using a static approach relying on a few points on the PES and an independent set of harmonic oscillators. (ii) When the material is evaluated at higher temperatures or when additional complexity enters the system, e.g., strong anharmonicity, defects, or guest species, the harmonic regime breaks down and dynamic sampling is required for a correct prediction of the phonon spectrum. These guidelines and their illustrations for prototype material classes can help experimental and theoretical researchers to enhance the knowledge obtained from a lattice dynamics study.

M11pz: A Nonlocal Meta Functional with Zero Hartree-Fock Exchange and with Broad Accuracy for Chemical Energies and Structures

The accuracy of Kohn-Sham density functional theory depends strongly on the approximation to the exchange-correlation functional. In this work, we present a new exchange-correlation functional called M11pz (M11 plus rung-3.5 terms with zero Hartree-Fock exchange) that is built on the M11plus functional with the goal of using its rung-3.5 terms without a Hartree-Fock exchange term, especially to improve the accuracy for strongly correlated systems. The M11pz functional is optimized with the same local and rung-3.5 ingredients that are used in M11plus but without any percentage of Hartree-Fock exchange. The performance of M11pz is compared with eight local functionals, and M11pz is found to be in top three when the errors or ranks are averaged over eight grouped and partially overlapping databases: AME418/22, atomic and molecular energies; MGBE172, main-group bond energies; TMBE40, transition-metal bond energies; SR309, single-reference systems; MR54, multireference systems; BH192, barrier heights; NC579, noncovalent interaction energies; and MS20, molecular structures. For calculations of band gaps of solids, M11pz is the second best of the nine tested functionals that have zero Hartree-Fock exchange.

A study of major cannabinoids via Raman spectroscopy and density functional theory

Cannabinoids, a class of molecules specific to the cannabis plant, are some of the most relevant molecules under study today due to their widespread use and varying legal status. Here, we present Raman spectra of a series of eleven cannabinoids and compare them to simulated spectra from density functional theory computations. The studied cannabinoids include three cannabinoid acids (Δ9-THC acid, CBD acid, and CBG acid) and eight neutral ones (Δ9-THC, CBD, CBG, CBDVA, CBDV, Δ8-THC, CBN and CBC). All cannabinoids have been isolated from cannabis plant gown at the University of Mississippi. The data presented in this work represents the most resolved experimental and highest-level simulated spectra available to date for each cannabinoid. All cannabinoids displayed higher peak separation in the experimental spectra than CBGA, which is most likely attributable to physical composition of the samples. The overall agreement between the experimental and simulated spectra is good, however for certain vibrational modes, especially those in the -OH stretching region, deviations are observed due to hydrogen bonding, suggesting that the OH stretching region is a good probe for decarboxylation reactions in these and related species.

Cluster-in-Molecule Local Correlation Method for Dispersion Interactions in Large Systems and Periodic Systems

ConspectusThe noncovalent interactions, including dispersion interactions, control the structures and stabilities of complex chemical systems, including host-guest complexes and the adsorption process of molecules on the solid surfaces. The density functional theory (DFT) with empirical dispersion correction is now the working horse in many areas of applications. Post-Hartree-Fock (post-HF) methods have been well recognized to provide more accurate descriptions in a systematic way. However, traditional post-HF methods are mainly limited to small- or medium-sized systems, and their applications to periodic condensed phase systems are still very limited due to their expensive computational costs.To extend post-HF calculations to large molecules, the cluster-in-molecule (CIM) local correlation approach has been established, allowing highly accurate electron correlation calculations that are routinely available for very large systems. In the CIM approach, the electron correlation energy of a large molecule could be obtained from electron correlation calculations on a series of clusters, each of which contains a subset of occupied and virtual localized molecular orbitals. The CIM method could be massively and efficiently parallelized on general computer clusters. The CIM method has been implemented at various electron correlation levels, including second-order Mo̷ller-Plesset perturbation theory (MP2), coupled cluster singles and doubles (CCSD), CCSD with perturbative triples correction [CCSD(T)], etc. The CIM-MP2 energy gradient algorithm was developed and applied to the geometry optimizations of large systems. The CIM method has also been extended to condensed-phase systems under periodic boundary conditions (PBC-CIM). For periodic systems, the correlation energy per unit cell could be evaluated with correlation energy contributions from a series of clusters that are built with localized Wannier functions.CIM-based electron correlation calculations have been employed to investigate a number of chemical problems in which the dispersion interaction is important. CIM-based post-HF methods including CIM domain-based local pair natural orbital (DLPNO) CCSD(T) are applied to compute the relative or binding energies of biological systems or supramolecular complexes, the reaction barrier in a relatively complex chemical reaction. The CIM-MP2 method is used to obtain the optimized geometry of large systems. CIM-based post-HF calculations have also been used to compute the cohesive energies of molecular crystals and adsorption energies of molecules on the solid surfaces. The CIM and its PBC variant are expected to become a powerful theoretical tool for accurate calculations of the energies and structures for a broad range of large systems and condensed-phase systems with significant dispersion interactions.

How important is the amount of exact exchange for spin-state energy ordering in DFT? Case study of molybdenum carbide cluster, Mo4C2

Since the form of the exact functional in density functional theory is unknown, we must rely on density functional approximations (DFAs). In the past, very promising results have been reported by combining semi-local DFAs with exact, i.e. Hartree-Fock, exchange. However, the spin-state energy ordering and the predictions of global minima structures are particularly sensitive to the choice of the hybrid functional and to the amount of exact exchange. This has been already qualitatively described for single conformations, reactions, and a limited number of conformations. Here, we have analyzed the mixing of exact exchange in exchange functionals for a set of several hundred isomers of the transition metal carbide, Mo4C2. The analysis of the calculated energies and charges using PBE0-type functional with varying amounts of exact exchange yields the following insights: (1) The sensitivity of spin-energy splitting is strongly correlated with the amount of exact exchange mixing. (2) Spin contamination is exacerbated when correlation is omitted from the exchange-correlation functional. (3) There is not one ideal value for the exact exchange mixing which can be used to parametrize or choose among the functionals. Calculated energies and electronic structures are influenced by exact exchange at a different magnitude within a given distribution; therefore, to extend the application range of hybrid functionals to the full periodic table the spin-energy splitting energies should be investigated.

CHNO - Formylnitrene, Cyanic, Isocyanic, Fulminic, and Isofulminic Acids and their Interrelationships at DFT and CASPT2 Levels of Theory

Fulminic and cyanic acids played a decisive role in the conception of isomerism 200 years ago. Cyanic (HOCN), isocyanic (HNCO), and fulminic (HCNO) acids have been detected in several interstellar sources, but isofulminic acid (HONC) is little known. Here we examine the interrelationships between the four acids and formylnitrene, HC(O)N, at the CASPT2 and three DFT levels. Formylnitrene has a triplet ground state, T0, a closed shell singlet (CSS), S0, and an open-shell singlet (OSS), S1, lying ∼7 and 27 kcal/mol above T0, respectively. The CSS is weakly stabilized by a 12 kcal/mol bond between the N and the O atoms. A conical intersection 12 kcal/mol above T0 permits easy T0-S0 interchange. Formyl azide and formylnitrene (T0 and S0) are isomerized thermally to HNCO. HOCN is best obtained via dissociation of the nitrene (or of HNCO) to H• + NCO• radicals ∼46 kcal/mol above the T0 nitrene. Isofulminic acid, HONC, isomerizes readily to cyanic acid, HOCN, in thermal and photochemical reactions. Fulminic acid, HCNO, can isomerize to HNCO via CSS formylnitrene. Easy tautomerization prevents the preparation of HOCN in quantity. The barrier to isomerization is strongly reduced in small hydrogen-bonded aggregates so that trace amounts of HOCN can exist in equilibrium with HNCO.

Accelerating the prediction of stable materials with machine learning

Despite the rise in computing power, the large space of possible combinations of elements and crystal structure types makes large-scale high-throughput surveys of stable materials prohibitively expensive, especially for complex materials and materials subject to environmental conditions such as finite temperature. When physics-based computational methods and labor-intensive experiments are not feasible, machine learning (ML) methods can be a rapid and powerful alternative. Owing to a wealth of experimental and first-principles data as well as improved ML frameworks designed for materials modeling, ML is shown to be effective in predicting stability parameters and accelerating the discovery of new stable materials. In this Review, we summarize the most recent advancements in applying ML methodologies in predicting materials stability, focusing particularly on predictions of zero- and finite-temperature stability. We also highlight the need for more ML development in predictions of other thermodynamic knobs, such as pressure and surface/interfacial energy, which practically impact materials stability.

A Readily Achieved Potentiostatic Method in Density Functional Theory Calculation for Improved Prediction of the Performance for Electrocatalytic Nitrogen Reduction Reaction

Accurate prediction of the catalytic performance of nitrogen reduction reaction catalysts based on density functional theory (DFT) calculation is of great significance for developing catalytic materials for nitrogen fixation. However, the applied electrode potential induced the fixation of Fermi level and solvation effect are commonly ignored in the current computational hydrogen electrode method, which leads to the large deviation between the calculation predicted limit potential and the experimentally measured limit potential. In this work, the simple external iteration method is proposed to simulate the Fermi level of the catalysts that are fixed by the applied electrode potential, along with the hybrid solvent model to describe the strong interaction, such as hydrogen bond, between the solvent molecules and the intermediates. This method allowed the theoretical and experimental limit potentials to be in good agreement, indicating the significant effect of the electrode potential and solvation in the DFT calculation. These results will guide the calculation-based prediction of other reaction systems in the field of electrocatalysis.

CRYSTAL23: A Program for Computational Solid State Physics and Chemistry

The Crystal program for quantum-mechanical simulations of materials has been bridging the realm of molecular quantum chemistry to the realm of solid state physics for many years, since its first public version released back in 1988. This peculiarity stems from the use of atom-centered basis functions within a linear combination of atomic orbitals (LCAO) approach and from the corresponding efficiency in the evaluation of the exact Fock exchange series. In particular, this has led to the implementation of a rich variety of hybrid density functional approximations since 1998. Nowadays, it is acknowledged by a broad community of solid state chemists and physicists that the inclusion of a fraction of Fock exchange in the exchange-correlation potential of the density functional theory is key to a better description of many properties of materials (electronic, magnetic, mechanical, spintronic, lattice-dynamical, etc.). Here, the main developments made to the program in the last five years (i.e., since the previous release, Crystal17) are presented and some of their most noteworthy applications reviewed.

Development of scalable and generalizable machine learned force field for polymers

Understanding and predicting the properties of polymers is vital to developing tailored polymer molecules for desired applications. Classical force fields may fail to capture key properties, for example, the transport properties of certain polymer systems such as polyethylene glycol. As a solution, we present an alternative potential energy surface, a charge recursive neural network (QRNN) model trained on DFT calculations made on smaller atomic clusters that generalizes well to oligomers comprising larger atomic clusters or longer chains. We demonstrate the validity of the polymer QRNN workflow by modeling the oligomers of ethylene glycol. We apply two rounds of active learning (addition of new training clusters based on current model performance) and implement a novel model training approach that uses partial charges from a semi-empirical method. Our developed QRNN model for polymers produces stable molecular dynamics (MD) simulation trajectory and captures the dynamics of polymer chains as indicated by the striking agreement with experimental values. Our model allows working on much larger systems than allowed by DFT simulations, at the same time providing a more accurate force field than classical force fields which provides a promising avenue for large-scale molecular simulations of polymeric systems.

The Best Models of Bodipy's Electronic Excited State: Comparing Predictions from Various DFT Functionals with Measurements from Femtosecond Stimulated Raman Spectroscopy

Density functional theory (DFT) and time-dependent DFT (TD-DFT) are pivotal approaches for modeling electronically excited states of molecules. However, choosing a DFT exchange-correlation functional (XCF) among the myriad of alternatives is an overwhelming task that can affect the interpretation of results and lead to erroneous conclusions. The performance of these XCFs to describe the excited-state properties is often addressed by comparing them with high-level wave function methods or experimentally available vertical excitation energies; however, this is a limited analysis that relies on evaluation of a single point in the excited-state potential energy surface (PES). Different strategies have been proposed but are limited by the difficulty of experimentally accessing the electronic excited-state properties. In this work, we have tested the performance of 12 different XCFs and TD-DFT to describe the excited-state potential energy surface of Bodipy (2,6-diethyl-1,3,5,7-tetramethyl-8-phenyldipyrromethene difluoroborate). We compare those results with resonance Raman spectra collected by using femtosecond stimulated Raman spectroscopy (FSRS). By simultaneously fitting the absorption spectrum, fluorescence spectrum, and all of the resonance Raman excitation profiles within the independent mode displaced harmonic oscillator (IMDHO) formalism, we can describe the PES at the Franck-Condon (FC) region and determine the solvent and intramolecular reorganization energy after relaxation. This allows a direct comparison of the TD-DFT output with experimental observables. Our analysis reveals that using vertical absorption energies might not be a good criterion to determine the best XCF for a given molecular system and that FSRS opens up a new way to benchmark the excited-state performance of XCFs of fluorescent dyes.

Nonlocal Functionals Inspired by the Strongly Interacting Limit of DFT: Exact Constraints and Implementation

Capturing strong correlation effects remains a key challenge for the development of improved exchange-correlation (XC) functionals in density functional theory. The recently proposed multiple radii functional (MRF) [J. Phys. Chem. Lett. 2017, 8, 2799; J. Chem. Theory Comput. 2019, 15, 3580] was designed to capture strong correlation effects seamlessly, as its mathematical structure draws from that of the exact XC functional in the limit of infinite correlations. The MRF functional provides a framework for building approximations along the density-fixed adiabatic connection, delivers accurate XC energy densities in the standard DFT gauge (same as that of the exact exchange energy density), and is free of one-electron self-interaction errors. To facilitate the development of XC functionals based on the MRF, we examine the behavior of the MRF functional when applied to uniform and scaled densities and consider how it can be made exact for the uniform electron gas. These theoretical insights are then used to build improved forms for the fluctuation function, an object that defines XC energy densities within the MRF framework. We also show how the MRF fluctuation function for physical correlation can be easily readjusted to accurately capture the XC functional in the limit of infinite correlations, demonstrating the versatility of MRF for building approximations for different correlation regimes. We describe the implementation of MRF using densities expanded on Gaussian basis sets, which improves the efficiency of previous grid-based MRF implementations.

Better performance of Hartree-Fock over DFT: a quantum mechanical investigation on pyridinium benzimidazolate types of zwitterions in the light of localization/delocalization issues

CONTEXT

With the advent of fast computing facilities, combined with rapid emerges of many new and intricate quantum mechanical functionals, computations with pure Hartree-Fock (HF) theory are now-a-days regarded as trivial or obsolete, or even considered as not reliable by many researchers. Consequently, current trends in computational chemistry show extensive use of post-HF theories for smaller molecular systems and various DFT methods for organic and inorganic chemistry related problems (larger molecules/systems). In this contribution, I have tried to show that sometimes, HF might be more suitable over DFT methodologies in addressing structure-property correlations. Molecules studied here were previously synthesized by Boyd in 1966 and important experimental data were produced by Alcalde and co-workers in 1987. Comparison of computed and experimental results clearly shows that HF method was more effective in reproducing the experimental data compared to especially the DFT methodologies. Reliability of HF method was further assured from the very similar results shown by the CCSD, CASSCF, CISD and QCISD methods. Current study also indicates that the localization issue associated with HF proved to be advantageous over delocalization issue of DFT based methodologies, in correctly describing the structure-property correlation for zwitterion systems.

METHODS

All computations were performed with Gaussian 09. A wide-range of quantum mechanical methodologies, HF, B3LYP, CAM-B3LYP, BMK, B3PW91, TPSSh, LC-ωPBE, M06-2X, M06-HF, ωB97xD, MP2, CASSCF, CCSD, QCISD, CISD and semi-empirical methods like, Huckel, CNDO, AM1, PM3MM and PM6, were used for investigations.

Nonempirical Range-Separated Hybrid Functional with Spatially Dependent Screened Exchange

Electronic structure calculations based on density functional theory (DFT) have successfully predicted numerous ground-state properties of a variety of molecules and materials. However, exchange and correlation functionals currently used in the literature, including semilocal and hybrid functionals, are often inaccurate to describe the electronic properties of heterogeneous solids, especially systems composed of building blocks with large dielectric mismatch. Here, we present a dielectric-dependent range-separated hybrid functional, screened-exchange range-separated hybrid (SE-RSH), for the investigation of heterogeneous materials. We define a spatially dependent fraction of exact exchange inspired by the static Coulomb-hole and screened-exchange (COHSEX) approximation used in many-body perturbation theory, and we show that the proposed functional accurately predicts the electronic structure of several nonmetallic interfaces, three- and two-dimensional, pristine, and defective solids and nanoparticles.

Stimulated Resonance Raman and Excited-State Dynamics in an Excitonically Coupled Bodipy Dimer: A Test for TD-DFT and the Polarizable Continuum Model

Bodipy is one of the most versatile and studied functional dyes due to its myriad applications and tunable spectral properties. One of the strategies to adjust their properties is the formation of Bodipy dimers and oligomers whose properties differ significantly from the corresponding monomer. Recently, we have developed a novel strategy for synthesizing α,α-ethylene-bridged Bodipy dimers; however, their excited-state dynamics was heretofore unknown. This work presents the ultrafast excited-state dynamics of a novel α,α-ethylene-bridge Bodipy dimer and its monomeric parent. The dimer's steady-state absorption and fluorescence suggest a Coulombic interaction between the monomeric units' transition dipole moments (TDMs), forming what is often termed a "J-dimer". The excited-state properties of the dimer were studied using molecular excitonic theory and time-dependent density functional theory (TD-DFT). We chose the M06 exchange-correlation functional (XCF) based on its ability to reproduce the experimental oscillator strength and resonance Raman spectra. Ultrafast laser spectroscopy reveals symmetry-breaking charge separation (SB-CS) in the dimer in polar solvents and the subsequent population of the charge-separated ion-pair state. The charge separation rate falls into the normal regime, while the charge recombination is in the inverted regime. Conversely, in nonpolar solvents, the charge separation is thermodynamically not feasible. In contrast, the monomer's excited-state dynamics shows no dependence on the solvent polarity. Furthermore, we found no evidence of significant structural rearrangement upon photoexcitation, regardless of the deactivation pathway. After an extensive analysis of the electronic transitions, we concluded that the solvent fluctuations in the local environment around the dimer create an asymmetry that drives and stabilizes the charge separation. This work sheds light on the charge-transfer process in this new set of molecular systems and how excited-state dynamics can be modeled by combining the experiment and theory.

Theoretical investigation on the functional group modulation of UV-Vis absorption profiles of triphenylamine derivatives

Understanding the functional group modulation of electronic structure and excitation is pivotal to the design of organic small molecules (OSMs) for photoelectric applications. In this study, we employed density functional theory (DFT) and time-dependent DFT (TDDFT) calculations to explore the unique absorption character of four triphenylamine photosensitizers. The various conformations were investigated given the multiple single bonds in the compounds, and the resemblance in the electronic structure of different conformations is affirmed because the coplanarity and consequent long-range conjugation is maintained regardless of the orientation of the flexible blocks. Six functionals were evaluated, and MN15 was found to successfully reproduce the intense secondary absorption peak for the double 3,4-ethylenedioxythiophene (EDOT) modified sensitizer over B3LYP, PBE0, M062X, CAM-B3LYP, and ωB97XD. The introduction of EDOT gives rise to a new excited state S4, which is a local excitation constrained in the EDOT substituent triphenylamine block. This new excited state S4, in combination with inherent S2 and S3 derived from prototype molecule TPA-Pyc, jointly contributes to the hump of the secondary absorption peak of ETE-Pyc and finally affects the light-harvesting ability of the dye-sensitized TiO2 photoanode. The current findings provide guidance toward the rational design of OSMs with good light-harvest ability.

Electronic Free Energy Surface of the Nitrogen Dimer Using First-Principles Finite Temperature Electronic Structure Methods

We use full configuration interaction and density matrix quantum Monte Carlo methods to calculate the electronic free energy surface of the nitrogen dimer within the free-energy Born-Oppenheimer approximation. As the temperature is raised from T = 0, we find a temperature regime in which the internal energy causes bond strengthening. At these temperatures, adding in the entropy contributions is required to cause the bond to gradually weaken with increasing temperature. We predict a thermally driven dissociation for the nitrogen dimer between 22,000 to 63,200 K depending on symmetries and basis set. Inclusion of more spatial and spin symmetries reduces the temperature required. The origin of these observations is explored using the structure of the density matrix at various temperatures and bond lengths.

Robust relativistic many-body Green's function based approaches for assessing core ionized and excited states

A two-component contour deformation (CD) based GW method that employs frequency sampling to drastically reduce the computational effort when assessing quasiparticle states far away from the Fermi level is outlined. Compared to the canonical CD-GW method, computational scaling is reduced by an order of magnitude without sacrificing accuracy. This allows for an efficient calculation of core ionization energies. The improved computational efficiency is used to provide benchmarks for core ionized states, comparing the performance of 15 density functional approximations as Kohn-Sham starting points for GW calculations on a set of 65 core ionization energies of 32 small molecules. Contrary to valence states, GW calculations on core states prefer functionals with only a moderate amount of Hartree-Fock exchange. Moreover, modern ab initio local hybrid functionals are also shown to provide excellent generalized Kohn-Sham references for core GW calculations. Furthermore, the core-valence separated Bethe-Salpeter equation (CVS-BSE) is outlined. CVS-BSE is a convenient tool to probe core excited states. The latter is tested on a set of 40 core excitations of eight small inorganic molecules. Results from the CVS-BSE method for excitation energies and the corresponding absorption cross sections are found to be in excellent agreement with those of reference damped response BSE calculations.

Barrier Heights for Diels-Alder Transition States Leading to Pentacyclic Adducts: A Benchmark Study of Crowded, Strained Transition States of Large Molecules

Theoretical characterization of reactions of complex molecules depends on providing consistent accuracy for the relative energies of intermediates and transition states. Here we employ the DLPNO-CCSD(T) method with core-valence correlation, large basis sets, and extrapolation to the CBS limit to provide benchmark values for Diels-Alder transition states leading to competitive strained pentacyclic adducts. We then used those benchmarks to test a diverse set of wave function and density functional methods for the absolute and relative barrier heights of these transition states. Our results show that only a few of the tested density functionals can predict the absolute barrier heights satisfactorily, although relative barrier heights are more accurate. The most accurate functionals tested are ωB97M-V, M11plus, ωB97X-V, PBE-D3(0), M11, and MN15 with MUDs from best estimates less than 3.0 kcal. These findings can guide selection of density functionals for future studies of crowded, strained transition states of large molecules.

Gauge-Invariant Excited-State Linear and Quadratic Response Properties within the Meta-Generalized Gradient Approximation

Gauge invariance is a fundamental symmetry connected to charge conservation and is widely accepted as indispensable for any electronic structure method. Hence, the gauge variance of the time-dependent kinetic energy density τ used in many meta-generalized gradient approximations (MGGAs) to the exchange-correlation (XC) functional presents a major obstacle for applying MGGAs within time-dependent density functional theory (TDDFT). Replacing τ by the gauge-invariant generalized kinetic energy density τ̂ significantly improves the accuracy of various functionals for vertical excitation energies [R. Grotjahn, F. Furche, and M. Kaupp. J. Chem. Phys. 2022, 157, 111102]. However, the dependence of the resulting current-MGGAs (cMGGAs) on the paramagnetic current density gives rise to new exchange-correlation kernels and hyper-kernels ignored in previous implementations of quadratic and higher-order response properties. Here we report the first implementation of cMGGAs and hybrid cMGGAs for excited-state gradients and dipole moments, as well as an extension to quadratic response properties including dynamic hyperpolarizabilities and two-photon absorption cross sections. In the first comprehensive benchmark study of MGGAs and cMGGAs for two-photon absorption cross sections, the M06-2X functional is found to be superior to the GGA hybrid PBE0. Additionally, two case studies from the literature for the practical prediction of nonlinear optical properties are revisited and potential advantages of hybrid (c)MGGAs compared to hybrid GGAs are discussed. The effect of restoring gauge invariance varies depending on the employed MGGA functional, the type of excitation, and the property under investigation: While some individual excited-state equilibrium structures are significantly affected, on average, these changes result in marginal improvements when compared against high-level reference data. Although the gauge-variant MGGA quadratic response properties are generally close to their gauge-invariant counterparts, the resulting errors are not bounded and significantly exceed typical method errors in some of the cases studied. Despite the limited effects seen in benchmark studies, gauge-invariant implementations of cMGGAs for excited-state properties are desirable from a fundamental perspective, entail little additional computational cost, and are necessary for response properties consistent with cMGGA linear response calculations such as excitation energies.

Protein Ca2+-Sites Prone to Sr2+ Substitution: Implications for Strontium Therapy

Strontium (Sr), an alkali metal with properties similar to calcium, in the form of soluble salts is used to treat osteoporosis. Despite the information accumulated on the role of Sr²⁺ as a Ca²⁺ mimetic in biology and medicine, there is no systematic study of how the outcome of the competition between the two dications depends on the physicochemical properties of (i) the metal ions, (ii) the first- and second-shell ligands, and (iii) the protein matrix. Specifically, the key features of a Ca²⁺-binding protein that enable Sr²⁺ to displace Ca²⁺ remain unclear. To address this, we studied the competition between Ca²⁺ and Sr²⁺ in protein Ca²⁺-binding sites using density functional theory combined with the polarizable continuum model. Our findings indicate that Ca²⁺-sites with multiple strong charge-donating protein ligands, including one or more bidentately bound Asp^-/Glu^- that are relatively buried and rigid are protected against Sr²⁺ attack. On the other hand, Ca²⁺-sites crowded with multiple protein ligands may be prone to Sr²⁺ displacement if they are solvent-exposed and flexible enough so that an extra backbone ligand from the outer shell can bind to Sr²⁺. In addition, solvent-exposed Ca²⁺ sites with only a few weak charge-donating ligands that can rearrange to fit the strontium's coordination requirements are susceptible to Sr²⁺ displacement. We provide the physical basis of these results and discuss potential novel protein targets of therapeutic Sr²⁺.

Realistic phase diagram of water from "first principles" data-driven quantum simulations

Since the experimental characterization of the low-pressure region of water's phase diagram in the early 1900s, scientists have been on a quest to understand the thermodynamic stability of ice polymorphs on the molecular level. In this study, we demonstrate that combining the MB-pol data-driven many-body potential for water, which was rigorously derived from "first principles" and exhibits chemical accuracy, with advanced enhanced-sampling algorithms, which correctly describe the quantum nature of molecular motion and thermodynamic equilibria, enables computer simulations of water's phase diagram with an unprecedented level of realism. Besides providing fundamental insights into how enthalpic, entropic, and nuclear quantum effects shape the free-energy landscape of water, we demonstrate that recent progress in "first principles" data-driven simulations, which rigorously encode many-body molecular interactions, has opened the door to realistic computational studies of complex molecular systems, bridging the gap between experiments and simulations.

Revealing specific transformation pattern of sulfonamides during wastewater biological treatment processes by molecular networking nontarget screening

Biotransformation of emerging contaminants (ECs) is of importance in various natural and engineered systems to eliminate the adverse effects of ECs toward organisms. In wastewater, structurally similar ECs may transform through similar reactions triggered by common enzymes. However, the transformation pattern for them was scarcely studied. To fill the research gaps, five sulfonamides were chosen as the targeted ECs with similar structure to explore the transformation pattern in wastewater biological treatment experiments at lab scale. Through molecular networking based nontarget screening, 45 transformation products (TPs) of sulfonamides were identified and 14 of them were newly found. On the basis, five specific transformation patterns were summarized for sulfonamides by transformation pathways comparing, reaction frequency analyzing and dominant TPs comparing. Results suggested that pterin-chelation and formylation (dominant transformation pathway) and acetylation, methylation and deamination reactions were commonly occurred for sulfonamides in wastewater. Among them, the role of formylation as the dominant transformation pathway for sulfonamides transformed in wastewater was firstly reported in present study. Subsequent frontier molecular orbital calculation suggested the active site of amino (N₁H₂-) may contribute the specific transformation pattern of sulfonamides. Present study reveals the specific transformation pattern of sulfonamides from the aspect of TPs and transformation pathways. In the future, knowledge on the specific transformation pattern can be used to regulate and enhance the removal of a class of ECs with similar structure rather than just one of ECs.

The entropic penalty for associative reactions and their physical treatment during routine computations

A systematic study of the entropic penalty for associative reactions is presented. It is shown that computed solution-phase Gibbs free energies typically overestimate entropic contributions. This entropic penalty for associative reactions in solution, i.e., if the number of particles decreases along the reaction coordinate (sum of stoichiometric numbers ), originates from the insufficient treatment of entropic effects by implicit solvent models. We propose an additive correction scheme to Gibbs free energies that is suitable for routine applications by non-expert users. This correction is based on Garza's formalism for the solution-phase entropy [A. J. Garza, J. Chem. Theory Comput., 2019, 15, 3204.] that is physically sound and embedded into an efficient black-box type algorithm. To critically evaluate the entropic penalty and its proposed treatment, we compiled an experimental benchmark set of 31 Δ_rG and 22 in 15 different solvents. Using a representative best-practice computational protocol (at wave function theory (WFT) based DLPNO-CCSD(T) and density functional theory (DFT) based revDSD-PBEP86-D4 level with an implicit solvent model), we determined a sizeable entropic penalty ranging from 2-11 kcal mol^-1. Using the correction scheme presented herein, the entropic penalty is corrected to the chemical accuracy of ≤1 kcal mol^-1 (WFT and DFT). The same applies to at the WFT level. Barriers at the DFT level are overestimated by 2 kcal mol^-1 (classic) and underestimated by 2 kcal mol^-1 (corrected). This effect is attributed to the finding that barriers computed at the DFT level are systematically 2-3 kcal mol^-1 lower than barriers obtained with WFT.

Computational Approaches for Organic Semiconductors: From Chemical and Physical Understanding to Predicting New Materials

While a complete understanding of organic semiconductor (OSC) design principles remains elusive, computational methods─ranging from techniques based in classical and quantum mechanics to more recent data-enabled models─can complement experimental observations and provide deep physicochemical insights into OSC structure-processing-property relationships, offering new capabilities for in silico OSC discovery and design. In this Review, we trace the evolution of these computational methods and their application to OSCs, beginning with early quantum-chemical methods to investigate resonance in benzene and building to recent machine-learning (ML) techniques and their application to ever more sophisticated OSC scientific and engineering challenges. Along the way, we highlight the limitations of the methods and how sophisticated physical and mathematical frameworks have been created to overcome those limitations. We illustrate applications of these methods to a range of specific challenges in OSCs derived from π-conjugated polymers and molecules, including predicting charge-carrier transport, modeling chain conformations and bulk morphology, estimating thermomechanical properties, and describing phonons and thermal transport, to name a few. Through these examples, we demonstrate how advances in computational methods accelerate the deployment of OSCsin wide-ranging technologies, such as organic photovoltaics (OPVs), organic light-emitting diodes (OLEDs), organic thermoelectrics, organic batteries, and organic (bio)sensors. We conclude by providing an outlook for the future development of computational techniques to discover and assess the properties of high-performing OSCs with greater accuracy.

Mechanistic Understanding and Reactivity Analyses for the Photochemistry of Disubstituted Tetrazoles

The photolysis of tetrazoles has undergone extensive research. However, there are still some problems to be solved in terms of mechanistic understanding and reactivity analyses, which leaves room for theoretical calculations. Herein, multiconfiguration perturbation theory at the CASPT2//CASSCF level was employed to account for electron correction effects involved in the photolysis of four disubstituted tetrazoles. Based on calculations of vertical excitation properties and evaluations of intersystem crossing (ISC) efficiencies in the Frank-Condon region, the combination of space and electronic effects is found in maximum-absorption excitation. Two types of ISC (¹ππ* → ³nπ*, ¹ππ* → ³ππ*) are determined in disubstituted tetrazoles, and the obtained rates follow the El-Sayed rule. Through mapping three representative types of minimum energy profiles for the photolysis of 1,5-, and 2,5-disubstituted tetrazoles, a conclusion can be drawn that the photolysis of tetrazoles exhibits reactivity characteristic of bond-breaking selectivity. Kinetic evaluations show that the photogeneration of singlet imidoylnitrene operates predominately over that in the triplet state, which can be confirmed by a double-well model in the triplet potential energy surface of 1,5-disubstituted tetrazole. Similar mechanistic explorations and reactivity analyses were also applied to the photolysis of 2,5-disubstituted tetrazole to unveil fragmentation patterns of nitrile imine generation. All computational efforts allow us to better understand the photoreactions of disubstituted tetrazoles and to provide useful strategies for regulating their unique reactivity.

Modeling of magnesium-decorated graphene quantum dot nanostructure for trapping AsH3, PH3 and NH3 gases

A magnesium-decorated graphene quantum dot (C₂₄H₁₂-Mg) surface has been examined theoretically using density functional theory (DFT) computations at the ωB97XD/6-311++G(2p,2d) level of theory to determine its sensing capability toward XH₃ gases, where X = As, N and P, in four different phases: gas, benzene solvent, ethanol solvent and water. This research was carried out in different phases in order to predict the best possible phase for the adsorption of the toxic gases. Analysis of the electronic properties shows that in the different phases the energy gap follows the order NH₃@C₂₄H₁₂-Mg < PH₃@C₂₄H₁₂-Mg < AsH₃@C₂₄H₁₂-Mg. The results obtained from the adsorption studies show that all the calculated adsorption energies are negative, indicating that the nature of the adsorption is chemisorption. The adsorption energies can be arranged in an increasing trend of NH₃@C₂₄H₁₂-Mg < PH₃@C₂₄H₁₂-Mg < AsH₃@C₂₄H₁₂-Mg. The best adsorption performance was noted in the gas phase compared to the other studied counterparts. The interaction between the adsorbed gases and the surfaces shows a non-covalent interaction nature, as confirmed by the quantum theory of atoms-in-molecules (QTAIM) and non-covalent interactions (NCI) analysis. The overall results suggest that we can infer that the surface of the magnesium-decorated graphene quantum dot C₂₄H₁₂-Mg is more efficient for sensing the gas AsH₃ than PH₃ and NH₃.

Comparison of the Performance of Density Functional Methods for the Description of Spin States and Binding Energies of Porphyrins

This work analyzes the performance of 250 electronic structure theory methods (including 240 density functional approximations) for the description of spin states and the binding properties of iron, manganese, and cobalt porphyrins. The assessment employs the Por21 database of high-level computational data (CASPT2 reference energies taken from the literature). Results show that current approximations fail to achieve the "chemical accuracy" target of 1.0 kcal/mol by a long margin. The best-performing methods achieve a mean unsigned error (MUE) <15.0 kcal/mol, but the errors are at least twice as large for most methods. Semilocal functionals and global hybrid functionals with a low percentage of exact exchange are found to be the least problematic for spin states and binding energies, in agreement with the general knowledge in transition metal computational chemistry. Approximations with high percentages of exact exchange (including range-separated and double-hybrid functionals) can lead to catastrophic failures. More modern approximations usually perform better than older functionals. An accurate statistical analysis of the results also casts doubts on some of the reference energies calculated using multireference methods. Suggestions and general guidelines for users are provided in the conclusions. These results hopefully stimulate advances for both the wave function and the density functional side of electronic structure calculations.

A Comprehensive Investigation into the Crystallology, Molecule, and Quantum Chemistry Properties of Two New Hydrous Long-Chain Dibasic Ammonium Salts CnH2n+8N2O6 (n = 35 and 37)

Through the salification reaction of carboxylation, successful attachment of the long-chain alkanoic acid to the two ends of 1,3-propanediamine was realized, which enabled the doubling of the long-chain alkanoic acid carbon chain. Hydrous 1,3-propanediamine dihexadecanoate (abbreviated as 3C16) and 1,3-propanediamine diheptadecanoate (abbreviated as 3C17) were synthesized afterward, and their crystal structures were characterized by the X-ray single crystal diffraction technique. By analyzing their molecular and crystal structure, their composition, spatial structure, and coordination mode were determined. Two water molecules played important roles in stabilizing the framework of both compounds. Hirshfeld surface analysis revealed the intermolecular interactions between the two molecules. The 3D energy framework map presented the intermolecular interactions more intuitively and digitally, in which dispersion energy plays a dominant role. DFT calculations were performed to analyze the frontier molecular orbitals (HOMO–LUMO). The energy difference between the HOMO–LUMO is 0.2858 eV and 0.2855 eV for 3C16 and 3C17, respectively. DOS diagrams further confirmed the distribution of the frontier molecular orbitals of 3C16 and 3C17. The charge distributions in the compounds were visualized using a molecular electrostatic potential (ESP) surface. ESP maps indicated that the electrophilic sites are localized around the oxygen atom. The crystallographic data and parameters of quantum chemical calculation in this paper will provide data and theoretical support for the development and application of such materials.

Why Is Quantum Chemistry So Complicated?

The myriad tools of quantum chemistry are now widely used by a diverse community of chemists, biologists, physicists, and material scientists. The large number of methods (e.g., Hartree-Fock, density functional theory, configuration interaction, perturbation theory, coupled-clusters, equations of motion, Green's functions, and more) and the multitude of atomic orbital basis sets often give rise to consternation and confusion. In this Perspective, I explain why quantum chemistry has so many different methods and why researchers should understand their relative strengths and weaknesses. I explain how chemistry's use of orbitals and the need for wave functions to be antisymmetric causes computational-effort scaling proportional to the cube or higher power of the number of orbitals. I also illustrate how the fact that the Schrödinger equation's energies are extensive makes it difficult to extract intensive properties such as bond and excitation energies, ionization potentials, and electron affinities.

Projected Hybrid Density Functionals: Method and Application to Core Electron Ionization

This work introduces a new class of hybrid density functional theory (DFT) approximations, which incorporate different fractions of nonlocal exact exchange in predefined states such as core atomic orbitals (AOs). These projected hybrid density functionals are related to range-separated hybrid functionals, which incorporate different fractions of nonlocal exchange at different electron-electron separations. This work derives projected hybrids using the Adiabatic Projection formalism. One projects the electron-electron interaction operator onto the chosen predefined states, introduces the projected operator into the noninteracting Kohn-Sham reference system, and employs a formally exact density functional to model the remaining electron-electron interactions. Projected hybrids, like range-separated hybrids, approximate the partially interacting reference system's ground-state wave function as a single Slater determinant. Projected hybrids are readily implemented into existing density functional codes, requiring only a projection of the one-particle density matrices and exchange operators entering existing routines. This work also presents an application to core electron ionization. Projecting onto core atomic orbitals allows us to introduce additional nonlocal exchange into atomic core regions. This reduces the impact of self-interaction error on computed core electron properties. Benchmark studies are reported for PBE0c70, a core-projected variant of the Perdew-Burke-Ernzerhof global hybrid PBE0, in which the fraction of nonlocal exchange is increased from 25% to 70% in atomic core regions. PBE0c70-predicted core orbital energies accurately recover nonrelativistic core-electron binding energies of second-period elements Li-Ne and third-period elements Na-Ar, without degrading the good performance of PBE0 for atomization energies and valence ionization potentials.

Redox-active ligands as a challenge for electronic structure methods

To improve the catalytic activity of 3d transition metal catalysts, redox-active ligands are a promising tool. These ligands influence the oxidation state of the metal center as well as the ground spin-state and make the experimental determination of both properties challenging. Therefore, first-principles calculations, in particular employing density functional theory with a proper choice of exchange-correlation (xc) functional, are crucial. Common xc functionals were tested on a simple class of metal complexes: homoleptic, octahedral tris(diimine) iron(II) complexes. The spin-state energy splittings for most of these complexes showed the expected linear dependence on the amount of exact exchange included in the xc functionals. Even though varying redox-activity affects the electronic structure of the complexes considerably, the sensitivity of the spin-state energetics to the exact exchange admixture is surprisingly small. For iron(II) complexes with highly redox-active ligands and for a broad range of ligands in the reduced tris(diimine) iron(I) complexes, self-consistent field convergence to local minima was observed, which differ from the global minimum in the redox state of the ligand. This may also result in convergence to a molecular structure that corresponds to an energetically higher-lying local minimum. One criterion to detect such behavior is a change in the sign of the slope for the dependence of the spin-state energy splittings on the amount of exact exchange. We discuss possible protocols for dealing with such artifacts in cases in which a large number of calculations makes checking by hand unfeasible.