Assessment of the applicability of DFT methods to [Cp*Rh]-catalyzed hydrogen evolution processes

The present computational study provides a benchmark of density functional theory (DFT) methods in describing hydrogen evolution processes catalyzed by [Cp*Rh]-containing organometallic complexes. A test set was composed of 26 elementary reactions featuring chemical transformations and bonding situations essential for the field, including the emerging concept of non-innocent Cp* behavior. Reference values were obtained from a highly accurate 3/4 complete basis set and 6/7 complete PNO space extrapolated DLPNO-CCSD(T) energies. The performance of lower-level extrapolation procedures was also assessed. We considered 84 density functionals (DF) (including 13 generalized gradient approximations (GGA), nine meta-GGAs, 33 hybrids, and 29 double-hybrids) and three composite methods (HF-3c, PBEh-3c, and r2SCAN-3c), combined with different types of dispersion corrections (D3(0), D3BJ, D4, and VV10). The most accurate approach is the PBE0-DH-D3BJ (MAD of 1.36 kcal mol-1) followed by TPSS0-D3BJ (MAD of 1.60 kcal mol-1). Low-cost r2SCAN-3c composite provides a less accurate but much faster alternative (MAD of 2.39 kcal mol-1). The widely used Minnesota-family M06-L, M06, and M06-2X DFs should be avoided (MADs of 3.70, 3.94, and 4.01 kcal mol-1, respectively).

Fast and Robust Modeling of Lanthanide and Actinide Complexes, Biomolecules, and Molecular Crystals with the Extended GFN-FF Model

Lanthanides (Ln) and actinides (An) have recently become important tools in biomedical and materials science. However, the development of computational methods able to describe such elements in various environments has not kept up with the pace of the field. Addressing this challenge, this work introduces and showcases an extension of the GFN-FF to An alongside a reparameterization for Ln. This development fills a gap for fast computational methods that are out-of-the-box applicable to large f-element-containing systems with thousands of atoms. We discuss the reparameterization of the charge model and the covalent topology setup and showcase the model through various applications: Molecular dynamics simulations, optimization of Ln-containing biomolecules, and optimizations of several periodic structures. With the presented improvements, GFN-FF is a powerful method that routinely delivers robust and accurate geometries for large Ln/An systems with thousands of atoms.

Triantaspirols A-C and Paraphaeolactone Cs from Paraphaeosphaeria sp. KT4192: Sensitivity of CP3 in Distinguishing Close NMR Signals

Hybridized spirobisnaphthalene derivatives, triantaspirols A-C (1-3) and paraphaeolactones C1 and C2 (4 and 5), were identified from the culture broth of the fungus Paraphaeosphaeria sp. KT4192. The NMR spectra of 2 and 3, as well as 4 and 5, closely resembled each other, indicating that these were pairs of diastereomers. Although this NMR spectral resemblance made it challenging to distinguish their relative configurations, detailed analysis of the electronic circular dichroism (ECD) spectra and NOE correlations allowed us to deduce them. The CP3 metric with the DFT-based NMR chemical shifts was found to distinguish configurations of diastereomers in a highly sensitive and accurate manner that DP4 could not account for because of the very close chemical shift differences in the experimental NMR spectra. The reliability of this method was assessed using 23 published examples which could not be distinguished by DP4 protocol.

A Critical Evaluation of the Hybrid KS DFT Functionals Based on the KS Exchange-Correlation Potentials

We have developed a critical methodology for the evaluation of the quality of hybrid exchange-correlation (XC) density functional approximations (DFAs) based on very fundamental quantities, i.e., Kohn-Sham (KS) XC potentials, self-consistent electron densities, first ionization potentials (IPs), and total energies. Since the XC potentials, the primary objects in the current study, are not directly accessible for the hybrids, we calculate them by inverting the KS electron densities. Utilizing this methodology, we tested 155 hybrid DFAs available in the LIBXC library using FCI and CCSD(T) methods as a reference. We have found that a group of functionals produces very decent XC potentials, mainly those with a large mixture of Hartree-Fock exchange. Moreover, the value of IP strongly depends on the XC potential quality. On the other hand, we show that the XC energy is dominated by functional-driven error, which in some cases leads to substantial errors in electronic densities. The study shows new directions for constructing more accurate XC functionals within the KS-DFT framework.

Cu(II) Coordination Polymers for the Selective Oxidation of Biomass-Derived Veratryl Alcohol in Green Solvents: A Sustainable Catalytic Approach

Four air-stable one-dimensional copper(II) coordination polymers (CP1-CP4) with azide linkers were synthesized using tridentate NNS and NNN ligands. Single-crystal X-ray diffraction (XRD) analysis confirmed the molecular structures of CP1, CP3, and CP4. In the presence of TEMPO, all four coordination polymers demonstrated effective catalytic activity for the selective aerobic oxidation of veratryl alcohol, a biomass model compound, under base-free conditions. CP4 exhibited the best catalytic efficiency. Oxidations were conducted at ambient temperature (40 °C) utilizing air as a sustainable oxidant. Selective oxidation of veratryl alcohol to veratraldehyde was also conducted in the presence of a catalytic amount of base (5 mol %), and enhanced reactivity was observed. The green solvents, acetone, and water, were used to maximize sustainability. The optimized reaction conditions were applied to broaden the substrate scope of various lignin model alcohols and substituted benzylic alcohols with wide electronic variability. CP4 exhibited high recyclability, consistently providing quantitative yields even after ten consecutive runs. The catalytic protocol demonstrated sustainability and environmental compatibility, as evidenced by a low E-factor (4.29) and a high Eco-scale score (90). Based on experimental evidence and theoretical calculations, a plausible catalytic cycle was proposed. Finally, the sustainability credentials of the different optimized reaction protocols were evaluated using the CHEM21 green metrics toolkit.

Exploring non-covalent interactions in excited states: beyond aromatic excimer models

Time-dependent density functional theory (TD-DFT) offers a relatively accurate and inexpensive approach for excited state calculations. However, conventional TD-DFT may suffer from the same poor description of non-covalent interactions (NCIs) which is known from ground-state DFT. In this work we present a comprehensive benchmark study of TD-DFT for excited-state NCIs. This is achieved by calculating dissociation curves for excited complexes ('exciplexes'), whose binding strength depends on excited-state NCIs including electrostatics, Pauli repulsion, charge-transfer, and London dispersion. Reference dissociation curves are calculated with the reasonably accurate wave function method SCS-CC2/CBS(3,4) which is used to benchmark a range of TD-DFT methods. Additionally, we test the effect of ground-state dispersion corrections, DFT-D3(BJ) and VV10, for exciplex binding. Overall, we find that TD-DFT methods generally under-bind exciplexes which can be explained by the missing dispersion forces. Underbinding errors reduce going up the rungs of Jacob's ladder. Further, the D3(BJ) dispersion correction is essential for good accuracy in most cases. Likewise, the VV10-type non-local kernel yields relatively low errors and has comparable performance in either its fully self-consistent implementation or as a post-SCF additive correction, but its impact is solely on ground-state energies and not on excitation energies. From our analysis, the most robust TD-DFT methods for exciplexes with localised excitations in their equilibrium and non-equilibrium geometries are the double hybrids B2GP-PLYP-D3(BJ) and B2PLYP-D3(BJ). Their range-separated versions ωB2(GP-)PLYP-D3(BJ) or the spin-opposite scaled, range-separated double hybrid SOS-ωB88PP86 can be recommended when charge transfer plays a role in the excitations. We also identify the need for a state-specific dispersion correction as the next step for improved TD-DFT performance.

Enhanced ClNO2 Formation at the Interface of Sea-Salt Aerosol

The reactive uptake of N2O5 on sea-spray aerosol plays a key role in regulating the NOx concentration in the troposphere. Despite numerous field and laboratory studies, a microscopic understanding of its heterogeneous reactivity remains unclear. Here, we use molecular simulation and theory to elucidate the chlorination of N2O5 to form ClNO2, the primary reactive channel within sea-spray aerosol. We find that the formation of ClNO2 is markedly enhanced at the air-water interface due to the stabilization of the charge-delocalized transition state, as evident from the formulation of bimolecular rate theory in heterogeneous environments. We explore the consequences of the enhanced interfacial reactivity in the uptake of N2O5 using numerical solutions of molecular reaction-diffusion equations as well as their analytical approximations. Our results suggest that the current interpretation of aerosol branching ratios needs to be revisited.

Toward Reliable Conformational Energies of Amino Acids and Dipeptides─The DipCONFS Benchmark and DipCONL Datasets

Simulating peptides and proteins is becoming increasingly important, leading to a growing need for efficient computational methods. These are typically semiempirical quantum mechanical (SQM) methods, force fields (FFs), or machine-learned interatomic potentials (MLIPs), all of which require a large amount of accurate data for robust training and evaluation. To assess potential reference methods and complement the available data, we introduce two sets, DipCONFL and DipCONFS, which cover large parts of the conformational space of 17 amino acids and their 289 possible dipeptides in aqueous solution. The conformers were selected from the exhaustive PeptideCS dataset by Andris et al. [ J. Phys. Chem. B 2022, 126, 5949-5958]. The structures, originally generated with GFN2-xTB, were reoptimized using the accurate r2SCAN-3c density functional theory (DFT) composite method including the implicit CPCM water solvation model. The DipCONFS benchmark set contains 918 conformers and is one of the largest sets with highly accurate coupled cluster conformational energies so far. It is employed to evaluate various DFT and wave function theory (WFT) methods, especially regarding whether they are accurate enough to be used as reliable reference methods for larger datasets intended for training and testing more approximated SQM, FF, and MLIP methods. The results reveal that the originally provided BP86-D3(BJ)/DGauss-DZVP conformational energies are not sufficiently accurate. Among the DFT methods tested as an alternative reference level, the revDSD-PBEP86-D4 double hybrid performs best with a mean absolute error (MAD) of 0.2 kcal mol-1 compared with the PNO-LCCSD(T)-F12b reference. The very efficient r2SCAN-3c composite method also shows excellent results, with an MAD of 0.3 kcal mol-1, similar to the best-tested hybrid ωB97M-D4. With these findings, we compiled the large DipCONFL set, which includes over 29,000 realistic conformers in solution with reasonably accurate r2SCAN-3c reference conformational energies, gradients, and further properties potentially relevant for training MLIP methods. This set, also in comparison to DipCONFS, is used to assess the performance of various SQM, FF, and MLIP methods robustly and can complement training sets for those.

van der Waals Radii of Free and Bonded Atoms from Hydrogen (Z = 1) to Oganesson (Z = 118)

Reliable numerical values of van der Waals (vdW) radii are required for constructing empirical force fields, vdW-inclusive density functional, and quantum-chemical methods, as well as for implicit solvent models. However, multiple definitions exist for vdW radii, involving either equilibrium or the closest contact distances between free or bonded atoms within molecules or crystals. For the paradigmatic case of the hydrogen atom, its reported vdW radius fluctuates between 2.15 and 3.70 Bohr depending on the definition, leading to a high uncertainty in calculations and different conceptual interpretations of noncovalent interactions. In this work, we systematically review different definitions and methodologies to establish the free and bonded vdW radii for hydrogen, based on equilibrium vdW distances in noncovalently bonded molecules, enveloping electron density cutoffs, noncovalent positron bonds in hydrogen anion dimer, vacuum virtual photon cloud caused by the hydrogen atom, and atomic dipole polarizability. By doing so, we show that the vdW radius of the free hydrogen atom is 3.16 ± 0.06 Bohr. By employing the most general and elegant definition of atomic vdW radius as a function of the atomic polarizability, we tabulate consistent values of vdW radii for all atoms in the periodic table up to Z = 118.

How accurate can Kohn-Sham density functional be for both main-group and transition metal reactions

Achieving chemical accuracy in describing reactions involving both main-group elements and transition metals poses a substantial challenge for density functional approximations (DFAs), primarily due to the significantly different behaviors for electrons moving in the s,p-orbitals or in the d,f-orbitals. MOR41, a representative dataset of transition metal chemistry, has highlighted the PWPB95-D3(BJ) functional, a B2PLYP-type doubly hybrid (bDH) approximation equipped with an empirical dispersion correction, as the leading functional thus far (Dohm et al., J Chem Theory Comput 2018;14: 2596-2608). However, this functional is not among the top bDH methods for main-group chemistry (Goerigk et al., Phys Chem Chem Phys. 2017;19: 32184). Conversely, bDH methods such as DSD-BLYP-D3, proficient in main-group chemistry, often falter for transition metal chemistry. Herein, taking advantage of the home-made Rust-based Electronic-Structure Toolkits, we examine a suite of XYG3-type doubly hybrid (xDH) methods. We confirm that the trade-off in descriptive accuracy between main-group and transition metal systems persists within the realm of perturbation theory (PT2)-based xDH methods. Notably, however, our study ushers in a pivotal advance with the recently proposed renormalized xDH method, R-xDH7-SCC15. This method not only distinguishes itself among the elite methods for main-group chemistry, but also achieves an unprecedented accuracy for the MOR41 dataset, outperforming all other reported DFAs. The efficacy of R-xDH7-SCC15 stems from the successful integration of a renormalized PT2 correlation model (rPT2) and a machine-learning strong-correlation correction (SCC15), marking a significant step forward in the realm of computational chemistry.

Toward Efficient and Unified Treatment of Static and Dynamic Correlations in Generalized Kohn-Sham Density Functional Theory

Accurate description of the static correlation poses a persistent challenge in electronic structure theory, particularly when it has to be concurrently considered with the dynamic correlation. We develop here a method in the generalized Kohn-Sham density functional theory (DFT) framework, named R-xDH7-SCC15, which achieves an unprecedented accuracy in capturing the static correlation, while maintaining a good description of the dynamic correlation on par with the state-of-the-art DFT and wave function theory methods, all grounded in the same single-reference black-box methodology. Central to R-xDH7-SCC15 is a general-purpose static correlation correction (SCC) model applied to the renormalized XYG3-type doubly hybrid method (R-xDH7). The SCC model development involves a hybrid machine learning strategy that integrates symbolic regression with nonlinear parameter optimization, aiming to achieve a balance between generalization capability, numerical accuracy, and interpretability. Extensive benchmark studies confirm the robustness and broad applicability of R-xDH7-SCC15 across a diverse array of main-group chemical scenarios. Notably, it displays exceptional aptitude in accurately characterizing intricate reaction kinetics and dynamic processes in regions distant from equilibrium, where the influence of static correlation is most profound. Its capability to consistently and efficiently predict the whole energy profiles, activation barriers, and reaction pathways within a user-friendly "black-box" framework represents an important advance in the field of electronic structure theory.

Spin parameter optimization for spin-polarized extended tight-binding methods

We present an optimization strategy for atom-specific spin-polarization constants within the spin-polarized GFN2-xTB framework, aiming to enhance the accuracy of molecular simulations. We compare a sequential and global optimization of spin parameters for hydrogen, carbon, nitrogen, oxygen, and fluorine. Sensitivity analysis using Sobol indices guides the identification of the most influential parameters for a given reference dataset, allowing for a nuanced understanding of their impact on diverse molecular properties. In the case of the W4-11 dataset, substantial error reduction was achieved, demonstrating the potential of the optimization. Transferability of the optimized spin-polarization constants over different properties, however, is limited, as we demonstrate by applying the optimized parameters on a set of singlet-triplet gaps in carbenes. Further studies on ionization potentials and electron affinities highlight some inherent limitations of current extended tight-binding methods that can not be resolved by simple parameter optimization. We conclude that the significantly improved accuracy strongly encourages the present re-optimization of the spin-polarization constants, whereas the limited transferability motivates a property-specific optimization strategy.

Graphene in Water is Hardly Ever Neutral

Graphene in water is electrically charged in most conditions. The level of charge can be large enough to stabilize single (or few) layer graphene colloidal dispersions in water, without the need of using any other additive. In this work, potentiometric titration, isothermal titration calorimetry, electrokinetic measurements, Density Functional Theory calculations, Raman Spectroscopy, and direct force measurements using Atomic Force Microscopy to investigate this charge and explore its origin are combined. The body of data collected suggests that this charge is a consequence of the interaction between water ions (hydroxide and hydronium) and graphene, and can be conveniently tuned (in magnitude and sign) by changing the pH of water.

Dynamic and solid-state behaviour of bromoisotrianglimine

Solid-state materials formed from discrete imine macrocycles have potential in industrial separations, but dynamic behaviour during both synthesis and crystallisation makes them challenging to exploit. Here, we explore opportunities for structural control by investigating the dynamic nature of a C-5 brominated isotrianglimine in solution and under crystallisation conditions. In solution, the equilibrium between the [3 + 3] and the less reported [2 + 2] macrocycle was investigated, and both macrocycles were fully characterised. Solvent templating during crystallisation was used to form new packing motifs for the [3 + 3] macrocycle and a previously unreported [4 + 4] macrocycle. Finally, chiral self-sorting was used to demonstrate how crystallisation conditions can not only influence packing arrangements but also shift the macrocycle equilibrium to yield new structures. This work thus exemplifies three strategies for exploiting dynamic behaviour to form isotrianglimine materials, and highlights the importance of understanding the dynamic behaviour of a system when designing and crystallising functional materials formed using dynamic covalent chemistry.

Getting the intermolecular forces correct: introducing the ASTA strategy for a water model

Having a force field for water providing good bulk properties is paramount for modern studies of most biological systems. Some of the most common three-site force fields are TIP3, SPC/ε or OPC3, providing a decent range of bulk properties. That does not mean though, that they have realistic inter-atomic forces. These force fields have been parameterized with a top-down approach, meaning, by fitting the force field parameters to the experimental bulk properties. This approach has been the governing strategy also for many variants of four- and more-site models. We test a bottom-up approach, in which the force field is parameterized by optimizing the non-bonded inter-atomic forces. Our philosophy is that correct inter-atomic forces lead to correct geometrical and dynamical properties. The first system we try to optimize with the accurately system tailored atomic (ASTA) approach is water, but we aim to eventually probe other systems in the future as well. We applied our ASTA strategy to find a good set of parameters providing accurate bulk properties for the simple three-site force field forms, and also for AMOEBA, a more detailed and polarizable force field. Even though our bottom-up approach did not provide satisfactory results for the simple three-site force fields (with fixed charges), for the case of the AMOEBA force field it led to a modification of the original strategy, giving very good intra- and inter-molecular forces, as compared to accurate quantum chemically calculated reference forces. At the same time, important bulk properties, in this study restricted to the density and diffusion, were accurately reproduced with respect to the experimental values.

Combined Multireference-Multiscale Approach to the Description of Photosynthetic Reaction Centers

A first-principles description of the primary photochemical processes that drive photosynthesis and sustain life on our planet remains one of the grand challenges of modern science. Recent research established that explicit incorporation of protein electrostatics in excited-state calculations of photosynthetic pigments, achieved for example with quantum-mechanics/molecular-mechanics (QM/MM) approaches, is essential for a meaningful description of the properties and function of pigment-protein complexes. Although time-dependent density functional theory has been used productively so far in QM/MM approaches for the study of such systems, this methodology has limitations. Here we pursue for the first time a QM/MM description of the reaction center in the principal enzyme of oxygenic photosynthesis, Photosystem II, using multireference wave function theory for the high-level QM region. We identify best practices and establish guidelines regarding the rational choice of active space and appropriate state-averaging for the efficient and reliable use of complete active space self-consistent field (CASSCF) and the N-electron valence state perturbation theory (NEVPT2) in the prediction of low-lying excited states of chlorophyll and pheophytin pigments. Given that the Gouterman orbitals are inadequate as a minimal active space, we define specific minimal and extended active spaces for the NEVPT2 description of electronic states that fall within the Q and B bands. Subsequently, we apply our multireference-QM/MM protocol to the description of all pigments in the reaction center of Photosystem II. The calculations reproduce the electrochromic shifts induced by the protein matrix and the ordering of site energies consistent with the identity of the primary donor (ChlD1) and the experimentally known asymmetric and directional electron transfer. The optimized protocol sets the stage for future multireference treatments of multiple pigments, and hence for multireference studies of charge separation, while it is transferable to the study of any photoactive embedded tetrapyrrole system.

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.

A nucleophilic beryllyl complex via metathesis at [Be-Be]2

Owing to its high toxicity, the chemistry of element number four, beryllium, is poorly understood. However, as the lightest elements provide the basis for fundamental models of chemical bonding, there is a need for greater insight into the properties of beryllium. In this context, the chemistry of the homo-elemental Be-Be bond is of fundamental interest. Here the ligand metathesis chemistry of diberyllocene (1; CpBeBeCp)-a stable complex with a Be-Be bond-has been investigated. These studies yield two complexes with Be-Be bonds: Cp*BeBeCp (2) and [K{(HCDippN)2BO}2]BeBeCp (3; Dipp = 2,6-diisopropylphenyl). Quantum chemical calculations indicate that the Be-Be bond in 3 is polarized to such an extent that the complex could be formulated as a mixed-oxidation state Be0/BeII complex. Correspondingly, it is demonstrated that 3 can transfer the 'beryllyl' anion, [BeCp]-, to an organic substrate, by analogy with the reactivity of sp2-sp3 diboranes. Indeed, this work reveals striking similarities between the homo-elemental bonding linkages of beryllium and boron, despite the respective metallic and non-metallic natures of these elements.

Evaluating Noncovalent Interactions in Halogenated Molecules with Double-Hybrid Functionals and a Dedicated Small Basis Set

We present here an extension of our recently developed PBE-QIDH/DH-SVPD basis set to halogen atoms, with the aim of obtaining, for weakly interacting halogenated molecules, interaction energies close to those provided by a large basis set (def2-TZVPP) coupled to empirical dispersion potential. The core of our approach is the split-valence basis set, DH-SVPD, that has been developed for F, Cl, Br, and I atoms using a self-consistent formula, containing only energy terms computed for dimers and the corresponding monomers at the same level of theory. The basis set developed considering four systems, one for each halogen atoms, has been then tested on the X40, X4 × 10 benchmarks as well as on other two, less standard, data sets. Finally, a large system (380 atoms) has been also considered as a "crash" test. Our results show that the simple and nonempirical PBE-QIDH/DH-SVPD approach is able to provide accurate results for interaction energies of all the considered systems and can thus be considered as a cheaper alternative to DH functionals paired with empirical dispersion corrections and a large basis set of triple-ζ quality.

A Vacuum Ultraviolet Photoionization Mass Spectrometry and Density Functional Calculation Study of Formic Acid-Water Clusters

The interaction between formic acid (FA) and water (W) holds significant importance in various chemical processes. Our study combines vacuum-ultraviolet photoionization mass spectrometry with density functional calculations to investigate formic acid water clusters generated in supersonic molecular beams. The mass spectra obtained reveal the formation of protonated clusters as the major product. Enhanced intensities are observed in the mass spectra for a number of clusters holding the following composition, FA1W5H+, FA2W4H+, FA3W3H+, FA4W2H+, FA5W1H+ and FA6W2H+ compared to their neighbors with one less or one more water component. Our calculations shed light on these potentially stable structures, highlighting cyclic arrangements with molecules enclosed within the ring as the most stable structures, and demonstrate a decrease in the stability upon the addition of a water molecule. Comparing experimental appearance energies with calculated ionization energies suggests that fragmentation can occur from clusters of various sizes.

On the Interplay Between Force, Temperature, and Electric Fields in the Rupture Process of Mechanophores

The use of oriented external electric fields (OEEFs) shows promise as an alternative approach to chemical catalysis. The ability to target a specific bond by aligning it with a bond-weakening electric field may be beneficial in mechanochemical reactions, which use mechanical force to selectively rupture bonds. Previous computational studies have focused on a static description of molecules in OEEFs, neglecting to test the influence of thermal oscillations on molecular stability. Here, we performed ab initio molecular dynamics (AIMD) simulations based on density functional theory (DFT) to investigate the behaviour of a model mechanophore under the simultaneous influence of thermal and electric field effects. We show that the change in bond length caused by a strong electric field is largely independent of the temperature, both without and with mechanical stretching forces applied to the molecule. The amplitude of thermal oscillations increases with increasing field strength and temperature, but at low temperatures, the application of mechanical force leads to an additional increase in amplitude. Our research shows that methods for applying mechanical force and OEEFs can be safely combined and included in an AIMD simulation at both low and high temperatures, allowing researchers to computationally investigate mechanochemical reactions in realistic application scenarios.

Influence of Electronic Correlations on Electron-Phonon Interactions of Molecular Systems with the GW and Coupled Cluster Methods

Electron-phonon interactions are of great importance to a variety of physical phenomena, and their accurate description is an important goal for first-principles calculations. Isolated examples of materials and molecular systems have emerged where electron-phonon coupling is enhanced over density functional theory (DFT) when using the Green's-function-based ab initio GW method, which provides a more accurate description of electronic correlations. It is, however, unclear how general this enhancement is and how employing high-end quantum chemistry methods, which further improve the description of electronic correlations, might further alter electron-phonon interactions over GW or DFT. Here, we address these questions by computing the renormalization of the highest occupied molecular orbital energies of Thiel's set of organic molecules by harmonic vibrations using DFT, GW, and equation-of-motion coupled-cluster calculations. We find that, depending on the amount of exact exchange included in the DFT starting point, GW can increase the magnitude of the electron-phonon coupling across Thiel's set of molecules by an average factor of 1.1-1.8 compared to the underlying DFT, while equation-of-motion coupled-cluster leads to an increase of 1.4-2. The electron-phonon coupling predicted with the ab initio GW method is generally in much closer agreement to coupled cluster values compared to DFT, establishing GW as a promising route for accurately computing electron-phonon phenomena in molecules and beyond at a much lower computational cost than higher-end quantum chemistry techniques.

Quantum chemical calculations of nitrosamine activation and deactivation pathways for carcinogenicity risk assessment

N-nitrosamines and nitrosamine drug substance related impurities (NDSRIs) became a critical topic for the development and safety of small molecule medicines following the withdrawal of various pharmaceutical products from the market. To assess the mutagenic and carcinogenic potential of different N-nitrosamines lacking robust carcinogenicity data, several approaches are in use including the published carcinogenic potency categorization approach (CPCA), the Enhanced Ames Test (EAT), in vivo mutagenicity studies as well as read-across to analogue molecules with robust carcinogenicity data. We employ quantum chemical calculations as a pivotal tool providing insights into the likelihood of reactive ion formation and subsequent DNA alkylation for a selection of molecules including e.g., carcinogenic N-nitrosopiperazine (NPZ), N-nitrosopiperidine (NPIP), together with N-nitrosodimethylamine (NDMA) as well as non-carcinogenic N-nitrosomethyl-tert-butylamine (NTBA) and bis (butan-2-yl) (nitros)amine (BBNA). In addition, a series of nitroso-methylaminopyridines is compared side-by-side. We draw comparisons between calculated reaction profiles for structures representing motifs common to NDSRIs and those of confirmed carcinogenic and non-carcinogenic molecules with in vivo data from cancer bioassays. Furthermore, our approach enables insights into reactivity and relative stability of intermediate species that can be formed upon activation of several nitrosamines. Most notably, we reveal consistent differences between the free energy profiles of carcinogenic and non-carcinogenic molecules. For the former, the intermediate diazonium ions mostly react, kinetically controlled, to the more stable DNA adducts and less to the water adducts via transition-states of similar heights. Non-carcinogenic molecules yield stable carbocations as intermediates that, thermodynamically controlled, more likely form the statistically preferred water adducts. In conclusion, our data confirm that quantum chemical calculations can contribute to a weight of evidence approach for the risk assessment of nitrosamines.

Pushing the Limits of Organometallic Redox Chemistry with an Isolable Mn(-I) Dianion

We report an incredibly reducing and redox-active Mn-I dianion, [Mn(CO)3(Ph2B(tBuNHC)2)]2- (NHC = N-heterocyclic carbene), furnished via 2e- reduction of the parent 16e- MnI complex with Na0 or K0. Cyclic voltammograms show a Mn0/-I redox couple at -3.13 V vs Fc+/0 in tetrahydrofuran (THF), -3.06 V in 1,2-dimethoxyethane, and -2.85 V in acetonitrile. The diamagnetic Mn-I dianion is stable in solution and solid-state at room temperature, tolerating a wide range of countercations ([M(2.2.2)crypt]+, [M(18-crown-6)]+, [nBu4N]+; M = Na, K). Countercation identity does not significantly alter 13C NMR spectral signatures with [nBu4N]+ and Na+, suggesting minimal ion pairing in solution. IR spectroscopy reveals a significant decrease in CO stretching frequencies from MnI to Mn-I (ca. 240 cm-1), consistent with a drastic increase in electron density at Mn. State-of-the-art DFT calculations are in excellent agreement with the observed IR spectral data. Moreover, the Mn-I dianion behaves as a chemical reductant, smoothly releasing 1e- or 2e- to regenerate the oxidized Mn0 or MnI species in solution. The reducing potential of [Mn(CO)3(Ph2B(tBuNHC)2)]2- surpasses the naphthalenide anion in THF (-3.09 V) and represents one of the strongest isolable chemical redox agents.

Tailoring parameters for QM/MM simulations: accurate modeling of adsorption and catalysis in zirconium-based metal-organic frameworks

Quantum mechanics/molecular mechanics (QM/MM) simulations offer an efficient way to model reactions occurring in complex environments. This study introduces a specialized set of charge and Lennard-Jones parameters tailored for electrostatically embedded QM/MM calculations, aiming to accurately model both adsorption processes and catalytic reactions in zirconium-based metal-organic frameworks (Zr-MOFs). To validate our approach, we compare adsorption energies derived from QM/MM simulations against experimental results and Monte Carlo simulation outcomes. The developed parameters showcase the ability of QM/MM simulations to represent long-range electrostatic and van der Waals interactions faithfully. This capability is evidenced by the prediction of adsorption energies with a low root mean square error of 1.1 kcal mol-1 across a wide range of adsorbates. The practical applicability of our QM/MM model is further illustrated through the study of glucose isomerization and epimerization reactions catalyzed by two structurally distinct Zr-MOF catalysts, UiO-66 and MOF-808. Our QM/MM calculations closely align with experimental activation energies. Importantly, the parameter set introduced here is compatible with the widely used universal force field (UFF). Moreover, we thoroughly explore how the size of the cluster model and the choice of density functional theory (DFT) methodologies influence the simulation outcomes. This work provides an accurate and computationally efficient framework for modeling complex catalytic reactions within Zr-MOFs, contributing valuable insights into their mechanistic behaviors and facilitating further advancements in this dynamic area of research.

Simple and Accurate One-Body Energy and Dipole Moment Surfaces for Water and Beyond

Water is often the testing ground for new, advanced force fields. While advanced functional forms for intermolecular interactions have been integral to the development of accurate water models, less attention has been paid to a transferable model for intramolecular valence terms. In this work, we present a one-body energy and dipole moment surface model, named 1B-UCB, that is simple yet accurate and can be feasibly adapted for both standard and advanced potentials. 1B-UCB for water is comparable in accuracy to those with much more complex functional forms, despite having drastically fewer parameters. The parametrization protocol has been implemented as part of the Q-Force automated workflow and requires only a quantum mechanical Hessian calculation as reference data, hence allowing it to be easily extended to a variety of molecular systems beyond water, which we demonstrate on a selection of small molecules with different symmetries.

Will We Witness Enzymatic or Pd-(Oligo)Peptide Catalysis in Suzuki Cross-Coupling Reactions?

Despite the development of numerous advanced ligands for Pd-catalyzed Suzuki cross-coupling reaction, the potential of (oligo)peptides serving as ligands remains unexplored. This study demonstrates via density functional theory (DFT) modeling that (oligo)peptide ligands can drive superior activity compared to classic phosphines in these reactions. The utilization of natural amino acids such as Met, SeMet, and His leads to strong binding of the Pd center, thereby ensuring substantial stability of the system. The increasing sustainability and economic viability of (oligo)peptide synthesis open new prospects for applying Pd-(oligo)peptide systems as greener catalysts. The feasibility of de novo engineering an artificial Pd-based enzyme for Suzuki cross-coupling is discussed, laying the groundwork for future innovations in catalytic systems.

Solubilities of Ethylene and Carbon Dioxide Gases in Lithium-Ion Battery Electrolyte

During Li-ion battery operation, (electro)chemical side reactions occur within the cell that can promote or degrade performance. These complex reactions produce byproducts in the solid, liquid, and gas phases. Studying byproducts in these three phases can help optimize battery lifetimes. To relate the measured gas-phase byproducts to species dissolved in the liquid-phase, equilibrium proprieties such as the Henry's law constants are required. The present work implements a pressure decay experiment to determine the thermodynamic equilibrium concentrations between the gas and liquid phases for ethylene (C2H4) and carbon dioxide (CO2), which are two gases commonly produced in Li-ion batteries, with an electrolyte of 1.2 M LiPF6 in 3:7 wt/wt ethylene carbonate/ethyl methyl carbonate and 3 wt % fluoroethylene carbonate (15:25:57:3 wt % total composition). The experimentally measured pressure decay curve is fit to an analytical dissolution model and extrapolated to predict the final pressure at equilibrium. The relationship between the partial pressures and concentration of dissolved gas in electrolyte at equilibrium is then used to determine Henry's law constants of 2.0 × 104 kPa for C2H4 and k CO2 = 1.1 × 104 kPa for CO2. These values are compared to Henry's law constants predicted from density functional theory and show good agreement within a factor of 3.

Combining low-cost electronic structure theory and low-cost parallel computing architecture

The computational efficiency of low-cost electronic structure methods can be further improved by leveraging heterogenous computing architectures. The software package TeraChem has been developed since 2008 to make use of graphical processing units (GPUs), particularly their strong single-precision performance, for the acceleration of quantum chemical calculations. Here, we present the implementation of three low-cost methods, namely HF-3c, PBEh-3c, and the recently introduced ωB97X-3c. We show that these can benefit in terms of performance when combined with "consumer grade" GPUs by leveraging the mixed precision integral handling in TeraChem. The current limitation of the latter's GPU integral library is that Gaussian integrals only for functions with angular momentum l < 3 can be computed, which generally restricts the achievable accuracy in terms of the one-particle basis set. Particularly, the implementation of the ωB97X-3c method now enables higher accuracy with this setting which, in turn, provides the most efficient implementation accessible with consumer-grade hardware. We furthermore show that the implemented 3c methods can be combined with the hh-TDA formalism. This gives new and efficient low-cost multi-configurational excited states methods, which are benchmarked for the description of lowest vertical excitation energies in this work. All in all, the combination of these efficient electronic structure theory methods with affordable highly parallelized computing hardware provides an optimal computational and monetary cost to accuracy ratio.

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.

Infrared Photodissociation Spectroscopy of Water-Tagged Ions with a Widely Tunable Quantum Cascade Laser for Planetary Science Applications

This work presents a benchtop method for collecting the room temperature gas phase infrared (IR) action spectra of protonated amino acids and their isomers. The adopted setup uses a minimally modified commercial electrospray ionization linear ion trap mass spectrometer (ESI-LIT-MS) coupled to a broadband continuous wave (cw) quantum cascade laser (QCL) source. This approach leverages messenger assisted action spectroscopic techniques using water-tagged molecular ions with complex formation, irradiation, and subsequent analysis, all taking place within a single linear ion trap stage. This configuration thus circumvents the use of multiple mass selection and analysis stages, cryogenic buffer cells, and complex high-power laser systems typically called upon to execute these techniques. The benchtop action spectrometer is used to collect the 935-1600 cm-1 (6.2-10.7 μm) IR action spectrum of a collection of amino acids and a dipeptide with results cross referenced against literature examples obtained with a free electron laser source. Recorded IR spectra are used for the analysis of binary mixture samples composed of constitutional isomers α-alanine and β-alanine with ratios determined to ∼4% measurement uncertainty without the aid of a front-end separation stage. This turn-key QCL-based approach is a major step in showing the viability of tag-based action spectroscopic techniques for use in future in situ planetary science sensors and general analytical applications.

Proposal for structure revision of pinofuranoxin A through total syntheses of stereoisomers

The relative configuration of the epoxide functionality in pinofuranoxin A (1), α-alkylidene-β-hydroxy-γ-methyl-γ-butyrolactone with trans-epoxy side chain isolated by Evidente et al. in 2021, was revised by DFT-based spectral reinvestigations and stereo-controlled synthesis. The present investigation demonstrates the difficulty of the configurational elucidation of the stereogenic centers on the conformationally flexible acyclic side-chains. Sharpless's enantioselective epoxidations and dihydroxylations were quite effective in the reinvestigations of the configurations. As our syntheses made all diastereomers available, these would be quite effective in the next structure-biological activity relationship studies.

On the brink of self-hydration: the water heptadecamer

For pure, neutral, isolated molecular clusters, (H2O)17 marks the transition from structures with all water molecules on the cluster surface to water self-hydration, i.e., cluster structures around one central water molecule. Getting this right with water model potentials turns out to be challenging. Even the best water potentials currently available, which reproduce collective properties very well, still deliver contradicting results for (H2O)17, when different low-energy isomers from global structure optimizations are examined. Interestingly, ab initio quantum chemistry also struggles with the only seemingly simple question if (H2O)17 is all-surface or water-centered. Hence, although the long history of water potential development may be entering its final phase, it is not quite finished yet.

A reactive neural network framework for water-loaded acidic zeolites

Under operating conditions, the dynamics of water and ions confined within protonic aluminosilicate zeolite micropores are responsible for many of their properties, including hydrothermal stability, acidity and catalytic activity. However, due to high computational cost, operando studies of acidic zeolites are currently rare and limited to specific cases and simplified models. In this work, we have developed a reactive neural network potential (NNP) attempting to cover the entire class of acidic zeolites, including the full range of experimentally relevant water concentrations and Si/Al ratios. This NNP has the potential to dramatically improve sampling, retaining the (meta)GGA DFT level accuracy, with the capacity for discovery of new chemistry, such as collective defect formation mechanisms at the zeolite surface. Furthermore, we exemplify how the NNP can be used as a basis for further extensions/improvements which include data-efficient adoption of higher-level (hybrid) references via Δ-learning and the acceleration of rare event sampling via automatic construction of collective variables. These developments represent a significant step towards accurate simulations of realistic catalysts under operando conditions.

Excitation landscape of the CP43 photosynthetic antenna complex from multiscale simulations

Photosystem II (PSII), the principal enzyme of oxygenic photosynthesis, contains two integral light harvesting proteins (CP43 and CP47) that bind chlorophylls and carotenoids. The two intrinsic antennae play crucial roles in excitation energy transfer and photoprotection. CP43 interacts most closely with the reaction center of PSII, specifically with the branch of the reaction center (D1) that is responsible for primary charge separation and electron transfer. Deciphering the function of CP43 requires detailed atomic-level insights into the properties of the embedded pigments. To advance this goal, we employ a range of multiscale computational approaches to determine the site energies and excitonic profile of CP43 chlorophylls, using large all-atom models of a membrane-bound PSII monomer. In addition to time-dependent density functional theory (TD-DFT) used in the context of a quantum-mechanics/molecular-mechanics setup (QM/MM), we present a thorough analysis using the perturbed matrix method (PMM), which enables us to utilize information from long-timescale molecular dynamics simulations of native PSII-complexed CP43. The excited state energetics and excitonic couplings have both similarities and differences compared with previous experimental fits and theoretical calculations. Both static TD-DFT and dynamic PMM results indicate a layered distribution of site energies and reveal specific groups of chlorophylls that have shared contributions to low-energy excitations. Importantly, the contribution to the lowest energy exciton does not arise from the same chlorophylls at each system configuration, but rather changes as a function of conformational dynamics. An unexpected finding is the identification of a low-energy charge-transfer excited state within CP43 that involves a lumenal (C2) and the central (C10) chlorophyll of the complex. The results provide a refined basis for structure-based interpretation of spectroscopic observations and for further deciphering excitation energy transfer in oxygenic photosynthesis.

Beyond Explored Functionals: A Computational Journey of Two-Photon Absorption

We present a thorough investigation into the efficacy of 19 density functional theory (DFT) functionals, relative to RI-CC2 results, for computing two-photon absorption (2PA) cross sections (σ2PA) and key dipole moments (|μ00|, |μ11|, |Δμ|, |μ01|) for a series of coumarin dyes in the gas-phase. The functionals include different categories, including local density approximation (LDA), generalized gradient approximation (GGA), hybrid-GGA (H-GGA), range-separated hybrid-GGA (RSH-GGA), meta-GGA (M-GGA), and hybrid M-GGA (HM-GGA), with 14 of them being subjected to analysis for the first time with respect to predicting σ2PA values. Analysis reveals that functionals integrating both short-range (SR) and long-range (LR) corrections, particularly those within the RSH-GGA and HM-GGA classes, outperform the others. Furthermore, the range-separation approach was found more impactful compared to the varying percentages of Hartree-Fock exchange (HF Ex) within different functionals. The functionals traditionally recommended for 2PA do not appear among the top 9 in our study, which is particularly interesting, as these top-performing functionals have not been previously investigated in this context. This list is dominated by M11, QTP variants, ωB97X, ωB97X-V, and M06-2X, surpassing the performance of other functionals, including the commonly used CAM-B3LYP.

The p-block challenge: assessing quantum chemistry methods for inorganic heterocycle dimerizations

The elements of the p-block of the periodic table are of high interest in various chemical and technical applications like frustrated Lewis-pairs (FLP) or opto-electronics. However, high-quality benchmark data to assess approximate density functional theory (DFT) for their theoretical description are sparse. In this work, we present a benchmark set of 604 dimerization energies of 302 "inorganic benzenes" composed of all non-carbon p-block elements of main groups III to VI up to polonium. This so-called IHD302 test set comprises two classes of structures formed by covalent bonding and by weaker donor-acceptor (WDA) interactions, respectively. Generating reliable reference data with ab initio methods is challenging due to large electron correlation contributions, core-valence correlation effects, and especially the slow basis set convergence. To compute reference values for these dimerization reactions, after thorough testing, we applied a computational protocol using state-of-the-art explicitly correlated local coupled cluster theory termed PNO-LCCSD(T)-F12/cc-VTZ-PP-F12(corr.). It includes a basis set correction at the PNO-LMP2-F12/aug-cc-pwCVTZ level. Based on these reference data, we assess 26 DFT methods in combination with three different dispersion corrections and the def2-QZVPP basis set, five composite DFT approaches, and five semi-empirical quantum mechanical methods. For the covalent dimerizations, the r2SCAN-D4 meta-GGA, the r2SCAN0-D4 and ωB97M-V hybrids, and the revDSD-PBEP86-D4 double-hybrid functional are found to be the best-performing methods among the evaluated functionals of the respective class. However, since def2 basis sets for the 4th period are not associated to relativistic pseudo-potentials, we obtained significant errors in the covalent dimerization energies (up to 6 kcal mol-1) for molecules containing p-block elements of the 4th period. Significant improvements were achieved for systems containing 4th row elements by using ECP10MDF pseudopotentials along with re-contracted aug-cc-pVQZ-PP-KS basis sets introduced in this work with the contraction coefficients taken from atomic DFT (PBE0) calculations. Overall, the IHD302 set represents a challenge to contemporary quantum chemical methods. This is due to a large number of spatially close p-element bonds which are underrepresented in other benchmark sets, and the partial covalent bonding character for the WDA interactions. The IHD302 set may be helpful to develop more robust and transferable approximate quantum chemical methods in the future.

Quasi-Classical Trajectory Calculation of Rate Constants Using an Ab Initio Trained Machine Learning Model (aML-MD) with Multifidelity Data

Machine learning (ML) provides a great opportunity for the construction of models with improved accuracy in classical molecular dynamics (MD). However, the accuracy of a ML trained model is limited by the quality and quantity of the training data. Generating large sets of accurate ab initio training data can require significant computational resources. Furthermore, inconsistent or incompatible data with different accuracies obtained using different methods may lead to biased or unreliable ML models that do not accurately represent the underlying physics. Recently, transfer learning showed its potential for avoiding these problems as well as for improving the accuracy, efficiency, and generalization of ML models using multifidelity data. In this work, ab initio trained ML-based MD (aML-MD) models are developed through transfer learning using DFT and multireference data from multiple sources with varying accuracy within the Deep Potential MD framework. The accuracy of the force field is demonstrated by calculating rate constants for the H + HO2 → H2 + 3O2 reaction using quasi-classical trajectories. We show that the aML-MD model with transfer learning can accurately predict the rate constants while reducing the computational cost by more than five times compared to the use of more expensive quantum chemistry training data sets. Hence, the aML-MD model with transfer learning shows great potential in using multifidelity data to reduce the computational cost involved in generating the training set for these potentials.

Isolation of Paraphaeoketones: A Plausible Biosynthetic Explanation for Paraphaeolactones via a Benzilic Acid Rearrangement Rather than a Favorskii Rearrangement

Paraphaeoketones A-C (1-3) were isolated from the culture broth of Paraphaeosphaeria sp. KT4192. Their structures and relative configurations were determined using spectroscopic analysis and verified through density functional theory (DFT)-based chemical shift calculations. The absolute configurations of these compounds were determined by comparing the experimental electronic circular dichroism (ECD) spectra with those based on DFT calculations. We also propose a plausible biosynthetic route to 1-3. While our prior studies on the isolation and structural elucidation of paraphaeolactones (e.g., 4) led us to suggest a Favorskii rearrangement for their biosynthesis, the isolation of 2 prompted the proposal of an alternative biosynthesis for 4, featuring a benzilic acid rearrangement of 2. Moreover, an in vitro conversion of 2 into 4 was achieved successfully, suggesting that a biosynthetic pathway for paraphaeolactones involving a benzilic acid rearrangement is more plausible than the previously presumed Favorskii rearrangement pathway. Arguments based on DFT calculations for these pathways are also described.

Sorting drug conformers in enzyme active sites: the XTB way

In the present study, we have used the MEI196 set of interaction energies to investigate low-cost computational chemistry approaches for the calculation of binding between a molecule and its environment. Density functional theory (DFT) methods, when used with the vDZP basis set, yield good agreement with the reference energies. On the other hand, semi-empirical methods are less accurate as expected. By examining different groups of systems within MEI196 that contain species of a similar nature, we find that chemical similarity leads to cancellation of errors in the calculation of relative binding energies. Importantly, the semi-empirical method GFN1-xTB (XTB1) yields reasonable results for this purpose. We have thus further assessed the performance of XTB1 for calculating relative energies of docking poses of substrates in enzyme active sites represented by cluster models or within the ONIOM protocol. The results support the observations on error cancellation. This paves the way for the use of XTB1 in parts of large-scale virtual screening workflows to accelerate the drug discovery process.

Spurious Oscillations Caused by Density Functional Approximations: Who is to Blame? Exchange or Correlation?

We analyze the varying susceptibilities of different density functional approximations (DFAs) to present spurious oscillations on the profiles of several vibrational properties. Among other problems, these spurious oscillations cause significant errors in harmonic and anharmonic IR and Raman frequencies and intensities. This work hinges on a judicious strategy to dissect the exchange and correlation components of DFAs and pinpoint the origins of these oscillations. We identify spurious oscillations in derivatives of all energy components with respect to nuclear displacements, including those energy terms that do not involve numerical integrations. These indirect spurious oscillations are attributed to suboptimal electron densities resulting from a self-consistent field procedure using a DFA that exhibits direct spurious oscillations. Direct oscillations stem from inaccurate numerical integration of the exchange and correlation energy density functionals. A thorough analysis of direct spurious oscillations reveals that only a handful of exchange and correlation components are insensitive to spurious oscillations, giving rise to three families of functionals, BH&H, LSDA, and BLYP. Among the functionals in these families, we encounter four widespread DFAs: BLYP, B3LYP, LC-BLYP, and CAM-B3LYP. Certain DFAs like PBE appear less sensitive to spurious oscillations due to compensatory cancellations between their energy components. Additionally, we found non-negligible but small oscillations in PBE and TPSS, which could be safely employed provided a sufficiently large integration grid is used in the calculations. These findings hint at the key components of current approximations to be improved and emphasize the necessity to develop accurate DFAs suitable for studying molecular spectroscopies.

Predicting valence tautomerism in diverse cobalt-dioxolene complexes: elucidation of the role of ligands and solvent

The ability of molecular switches to reversibly interconvert between different forms promises potential applications at the scale of single molecules up to bulk materials. One type of molecular switch comprises cobalt-dioxolene compounds that exhibit thermally-induced valence tautomerism (VT) interconversions between low spin Co(iii)-catecholate (LS-CoIII-cat) and high spin Co(ii)-semiquinonate (HS-CoII-sq) forms. Two families of these compounds have been investigated for decades but have generally been considered separately: neutral [Co(diox)(sq)(N2L)] and cationic [Co(diox)(N4L)]+ complexes (diox = generic dioxolene, N2L/N4L = bidentate/tetradentate N-donor ancillary ligand). Computational identification of promising new candidate compounds prior to experimental exploration is beneficial for environmental and cost considerations but requires a thorough understanding of the underlying thermochemical parameters that influence the switching. Herein, we report a robust approach for the analysis of both cobalt-dioxolene families, which involved a quantitative density functional theory-based study benchmarked with reliable quasi-experimental references. The best-performing M06L-D4/def2-TZVPP level of theory has subsequently been verified by the synthesis and experimental investigation of three new complexes, two of which exhibit thermally-induced VT, while the third remains in the LS-CoIII-cat form across all temperatures, in agreement with prediction. Valence tautomerism in solution is markedly solvent-dependent, but the origin of this has not been definitively established. We have extended our computational approach to elucidate the correlation of VT transition temperature with solvent stabilisation energy and change in dipole moment. This new understanding may inform the development of VT compounds for applications in soft materials including films, gels, and polymers.

Tris-Azo Triangular Paraphenylenes: Synthesis and Reversible Interconversion into Radial π-Conjugated Macrocycles

We report the synthesis of cycloparaphenylene derivatives featuring tris-azo groups. The smaller derivative, [3]cycloazobenzene, adopts a triangular all-cis form and exhibits thermally and photochemically stable characteristics due to significant ring strain as well as symmetric Kagome-patterned crystal packing. In contrast, the as-synthesized [3]cycloazobenzene with three biphenylene bridges adopts a triangular all-cis form, which undergoes photoinduced isomerization, leading to a photostationary state. Interestingly, the addition of an excess of acid selectively leads to the formation of an all-trans form. DFT calculations reveal that the interconversion from a triangular to a circular shape correlates with an increase in HOMO and a decrease in LUMO, characteristics intrinsic to radial π-conjugated systems.

Multilevel Framework for Analysis of Protein Folding Involving Disulfide Bond Formation

In this study, a three-layered multicenter ONIOM approach is implemented to characterize the naive folding pathway of bovine pancreatic trypsin inhibitor (BPTI). Each layer represents a distinct level of theory, where the initial layer, encompassing the entire protein, is modeled by a general all-atom force-field GFN-FF. An intermediate electronic structure layer consisting of three multicenter fragments is introduced with the state-of-the-art semiempirical tight-binding method GFN2-xTB. Higher accuracy, specifically addressing the breaking and formation of the three disulfide bonds, is achieved at the innermost layer using the composite DFT method r2SCAN-3c. Our analysis sheds light on the structural stability of BPTI, particularly the significance of interlinking disulfide bonds. The accuracy and efficiency of the multicenter QM/SQM/MM approach are benchmarked using the oxidative formation of cystine. For the folding pathway of BPTI, relative stabilities are investigated through the calculation of free energy contributions for selected intermediates, focusing on the impact of the disulfide bond. Our results highlight the intricate trade-off between accuracy and computational cost, demonstrating that the multicenter ONIOM approach provides a well-balanced and comprehensive solution to describe electronic structure effects in biomolecular systems. We conclude that multiscale energy landscape exploration provides a robust methodology for the study of intriguing biological targets.

Assessing the efficacy of aluminum metal clusters Al13 and Al15 in mitigating NO2 and SO2 pollutants: a DFT investigation

The present investigation delves into the adverse environmental impact of atmospheric pollutant gases, specifically nitrogen dioxide (NO2) and sulfur dioxide (SO2), which necessitates the identification and implementation of effective control measures. The central objective of this study is to explore the eradication of these pollutants through the utilization of aluminum Al13 and Al15 metal clusters, distinguished by their unique properties. The comprehensive evaluation of gas/cluster interactions is undertaken employing density functional theory (DFT). Geometric optimization calculations for all structures are executed using the ωB97XD functional and the Def2-svp basis set. To probe various interaction modalities, gas molecule distribution around the metal clusters is sampled using the bee colony algorithm. Frequency calculations employing identical model chemistry validate the precision of the optimization calculations. The quantum theory of atoms in molecules (QTAIM) and natural bond orbital (NBO) methodologies are applied for the analysis of intermolecular interactions. This research establishes the robust formation of van der Waals attractions between the investigated gas molecules, affirming aluminum metal clusters as viable candidates for the removal and control of these gases.

Basis Set Requirements of σ-Functionals for Gaussian- and Slater-Type Basis Functions and Comparison with Range-Separated Hybrid and Double Hybrid Functionals

σ-Functionals belong to the class of Kohn-Sham (KS) correlation functionals based on the adiabatic-connection fluctuation-dissipation theorem and are technically closely related to the random phase approximation (RPA). They have the same computational demand as the latter, with the computational effort of an energy evaluation for both methods being lower than that of a preceding hybrid DFT calculation for typical systems but yield much higher accuracy, reaching chemical accuracy of 1 kcal/mol for quantities such as reactions and transition energies in main group chemistry. In previous work on σ-functionals, rather large Gaussian basis sets have been used. Here, we investigate the actual basis set requirements of σ-functionals and present three setups that employ smaller Gaussian basis sets ranging from quadruple-ζ (QZ) to triple-ζ (TZ) quality and represent a good compromise between accuracy and computational efficiency. Furthermore, we introduce an implementation of σ-functionals based on Slater-type basis sets and present two setups of QZ and TZ quality for this implementation. We test the accuracy of these setups on a large database of various physical properties and types of reactions, as well as equilibrium geometries and vibrational frequencies. As expected, the accuracy of σ-functional calculations becomes somewhat lower with a decreasing basis set size. However, for all setups considered here, calculations with σ-functionals are clearly more accurate than those within the RPA and even more so than those of the conventional KS methods. For the smallest setup using Gaussian-type basis functions and Slater-type basis functions, we introduce a reparametrization that reduces the loss in accuracy due to the basis set error to some extent. A comparison with the range-separated hybrid ωB97X-V and the double hybrid DSD-BLYP-D3 shows that σ functionals outperform in accuracy both of these accurate and, for their class, representative functionals.

Performance of Density Functionals for Excited-State Properties of Isolated Chromophores and Exciplexes: Emission Spectra, Solvatochromic Shifts, and Charge-Transfer Character

This study assesses the performance of various meta-generalized gradient approximation (meta-GGA), global hybrid, and range-separated hybrid (RSH) density functionals in capturing the excited-state properties of organic chromophores and their excited-state complexes (exciplexes). Motivated by their uses in solar energy harvesting and photoredox CO2 reduction, we use oligo-(p-phenylenes) and their excited-state complexes with triethylamine as model systems. We focus on the fluorescence properties of these systems, specifically emission energies. We also consider solvatochromic shifts and wave function characteristics. The latter is described by using reduced quantities such as natural transition orbitals (NTOs) and exciton descriptors. The functionals are benchmarked against the experimental fluorescence spectra and the equation-of-motion coupled-cluster method with single and double excitations. Both in isolated chromophores and in exciplexes, meta-GGA functionals drastically underestimate the emission energies and exhibit significant exciton delocalization and anticorrelation between electron and hole motion. The performance of global hybrid functionals is strongly dependent on the percentage of exact exchange. Our study identifies RSH GGAs as the best-performing functionals, with ωPBE demonstrating the best agreement with experimental results. RSH meta-GGAs often overestimate emission energies in exciplexes and yield larger hole NTOs. Their performance can be improved by optimally tuning the range-separation parameter.

Enantioselective Intramolecular ortho Photocycloaddition Reactions of 2-Acetonaphthones

2-Acetonaphthones, which bear an alkenyl group tethered to its C1 carbon atom via an oxygen atom, were found to undergo an enantioselective intramolecular ortho photocycloaddition reaction. A chiral oxazaborolidine Lewis acid leads to a bathochromic absorption shift of the substrate and enables an efficient enantioface differentiation. Visible light irradiation (λ=450 nm) triggers the reaction which is tolerant of various groups at almost any position except carbon atom C8 (16 examples, 53-99 % yield, 80-97 % ee). Consecutive reactions were explored including a sensitized rearrangement to tetrahydrobiphenylenes, which occurred with full retention of configuration. Evidence was collected that the catalytic photocycloaddition occurs via triplet intermediates, and the binding mode of the acetonaphthone to the chiral Lewis acid was elucidated by DFT calculations.

Implementation and First Evaluation of Strong-Correlation-Corrected Local Hybrid Functionals for the Calculation of NMR Shieldings and Shifts

Local hybrid functionals containing strong-correlation factors (scLHs) and range-separated local hybrids (RSLHs) have been integrated into an efficient coupled-perturbed Kohn-Sham implementation for the calculation of nuclear shielding constants. Several scLHs and the ωLH22t RSLH have then been evaluated for the first time for the extended NS372 benchmark set of main-group shieldings and shifts and the TM70 benchmark of 3d transition-metal shifts. The effects of the strong-correlation corrections have been analyzed with respect to the spatial distribution of the sc-factors, which locally diminish exact-exchange admixture at certain regions in a molecule. The scLH22t, scLH23t-mBR, and scLH23t-mBR-P functionals, which contain a "damped" strong-correlation factor to retain the excellent performance of the underlying LH20t functional for weakly correlated situations, tend to make smaller corrections to shieldings and shifts than the "undamped" scLH22ta functional. While the latter functional can also deteriorate agreement with the reference data in certain weakly correlated cases, it provides overall better performance, in particular for systems where static correlation is appreciable. This pertains only to a minority of systems in the NS372 main-group test set but to many more systems in the TM70 transition-metal test set, in particular for high-oxidation-state complexes, e.g., Cr(+VI) complexes and other systems with stretched bonds. Another undamped scLH, the simpler LDA-based scLH21ct-SVWN-m, also tends to provide significant improvements in many cases. The differences between the functionals and species can be rationalized on the basis of one-dimensional plots of the strong-correlation factors, augmented by isosurface plots of the fractional orbital density (FOD). Position-dependent exact-exchange admixture is thus shown to provide substantial flexibility in treating response properties like NMR shifts for both weakly and strongly correlated systems.

CREST-A program for the exploration of low-energy molecular chemical space

Conformer-rotamer sampling tool (CREST) is an open-source program for the efficient and automated exploration of molecular chemical space. Originally developed in Pracht et al. [Phys. Chem. Chem. Phys. 22, 7169 (2020)] as an automated driver for calculations at the extended tight-binding level (xTB), it offers a variety of molecular- and metadynamics simulations, geometry optimization, and molecular structure analysis capabilities. Implemented algorithms include automated procedures for conformational sampling, explicit solvation studies, the calculation of absolute molecular entropy, and the identification of molecular protonation and deprotonation sites. Calculations are set up to run concurrently, providing efficient single-node parallelization. CREST is designed to require minimal user input and comes with an implementation of the GFNn-xTB Hamiltonians and the GFN-FF force-field. Furthermore, interfaces to any quantum chemistry and force-field software can easily be created. In this article, we present recent developments in the CREST code and show a selection of applications for the most important features of the program. An important novelty is the refactored calculation backend, which provides significant speed-up for sampling of small or medium-sized drug molecules and allows for more sophisticated setups, for example, quantum mechanics/molecular mechanics and minimum energy crossing point calculations.