DFTB+, a software package for efficient approximate density functional theory based atomistic simulations

Discriminating High from Low Energy Conformers of Druglike Molecules: An Assessment of Machine Learning Potentials and Quantum Chemical Methods

Accurate and efficient prediction of high energy ligand conformations is important in structure-based drug discovery for the exclusion of unrealistic structures in docking-based virtual screening and de novo design approaches. In this work, we constructed a database of 140 solution conformers from 20 druglike molecules of varying size and chemical complexity, with energetics evaluated at the DLPNO-CCSD(T)/complete basis set (CBS) level. We then assessed a selection of machine learning potentials and semiempirical quantum mechanical models for their ability to predict conformational energetics. The GFN2-xTB tight binding density functional method correlates with reference conformer energies, yielding a Kendall's τ of 0.63 and mean absolute error of 2.2 kcal/mol. As putative internal energy filters for screening, we find that the GFN2-xTB, ANI-2x and MACE-OFF23(L) models perform well in identifying low energy conformer geometries, with sensitivities of 95 %, 89 % and 95 % respectively, but display a reduced ability to exclude high energy conformers, with respective specificities of 80 %, 61 % and 63 %. The GFN2-xTB method therefore exhibited the best overall performance and appears currently the most suitable of the three methods to act as an internal energy filter for integration into drug discovery workflows. Enrichment of high energy conformers in the training of machine learning potentials could improve their performance as conformational filters.

Exploring the electronic properties of carbon nanoflake-based charge transport materials for perovskite solar cells: a computational study

Carbon-based materials, in particular carbon nanoflakes (CNFs) and carbon quantum dots (CQDs), have been increasingly used in charge transport layers and electrodes for perovskite solar cells (PSCs). There are practically limitless possibilities of designing such materials with different sizes, shapes and functional groups, which allow modulating their properties such as band alignment and charge transport. Solid state packing further modifies these properties. However, there is still limited insight into the electronic properties of these types of materials as a function of their chemical composition, structure, and packing. Here, we compute the dependence of band alignment and charge transport characteristics on the size, chemical composition, and structure of commonly accessible types of nanoflakes and functional groups and further consider the effect of their packing. We use a combination of density functional theory (DFT) and density functional-based tight binding (DFTB) to get electronic structure level insight at length scales (nanoflake sizes) relevant to the experiment. We find that CNFs must have sizes as small as 1.3 nm to provide band alignments suitable for their use as hole transport materials in PSCs containing the commonly used methylammonium lead iodide perovskite. We show that both shape and functionalization can significantly modify the band alignment of the CNF, by more than half an electron volt. Inter-flake interactions further modify the band alignment, in some cases by about half an electron volt. CNFs having small sizes possess sufficient inter-flake electronic coupling for efficient hole transport. In contrast, no shape or size of CNFs produces band alignment suitable for their use as electron transport materials.

Design and Computational Study of Sulfonamide-Modified Cannabinoids as Selective COX-2 Inhibitors Using Semiempirical Quantum Mechanical Methods: Drug-like Properties and Binding Affinity Insights

Cyclooxygenase (COX) is one of the concerned targets in the development of anti-inflammatory therapies. Using semiempirical quantum mechanical (SQM) methods with implicit solvation, we investigated the binding free energies and selectivity of natural cannabinoids and their sulfonamide-modified derivatives with the COX and cannabinoid (CB) receptors. Validation against benchmark data sets demonstrated the accuracy of these methods in predicting binding affinities while minimizing false positives and false negatives often associated with conventional docking tools. Our findings indicate that Δ9-THC and its carboxylic acid derivative exhibit strong binding affinities for COX-2 and CB2, suggesting their potential as anti-inflammatory agents, though their significant CB1 affinity suggests psychoactive risks. In contrast, carboxylic acid derivatives such as CBCA, CBNA, CBEA, CBTA, and CBLA demonstrated selective binding to COX-2 and CB2, with low CB1 affinity, supporting their potential as promising anti-inflammatory leads with reduced psychoactive side effects. Sulfonamide-modified analogs further enhanced COX-2 binding affinities and selectivity, displaying favorable drug-like properties, including compliance with Lipinski's rules, noninhibition of cytochromes P450, and oral bioavailability. These results highlight the utility of GFN2-xTB in identifying and optimizing cannabinoid-based therapeutic candidates for anti-inflammatory applications.

The Atomic Density-Based Tight-Binding (aTB) Model: A Robust and Accurate Semiempirical Method Parametrized for H-Ra; Applied to Structures, Vibrational Frequencies, Noncovalent Interactions, and Excited States

This work introduces a semiempirical method, named aTB, based on the tight-binding model and named for its zero-order Hamiltonian that utilizes density-fitting atomic densities. This method can calculate the molecular structure, vibrational frequencies, noncovalent interactions, and excited states of large molecular systems. The parameters of aTB cover elements from Hydrogen (H) to Radium (Ra), and for ground state calculations, it supports the analysis of first- and second-order derivatives. The Hamiltonian of aTB contains a zero-order Hamiltonian, Coulomb term, an explicit second- and third-order expansion of the exchange-correlation term, and a spin-polarization term with only one additional parameter. A series of extensive tests were conducted to compare aTB with existing semiempirical methods.

Discovery of a molecular adsorbent for efficient CO2/CH4 separation using a computation-ready experimental database of porous molecular materials

The development and sharing of computational databases for metal-organic frameworks (MOFs) and covalent organic frameworks (COFs) have significantly accelerated the exploration and application of these materials. Recently, molecular materials have emerged as a notable subclass of porous materials, characterized by their crystallinity, modularity, and processability. Among these, macrocycles and cages stand out as representative molecules. Experimental discovery of a target molecular material from a vast possibility of structures for defined applications is generally impractical due to high experimental costs. This study presents the most extensive Computation-ready Experimental (CoRE) database of macrocycles and cages (MCD) to date, comprising 7939 structures. Using the MCD, we conducted simulations of binary CO2/CH4 competitive adsorption under conditions relevant to industrial applications. These simulations established a structure-property-function relationship, enabling the identification of materials with potential for CO2/CH4 separation. Among them, a macrocycle, NDI-Δ, exhibited promising CO2 adsorption capacity and selectivity, as confirmed by gas sorption and breakthrough experiments.

Selective adsorption of CO2 in TAMOF-1 for the separation of CO2/CH4 gas mixtures

TAMOF-1 is a robust, highly porous metal-organic framework built from Cu2+ centers linked by a L-histidine derivative. Thanks to its high porosity and homochirality, TAMOF-1 has shown interesting molecular recognition properties, being able to resolve racemic mixtures of small organic molecules in gas and liquid phases. Now, we have discovered that TAMOF-1 also offers a competitive performance as solid adsorbent for CO2 physisorption, offering promising CO2 adsorption capacity ( > 3.8 mmol g-1) and CO2/CH4 Ideal Adsorbed Solution Theory (IAST) selectivity ( > 40) at ambient conditions. Moreover, the material exhibits favorable adsorption kinetics under dynamic conditions, demonstrating good stability in high-humidity environments and minimal degradation in strongly acidic media. We have identified the key interactions of CO2 within the TAMOF-1 framework by a combination of structural (neutron diffraction), spectroscopic and theoretical analyses which conclude a dual-site adsorption mechanism with the majority of adsorbed CO2 molecules occupying the empty voids in the TAMOF-1 channels without strong, directional supramolecular interactions. This very weak dominant binding opens the possibility of a low energy regeneration process for convenient CO2 purification. These features identify TAMOF-1 as a viable solid-state adsorbent for the realization of affordable biogas upgrading.

Exploring the electronic and mechanical properties of the recently synthesized nitrogen-doped amorphous monolayer carbon

The recent synthesis of nitrogen-doped amorphous monolayer carbon (NAMC) opens new possibilities for multifunctional materials. In this study, we have investigated the nitrogen doping limits and their effects on NAMC's structural and electronic properties using density functional-based tight-binding simulations. Our results show that NAMC remains stable up to 35% nitrogen doping, beyond which the lattice becomes unstable. The formation energies of NAMC are higher than those of nitrogen-doped graphene for all the cases we have investigated. Both undoped MAC and NAMC exhibit metallic behavior, although only MAC features a Dirac-like cone. MAC has an estimated Young's modulus value of about 410 GPa, while NAMC's modulus can vary around 416 GPa depending on nitrogen content. MAC displays optical activity in the ultraviolet range, whereas NAMC features light absorption within the infrared and visible ranges, suggesting potential for distinct optoelectronic applications. Their structural thermal stabilities were addressed through molecular dynamics simulations. MAC melts at approximately 4900 K, while NAMC loses its structural integrity for temperatures ranging from 300 K to 3300 K, lower than graphene. These results point to potential NAMC applications in flexible electronics and optoelectronics.

Comparative Study of UMCM-9 Polymorphs: Structural, Dynamic, and Hydrogen Storage Properties via Atomistic Simulations

The structural and dynamic properties of two polymorphs of the metal-organic framework UMCM-9 (UMCM-9-α and -β) have been studied via molecular dynamics (MD) simulations in conjunction with density functional tight binding (DFTB) as well as the newly developed MACE-MP neural network potential (NNP). Based on these calculations, a novel UMCM-9-β polymorph is proposed that exhibits reduced linker strain and increased flexibility compared to UMCM-9-α, which is shown to be energetically less stable. UMCM-9-β exhibits enhanced diffusion of molecular hydrogen due to weaker host-guest interactions, whereas UMCM-9-α exhibits stronger interactions, leading to improved hydrogen adsorption. The results suggest that synthesis conditions may control the formation of both polymorphs: UMCM-9-β is likely to be the thermodynamic product, forming under stable conditions, while UMCM-9-α may be the kinetic product, forming under accelerated synthesis conditions. This study highlights the potential for optimizing MOFs for specific gas storage applications to achieve the desired structural and associated gas storage properties.

Topochemical reduction of FeCo-oxide to FeCo-alloy nanosystems into a SiO2 matrix

This study focuses on the synthesis of metallic magnetic nanosystems embedded in mesoporous silica (SiO2), and the impact of matrix porosity, controlled by temperature treatment, on the efficiency of H2 reduction process. The reduction of FeCo oxides to the corresponding alloy nanosystems was first optimized, identifying FeCo with 50 at% Fe as the optimal composition due to its high saturation magnetization (∼242 A m2 kg-1) and oxidation onset temperature (∼440 °C). Then, the FeCo-oxide nanocomposites were synthesized into SiO2via sol-gel self-combustion under thermal treatments, to properly tune the surface area of the silica matrix. By controlling the annealing temperature, the specific surface area (SA) of the matrix decreases from ∼512(1) m2 g-1 to ∼345(1) m2 g-1 when annealed to 900 °C in air. Following topochemical reduction in H2, the structural properties of the obtained FeCo-SiO2 nanocomposites have been analyzed using X-ray powder diffraction and magnetic properties were evaluated to establish a correlation between matrix SA and reduction capability. The decrease of SA leads to incomplete reduction at higher temperatures, with the formation of FeYOX/CoXOY intermediates. This work underscores the critical role of matrix porosity in achieving a delicate balance to ensure both the efficient conversion of nanostructured oxide to their metallic state and the preservation of their magnetic and structural integrity.

Magnetic and reusable Fe3O4/PPE-2 functional material for efficient photodegradation of organic dye

Composite photocatalysts based on metal nanoparticles and functional polymers attract much attention compared to inorganic photocatalysts. In this study, a reusable magnetite/anion exchanger (Fe3O4/PPE-2) functional material is synthesized by a hydrothermal method, and its photocatalytic activity is evaluated for the photocatalytic degradation of Rhodamine B (RhB). The results from materials characterization confirm a well-defined morphology of magnetic Fe3O4/PPE-2 functional material and the formation of Fe3O4 nanocrystals with different shapes and sizes on the surface of anion exchange material (PPE-2). The optimized Fe3O4/PPE-2 in 180 °C (FM180) photocatalyst exhibited a band gap energy of 1.90 eV, demonstrating significant photocatalytic potential. Using RhB as a model pollutant, magnetic Fe3O4/PPE-2 (FM180) functional material achieved 98.2% degradation efficiency after 160 min of visible light irradiation (rate constant k = 0.03496 min-1). Efficiency of the photocatalytic materials, of photocatalytic degradation of RhB is 28.4% for pure anion exchanger (PPE-2), 56.5%, 64.7% and 98.2% for magnetic functional Fe3O4/PPE-2 materials, synthesized under conditions of 140 °C (FM140), 160 °C (FM160) and 180 °C (FM180), respectively. Compared to individual PPE-2 anion exchange material and Fe3O4, the magnetic functional FM180 material exhibits a remarkable photocatalytic reaction rate as high as four times that of PPE-2, with superior reusability over 10 cycles. The computational study and Mott-Schottky plots verify the formation of the internal electric field. Possible reaction pathways for the photocatalytic degradation of RhB are presented. In addition, the results demonstrate that the Fe3O4/PPE-2 functional material very efficiently removed Rhodamine B from textile wastewater. This work offers a simple route for the preparation of magnetic and reusable Fe3O4/PPE-2 magnetic functional material that can be used in the water purification process.

Overview on Building Blocks and Applications of Efficient and Robust Extended Tight Binding

The extended tight binding (xTB) family of methods opened many new possibilities in the field of computational chemistry. Within just 5 years, the GFN2-xTB parametrization for all elements up to Z = 86 enabled more than a thousand applications, which were previously not feasible with other electronic structure methods. The xTB methods provide a robust and efficient way to apply quantum mechanics-based approaches for obtaining molecular geometries, computing free energy corrections or describing noncovalent interactions and found applicability for many more targets. A crucial contribution to the success of the xTB methods is the availability within many simulation packages and frameworks, supported by the open source development of its program library and packages. We present a comprehensive summary of the applications and capabilities of xTB methods in different fields of chemistry. Moreover, we consider the main software packages for xTB calculations, covering their current ecosystem, novel features, and usage by the scientific community.

Quantum Dynamics of Charge Carriers in Fullerenes Encapsulated by Covalent Organic Polyhedra: Choice of Fullerene Matters

Charge separation is at the heart of solar energy applications, and efficient materials require fast photoinduced electron transfer (ET) and slow charge recombination (CR). Using time-dependent self-consistent charge density functional tight-binding theory combined with nonadiabatic (NA) molecular dynamics, we report a detailed analysis of ET and CR in hybrids composed of photoactive covalent organic polyhedra (COP) and encapsulated fullerenes. The ET occurs on a subpicosecond time scale and accelerates with increasing fullerene diameter, C60 to C70 to C84. As the fullerene size increases, the π-electron system available for interaction with the COP grows, the fullerene-COP separation decreases, and the number of fullerene states available to accept the photoexcited electron increases, accelerating the ET. In comparison, the CR occurs on a nanosecond time scale and correlates with the length of the fullerene shortest axis because the relevant fullerene state is polarized in that direction. The largest and least symmetrical C84 exhibits the fastest ET and the slowest CR, making COP@C84 the most promising hybrid. Both high-frequency bond stretching and bending vibrations and low-frequency breathing modes are involved in the ET and CR processes, with more modes present in the C84 system due its lower symmetry. The 10-20 fs vibrationally induced coherence loss in the electronic subsystem contributes to long lifetimes of the charge-separated states. The comprehensive investigation of the structure-property relationship of the charge carrier dynamics in the COP@fullerene hybrids provides a detailed atomistic understanding of interfacial ET processes and generates guidelines for rational design of high-performance materials for solar energy and related applications.

Towards catalytic fluoroquinolones: from metal-catalyzed to metal-free DNA cleavage

A library of eight new fluoroquinolone-nuclease conjugates containing a guanidinoethyl or aminoethyl auxiliary pendant on the 1,4,7-triazacyclononane (TACN) moiety was designed and synthesized to investigate their potential as catalytic antibiotics. The Cu(ii) complexes of the designer structures showed significant in vitro hydrolytic and oxidative DNA cleavage activity and good antibacterial activity against both Gram-negative and Gram-positive bacteria. The observed activity of all the Cu(ii)-TACN-ciprofloxacin complexes was strongly inhibited in the presence of Cu(ii)-chelating agents, thereby demonstrating "vulnerability" under physiological conditions. However, selected TACN-ciprofloxacin conjugates in their metal-free form efficiently cleaved plasmid DNA under physiological conditions. The lead compound 1 showed good DNase activity which was retained in the presence of strong metal chelators and exhibited excellent antibacterial activity against both Gram-negative and Gram-positive bacteria. Density functional theory calculations combined with quantum mechanics/molecular mechanics simulations suggest a general base-general acid mechanism for the hydrolytic DNA cleavage mechanism by compound 1.

Toxicity of pesticide cocktails in amphibian larvae: understanding the impact of agricultural activity on aquatic ecosystems in the Salado River basin, Argentina

Aquatic communities are increasingly exposed to complex mixtures of contaminants, mainly pesticides due to the impact of agricultural activity. The aim of this study was to evaluate the toxicity of an eight-pesticide cocktail on larvae of the South American common toad, Rinella arenarum. The cocktail represents a realistic mixture of insecticides (cypermethrin, chlorpyrifos and lambda-cyhalothrin), herbicides (glyphosate, glufosinate ammonium, prometryn and metolachlor), and a fungicide (pyraclostrobin) previously found in aquatic organisms (Prochilodus lineatus) from the Salado River Basin, an area with strong agricultural pressure. Computational simulations through the Density Functional Tight-Binding method indicated a strong spontaneous trend toward the formation of the cocktail, suggesting that it may act as a novel xenobiotic entity in the environment. The cocktail effects were evaluated in early-developing and premetamorphic larvae, at feasible concentrations found in real scenarios. The mixture led to high mortality and teratogenicity in early-developing larvae. Premetamorphic larvae showed endocrine disruption, oxidative stress, and impairments in detoxification and hepatic functioning. Neurotoxicity, genotoxicity, cardiotoxicity and high mortality under stress conditions were also observed in exposed larvae. This novel evaluation highlights the ecotoxicological risk for aquatic organisms exposed to complex mixtures and underscores the need to consider cocktail effects in studies regarding ecosystems health.

Design, spectral characterization, quantum chemical investigation, biological activity of nano-sized transition metal complexes of tridentate 3-mercapto-4H-1,2,4-triazol-4-yl-aminomethylphenol Schiff base ligand

A tridentate Schiff base ligand, H2MTIP, was produced by condensing salicylaldehyde with 4-amino-4H-1,2,4-triazole-3-thiol. The ligand was then used to create nanosized complexes of Pt(II), Ni(II), Cu(II), and Pd(II). The complexes have the composition [Pt/Ni/Cu/or Pd(MTIP)(H2O)], this conclusion is supported by molar conductance, magnetic moments, elemental analyses, spectral analyses. In DFT analysis, the 6-31+ g(d,p) basis set was used to fully optimize the energy with respect to the shapes of Schiff base ligand and metal complexes. Pt(II), Ni(II), Cu(II), and Pd(II) complexes have been assigned square-planar geometries. At the same time, the intense diffraction peaks in X-ray diffractograms show their crystalline features with particle sizes in the nanoscale range. The binding interaction of calf thymus DNA with these metal complexes and their insulin-like activity was examined in vitro by inhibiting α-amylase. The study investigated the in-vitro activity of several complexes and identified Pt(II) complex as the one with the highest activity. The researchers then tested this complex for in-vivo antidiabetic activity in induced diabetic rats using the STZ model, and it significantly lowered blood glucose levels. The antioxidant activity and toxicity level of Pt(II) complex were also excellent, suggesting that it could be a good candidate for further research as a possible diabetes drug.Communicated by Ramaswamy H. Sarma.

Impact of nitrogen configuration on the electronic properties of tailored triphenylamine derivatives as hole transport materials for perovskite solar cells: a computational chemistry study

Physical properties associated with charge transfer processes of tailored triphenylamine derivative molecules, generated from six nitrogen-containing heterocyclic aromatic cores (nTPAM), were theoretically studied. The conformer-rotamer ensemble sampling tool (CREST) was employed to study the geometric arrangements of n-TPAM monomers and dimers. Essential chemical parameters, such as reorganisation energies, spin densities, and chemical reactivity, were computed utilising the M06 and ωB97X-3c DFT functionals. The ω parameter of the ωB97X-3c functional was optimised through a non-empirical tuning method. Time-dependent DFT computations yielded insights into the maximum absorption wavelength and transition density matrix of n-TPAM monomers. The electronic coupling between dimers was assessed using M06 and ωB97X-3c. The HOMO energy levels of the n-TPAM derivatives correspond with the perovskite conduction band, situated between YZ22 and spiro-OMeTAD hole transport materials (HTMs). n-TPAM molecules demonstrated enhanced electronic coupling for hole transfer, except for C-TPAM (Jeff(h) = 52.0 meV), in contrast to YZ22 (Jeff(h) = 79.7 meV). Nonetheless, n-TPAM exhibited elevated reorganisation energies, varying from 268.76 to 346.31 meV, compared to YZ22 (149.78 meV). Among the analysed derivatives, A-TPAM exhibited the highest chemical hardness and was the only molecule with absorption extending beyond the visible spectrum. Although A-TPAM exhibited superior electronic properties, its high reorganisation energy may limit its performance as an HTM compared to YZ22. Our analysis revealed that the electronic properties relevant to the hole extraction process can be tuned by modifying the nitrogen core configuration. Additionally, the degree of charge delocalisation in cationic compounds significantly influences charge transfer rates; therefore, an optimised DFT functional that effectively represents charge delocalisation is crucial for anticipating accurate trends in physical characteristics.

Periodic GFN1-xTB Tight Binding: A Generalized Ewald Partitioning Scheme for the Klopman-Ohno Function

A novel formulation is presented for the treatment of electrostatics in the periodic GFN1-xTB tight-binding model. Periodic GFN1-xTB is hindered by the functional form of the second-order electrostatics, which only recovers Coulombic behavior at large interatomic distances and lacks a closed-form solution for its Fourier transform. We address this by introducing a binomial expansion of the Klopman-Ohno function to partition short- and long-range interactions, enabling the use of a generalized Ewald summation for the solution of the electrostatic energy. This approach is general and is applicable to any damped potential of the form |Rn + c|-m. Benchmarks on the X23 molecular crystal dataset and a range of prototypical bulk semiconductors demonstrate that this systematic treatment of the electrostatics eliminates unphysical behavior in the equation of state curves. In the bulk systems studied, we observe a mean absolute error in total energy of 35 meV/atom, comparable to the machine-learned universal force field, M3GNet, and sufficiently precise for structure relaxation. These results highlight the promising potential of GFN1-xTB as a universal tight-binding parametrization.

Tight Binding Simulation of the MgO and Mg(OH)2 Hydration and Carbonation Processes

Magnesium, the lightest engineering metal, has MgO and Mg(OH)2 as its common corrosion products, which can also be used for CO2 storage due to their chemical reactivity. In this study, we developed a DFTB model with monopole, dipole, and quadrupole electrostatics for magnesium compounds containing oxygen, hydrogen, and carbon and applied it in both static and molecular dynamics (DFTB-MD) calculations of the MgO and Mg(OH)2 hydration and carbonation processes. With our new model, the Electron Localization Function (ELF) and Charge Density Difference (CDD) were computed as part of the electronic structure analysis, providing insights into the electronic mechanism of MgO and Mg(OH)2 hydration and carbonation processes. The geometry for the brucite-water bulk system was analyzed, including the reconstruction of near-surface water molecules which may influence the dissolution, hydration, and carbonation processes. By comparing experimental, DFT, classical MD results and the results from other parameter set, the accuracy of the model was assessed. A strong covalent bond between CO2 and the (001) surface of MgO leads to the formation of a CO3 group, while no such CO3 group forms on the (101̅1) surface of Mg(OH)2. Defect sites, however, are more favorable for the formation of the CO3 group. In contrast, covalent bonds are not found for either surface when water interacted with them. This work provides new insights into the behavior of magnesium compounds interacting with water and carbon dioxide using our model, and it introduces a tool for effectively analyzing chemical electronic structures and bonding mechanisms.

MORE-Q, a dataset for molecular olfactorial receptor engineering by quantum mechanics

We introduce the MORE-Q dataset, a quantum-mechanical (QM) dataset encompassing the structural and electronic data of non-covalent molecular sensors formed by combining 18 mucin-derived olfactorial receptors with 102 body odor volatilome (BOV) molecules. To have a better understanding of their intra- and inter-molecular interactions, we have performed accurate QM calculations in different stages of the sensor design and, accordingly, MORE-Q splits into three subsets: i) MORE-Q-G1: QM data of 18 receptors and 102 BOV molecules, ii) MORE-Q-G2: QM data of 23,838 BOV-receptor configurations, and iii) MORE-Q-G3: QM data of 1,836 BOV-receptor-graphene systems. Each subset involves geometries optimized using GFN2-xTB with D4 dispersion correction and up to 39 physicochemical properties, including global and local properties as well as binding features, all computed at the tightly converged PBE+D3 level of theory. By addressing BOV-receptor-graphene systems from a QM perspective, MORE-Q can serve as a benchmark dataset for state-of-the-art machine learning methods developed to predict binding features. This, in turn, can provide valuable insights for developing the next-generation mucin-derived olfactory receptor sensing devices.

Impact of Fluctuations in the Peridinin-Chlorophyll a-Protein on the Energy Transfer: Insights from Classical and QM/MM Molecular Dynamics Simulations

The peridinin-chlorophyll a-protein is a light-harvesting complex found in dinoflagellates, which has an unusually high fraction of carotenoids. The carotenoids are directly involved in the energy transfer to chlorophyll with high efficiency. The detailed mechanism of energy transfer and the roles of the protein in the process remain debated in the literature, in part because most calculations have focused on a limited number of chromophore structures. Here we investigate the magnitude of the fluctuations of the site energies of individual and coupled chromophores, as the results are essential to the understanding of experimental spectra and the energy transfer mechanism. To this end, we sampled conformations of the PCP complex by means of classical and quantum mechanical/molecular mechanical (QM/MM) molecular dynamics simulations. Subsequently we performed (supermolecular) excitation energy calculations on a statistically significant number of snapshots using TD-LC-DFT/CAM-B3LYP and the semiempirical time-dependent long-range corrected density functional tight binding (TD-LC-DFTB2) as the QM method. We observed that the magnitude of the site energy fluctuations is large compared to the differences of the site energies between the chromophores, and this also holds for the coupled chromophores. We also investigated the composition of the coupled states, the effect of coupling on the absorption spectra, as well as transition dipole moment orientations and the possibility of delocalized states with Chl a. Our study thus complements previous computational studies relying on a single structure and establishes the most prominent features of the coupled chromophores that are essential to the robustness of the energy transfer process.

A Robust and Versatile QM/MM Interface for Molecular Dynamics in GROMOS

The integration of quantum mechanics and molecular mechanics (QM/MM) within molecular dynamics simulations is crucial to accurately model complex biochemical systems. Here, we present an enhanced implementation of the QM/MM interface in the GROMOS simulation package, introducing significant improvements in functionality and user control. We present new features, including the link atom scheme, which allows the modeling of QM regions as a part of bigger molecules. Benchmark tests on various systems, including QM water in water, amino acids in water, and tripeptides validate the reliability of the new functionalities. Performance evaluations demonstrate that the updated implementation is efficient, with the primary computational burden attributed to the QM program rather than the QM/MM interface or the MD program itself. The improved QM/MM interface enables more advanced investigations into biomolecular reactivity, enzyme catalysis, and other phenomena requiring detailed quantum mechanical treatment within classical simulations. This work represents a significant advancement in the capabilities of GROMOS, providing enhanced tools to explore complex molecular systems.

Evaluation of Density-Functional Tight-Binding Methods for Simulation of Protic Molecular Ion Pairs

In this work, we benchmark the accuracy of the density-functional tight-binding (DFTB) method, namely the long-range corrected second-order (LC-DFTB2) and third-order (DFTB3) models, for predicting energetics of imidazolium-based ionic liquid (IL) ion pairs. We compare the DFTB models against popular density functionals such as LC-ωPBE and B3LYP, using ab initio domain-based local pair-natural orbital coupled cluster (DLPNO-CC) energies as reference. Calculations were carried out in the gas phase, as well as in aqueous solution using implicit solvent methods. We find that the LC-DFTB2 model shows excellent performance in the gas phase and agrees well with reference energies in implicit solvent, often outperforming DFTB3 predictions for complexation energetics. Our study identifies a range of opportunities for use of the LC-DFTB method and quantifies its sensitivity to protonation states and the types of chemical interactions between ion pairs.

Advancing band structure simulations of complex systems of C, Si and SiC: a machine learning driven density functional tight-binding approach

We present a machine learning (ML) workflow for optimizing electronic band structures using density functional tight binding (DFTB) to replicate the results of costly hybrid functional calculations. The workflow is trained on carbon, silicon, and silicon carbide systems, encompassing bulk, slab, and defect geometries. Our method accurately reproduces hybrid functional results by applying a DFTB-ML scheme to train and predict the scaling parameters of two-center integrals and on-site energies, which is particularly accurate for electronic band structures near the Fermi energy. The DFTB-ML model demonstrates excellent scaling transferability, enabling training on smaller systems while maintaining hybrid functional-level accuracy when predicting larger systems. The high accuracy and adaptability of our model highlight its potential for precise band structure predictions across diverse chemical environments.

Simulation of 24,000 Electron Dynamics: Real-Time Time-Dependent Density Functional Theory (TDDFT) with the Real-Space Multigrids (RMG)

We present the theory, implementation, and benchmarking of a real-time time-dependent density functional theory (RT-TDDFT) module within the RMG code, designed to simulate the electronic response of molecular systems to external perturbations. Our method offers insights into nonequilibrium dynamics and excited states across a diverse range of systems, from small organic molecules to large metallic nanoparticles. Benchmarking results demonstrate excellent agreement with established TDDFT implementations and showcase the superior stability of our time integration algorithm, enabling long-term simulations with minimal energy drift. The scalability and efficiency of RMG on massively parallel architectures allow for simulations of complex systems, such as plasmonic nanoparticles with thousands of atoms. Future extensions, including nuclear and spin dynamics, will broaden the applicability of this RT-TDDFT implementation, providing a powerful toolset for studies of photoactive materials, nanoscale devices, and other systems where real-time electronic dynamics is essential.

Revisiting Water Adsorption on TiO2 and ZnO Surfaces: An SCC-DFTB Molecular Dynamics Study

Metal oxides (MOs) are the key materials in applications of biomedicine industrial technologies due to their versatile features. Knowing their possible toxicity level is crucial given some specific environments, particularly in water. We have learned that their reactivity almost depends on the electronic structure on the surface of the MOs. Thus, a detailed understanding of the electronic structure on the surface and its reactivity processes is useful for determining the toxicity in MOs and defining good descriptive parameters. We simulated the interaction of ZnO and TiO2 slab models with water and checked their geometric and electronic structure changes from the bulk of the material to the water interface. To this end, we used the density functional tight binding theory coupled with finite temperature molecular dynamics. We have observed the interaction of water with the MO surface in terms of electronic and geometric parameters for several conditions, such as temperature, hydrogenated or clean, and exposed surface. In doing so, we provide molecular-level insights into topographical and electronic processes on MO surfaces besides finding critical points on the surface that can explain the initialization of dissolution processes. Thus, we reveal information about potential toxicity descriptors in a systematic analysis approach.

Mechanistic Insights into the Eco-Friendly Conifer Cone Extract's Corrosion Inhibition on Steel Rebar and Cement Mortar: An Experimental and Simulation Approach

This study investigates the corrosion inhibition effects of eco-friendly conifer cone extract (CCE) on steel rebars embedded in cement mortar exposed to 3.5% NaCl under alternate wet/dry cycles. CCE concentrations of 0, 0.5, 1.0, 1.5, and 2.0% (denoted CCM0 to CCM4) were tested. Electrochemical and weight loss analyses revealed that 0.5% CCE significantly enhanced corrosion resistance, achieving 84.8% inhibition efficiency via polarization methods and a reduced corrosion rate of 9.46 mmpy. Chloride-binding studies indicated that 0.5% CCE improved adsorption intensity and multilayer adsorption constants compared to those of the control, as confirmed by Freundlich and Harkins-Jura isotherms. Surface analyses using SEM/EDS and AFM demonstrated the formation of a dense, protective passive layer on steel rebar surfaces, effectively reducing the surface roughness to 41.05 nm in CCM1 specimens. Theoretical simulations using SCC-DFTB and molecular dynamics showed a strong interaction between CCE functional groups and the iron surface, supporting experimental findings. Mechanical and porosity evaluations confirmed that 0.5% CCE maintained compressive strength and permeability while improving corrosion resistance. These results position CCE as a cost-effective, eco-friendly inhibitor with potential applications in protecting reinforced concrete structures in chloride-rich environments.

First-principles calculations of quartz-coesite interfaces

Atomistic interface structures compatible with periodic boundary conditions for the strain-induced subsolidus martensitic transition between quartz and coesite have been investigated. We identified layers of atoms that remained unchanged in terms of neighbor interactions throughout the transformation. Our analysis revealed that the orientation relationships between quartz and coesite, namely (1011)Qz||(010)Coe and (1321)Qz||(010)Coe, are consistent with experimental observations. Using density-functional-theory-based tight-binding model cal-culations, we determined an interface energy of approximately 660 mJ m-2 for these interfaces and strain energies of 196 (6) and 2760 (160) J mol-1 atom-1 for the (1321)Qz||(010)Coe and (1011)Qz||(010)Coe oriented interfaces, respectively. To visualize these interface structures and facilitate their identification in experiments, we simulated high-resolution transmission electron microscopy images and electron diffraction patterns.

End-Point Affinity Estimation of Galectin Ligands by Classical and Semiempirical Quantum Mechanical Potentials

The use of quantum mechanical potentials in protein-ligand affinity prediction is becoming increasingly feasible with growing computational power. To move forward, validation of such potentials on real-world challenges is necessary. To this end, we have collated an extensive set of over a thousand galectin inhibitors with known affinities and docked them into galectin-3. The docked poses were then used to systematically evaluate several modern force fields and semiempirical quantum mechanical (SQM) methods up to the tight-binding level under consistent computational workflow. Implicit solvation models available with the tested methods were used to simulate solvation effects. Overall, the best methods in this study achieved a Pearson correlation of 0.7-0.8 between the computed and experimental affinities. There were differences between the tested methods in their ability to rank ligands across the entire ligand set as well as within subsets of structurally similar ligands. A major discrepancy was observed for a subset of ligands that bind to the protein via a halogen bond, which was clearly challenging for all the tested methods. The inclusion of an entropic term calculated by the rigid-rotor-harmonic-oscillator approximation at SQM level slightly worsened correlation with experiment but brought the calculated affinities closer to experimental values. We also found that the success of the prediction strongly depended on the solvation model. Furthermore, we provide an in-depth analysis of the individual energy terms and their effect on the overall prediction accuracy.

Unconventional Near-Equilibrium Nucleation of Graphene on Si-Terminated SiC(0001) Surface

The transfer-free character of graphene growth on Silicon Carbide (SiC) makes it compatible with state-of-the-art Si semiconductor technologies for directly fabricating high-end electronics. Although significant progress has been achieved in epitaxial growth of graphene on SiC recently, the underlying nucleation mechanism remains elusive. Here, we present a theoretical study to elucidate graphene near-equilibrium nucleation on Si-terminated hexagonal-SiC(0001) surface. It is found that the ultra-large lattice mismatch between SiC(0001) surface and graphene and the highly localized electron distribution on SiC(0001) surface lead to a distinctive nucleation process: (i) Most of the magic carbon clusters on SiC(0001) show only C1 symmetry and are mainly composed of pentagonal rings; (ii) Two possible nucleation pathways are revealed, i.e., longitudinal and circular modes; (iii) Carbon clusters are more stable on flat terraces than near atomic step edges. Based on above findings, a graphene nucleation diagram on SiC(0001) is established and experimentally observed contradictories for graphene growth on SiC(0001) are answered. Our in-depth understanding on graphene nucleation on SiC(0001) extends nucleation mechanisms of 2D crystals and will benefit high-quality graphene growth on SiC(0001).

High Stability, Piezoelectric Response, and Promising Photocatalytic Activity on the New Pentagonal CGeP4 Monolayer

This study introduces the penta-structured semiconductor p-CGeP4 through density functional theory simulations, which possesses an indirect band gap transition of 3.20 eV. Mechanical analysis confirms the mechanical stability of p-CGeP4, satisfying Born-Huang criteria. Notably, p-CGeP4 has significant direct (e 31 = -11.27 and e 36 = -5.34 × 10-10 C/m) and converse (d 31 = -18.52 and d 36 = -13.18 pm/V) piezoelectric coefficients, surpassing other pentagon-based structures. Under tensile strain, the band gap energy increases to 3.31 eV at 4% strain, then decreases smoothly to 1.97 eV at maximum stretching, representing an ∼38% variation. Under compressive strain, the band gap decreases almost linearly to 2.65 eV at -8% strain and then drops sharply to 0.97 eV, an ∼69% variation. Strongly basic conditions result in a promising band alignment for the new p-CGeP4 monolayer. This suggests potential photocatalytic behavior across all tensile strain regimes and significant compression levels (ε = 0% to -8%). This study highlights the potential of p-CGeP4 for groundbreaking applications in nanoelectronic devices and materials engineering.

An Unexpected Water Channel in the Light-Harvesting Complex of a Diatom: Implications for the Switch between Light Harvesting and Photoprotection

Many important processes in cells depend on the transfer of protons through water wires embedded in transmembrane proteins. Herein, we have performed more than 55 μs all-atom simulations of the light-harvesting complex of a diatom, i.e., the fucoxanthin and chlorophyll a/c binding protein (FCP) from the marine diatom Phaeodactylum tricornutum. Diatoms are unique models to study natural photosynthesis as they exert an efficient light-harvesting machinery with a robust pH-dependent photoprotective mechanism. The present study reports on the dynamics of an FCP monomer, a dimer, and a tetramer at varying pH values. Surprisingly, we have identified at low pH a water channel across FCP that selectively hydrates and protonates the acrylate of a Chl-c2 pigment located in the middle of the membrane. These results are further supported by QM/MM calculations and steered MD simulations on the proton dynamics. It is shown that proton hopping events between the lumenal and stromal sides of the membrane through the observed water channel are highly disfavored. This hindrance is due to the presence of residues Arg31 and Lys82 close to the acrylate, along with an hydronium desolvation penalty that shows close similarities to the water conductance in aquaporins. Furthermore, we provide strong evidence that this identified water channel is governing the transition between light-harvesting and photoprotective states of the major FCP complex in the diatom P. tricornutum.

Creation of an Fe3P Schreibersite Density Functional Tight Binding Model for Astrobiological Simulations

The mineral schreibersite, e.g., Fe3P, is commonly found in iron-rich meteorites and could have served as an abiotic phosphorus source for prebiotic chemistry. However, atomistic calculations of its degradation chemistry generally require quantum simulation approaches, which can be too computationally cumbersome to study sufficient time and length scales for this process. In this regard, we have created a computationally efficient semiempirical quantum density functional tight binding (DFTB) model for iron and phosphorus-containing materials by adopting an existing semiautomated workflow that represents many-body interactions by linear combinations of Chebyshev polynomials. We have utilized a relatively small training set to optimize a DFTB model that is accurate for schreibersite physical and chemical properties, including its bulk properties, surface energies, and water absorption. We then show that our model shows strong transferability to several iron phosphide solids as well as multiple allotropes of iron metal. Our resulting DFTB parametrization will allow us to interrogate schreibersite aqueous decomposition at longer time and length scales than standard quantum approaches, providing for more detailed investigations of its role in prebiotic chemistry on early Earth.

Large-Area Transfer of Nanometer-Thin C60 Films

Fullerenes, with well-defined molecular structures and high scalability, hold promise as fundamental building blocks for creating a variety of carbon materials. The fabrication and transfer of large-area films with precisely controlled thicknesses and morphologies on desired surfaces are crucial for designing and developing fullerene-based materials and devices. In this work, we present strategies for solid-state transferring C60 molecular nanometer-thin films, with dimensions of centimeters in lateral size and thicknesses controlled in the range of 1-20 nm, onto various substrates. Furthermore, we have successfully fabricated centimeter-wide graphene/C60/graphene heterostructures through layer-by-layer stacking of C60 and graphene films. This transfer methodology is versatile, allowing for the complete transfer of chemically modified C60 films, including oxygenated C60 films and C60Pdn organometallic polymer films. Additionally, direct solid-state transfer of C60 and C60Pdn films onto electrode surfaces has enabled their electrocatalytic performance for the hydrogen evolution reaction to be probed directly. This thin-film transfer strategy allows precise manipulation of large-area, ultrathin C60 films on various substrates, providing a platform for fullerene chemistry and the experimental synthesis of artificial carbon structures.

Equipartitioning of Molecular Degrees of Freedom in MD Simulations of Gaseous Systems via an Advanced Thermostatization Strategy

This work introduces a dedicated thermostatization strategy for molecular dynamics simulations of gaseous systems. The proposed thermostat is based on the stochastic canonical velocity rescaling approach by Bussi and co-workers and is capable of ensuring an equal distribution of the kinetic energy among the translational, rotational, and vibrational degrees of freedom. The outlined framework ensures the correct treatment of the kinetic energy in gaseous systems, which is typically not the case in standard approaches due to the limited number of collisions between particles associated with a large free mean path. Additionally, an efficient strategy to effectively correct for intramolecular contributions to the virial in quantum mechanical simulations is presented. The equipartitioning thermostat was successfully tested by the determination of pV diagrams for carbon dioxide and methane at the density functional tight binding level of theory. The results unequivocally demonstrate that the equipartitioning thermostat can effectively achieve an equal distribution of the kinetic energy among the different degrees of freedom, thereby ensuring correct pressure in gaseous systems. Furthermore, RDF calculations show the capability of the proposed method to accurately depict the structure of gaseous systems, as well as enable an adequate treatment of gas molecules under confinement, as exemplified by an MD simulation of (CO2)50@MOF-5.

Mapping the Extended Ground State Reactivity Landscape of a Photoswitchable Molecule at a Single Molecular Level

Photoswitchable molecules with structural flexibility can exhibit a complex ground state potential energy landscape due to the accessibility of multiple metastable states at merely low energy barriers. However, conventional bulk analytical techniques are limited in their ability to probe these metastable ground states and their relative energies. This is partially due to the difficulty of inducing changes in small molecules in their ground state, as they do not respond to external stimuli, such as mechanical force, unless they are incorporated into larger polymer networks. This hinders the understanding of ground-state reactivity and the associated dynamics. In this study, we leverage the "perturb-probe" capability of the single molecular break junction technique to explore the ground state 6π electrocyclization of a dithienylethene (DTE) derivative, a process traditionally achieved through electro- or photochromism. Our findings reveal that this reaction can also be triggered by mechanical force and an oriented electric field at the single-molecule level via ground state dynamics. We demonstrated that external perturbations could control the ground state reaction dynamics and steer the reaction trajectories away from constraints imposed by typical excited state dynamics. This strategy will thus offer access to a whole new dimension of single molecular electromechanical conversions and extend our knowledge of the ground state potential energy surface available to molecules under external force fields.

Atomic-level structure of the amorphous drug atuliflapon via NMR crystallography

We determine the complete atomic-level structure of the amorphous form of the drug atuliflapon, a 5-lipooxygenase activating protein (FLAP) inhibitor, via chemical-shift-driven NMR crystallography. The ensemble of preferred structures allows us to identify a number of specific conformations and interactions that stabilize the amorphous structure. These include preferred hydrogen-bonding motifs with water and with other drug molecules, as well as conformations of the cyclohexane and pyrazole rings that stabilize structure by indirectly allowing for optimization of hydrogen bonding.

Engineering Trifluoromethyl Groups in Porous Coordination Polymers to Enhance Stability and Regulate Pore Window for Hexane Isomers Separation

Effective separation of hexane (C6) isomers is critical for a variety of industrial applications but conventional distillation methods are energy-intensive. Adsorptive separations based on porous coordination polymers (PCPs) offer a promising alternative due to their exceptional porosity and tunable properties. However, there is still an urgent need to develop PCPs with high stability and separation performance. This study investigates how substituting a methyl (-CH3) group with a trifluoromethyl (-CF3) group can regulate pores and hydrophobicity in PCPs. This precise adjustment aims to enhance stability and improve the kinetic separation performance of hydrophobic C6 isomers by considering the size and hydrophobicity of the trifluoromethyl group. Two isostructural PCPs with pcu topology, PCP-CH3 and PCP-CF3, were synthesized to vary pore diameters and hydrophobicity based on the presence of -CH3 or -CF3 groups. PCP-CF3 showed greater stability in water compared to PCP-CH3. While PCP-CH3 had high adsorption capacities, it lacked selectivity, whereas PCP-CF3 demonstrated improved selectivity, particularly in excluding dibranched isomers. Dynamic column separation experiments revealed that PCP-CF3 could selectively adsorb linear and monobranched isomers over dibranched isomers at room temperature. These findings highlight the potential of fluorine-modified PCPs for efficient isomer separation and underscore the importance of stability improvement strategies.

Hybrid Materials Based on Carbon Nanotubes and Tetra- and Octa-Halogen-Substituted Zinc Phthalocyanines: Sensor Response Toward Ammonia from the Quantum-Chemical Point of View

This paper presents the results of quantum-chemical modeling performed by the Density Functional-Based Tight Binding (DFTB) method to investigate the change in the band structure of hybrid materials based on carbon nanotubes and unsubstituted, tetra-, or octa-halogen-substituted zinc phthalocyanines upon the adsorption of ammonia molecules. The study showed that the electrical conductivity of these materials and its changes in the case of interaction with ammonia molecules depend on the position of the impurity band formed by the orbitals of macrocycle atoms relative to the forbidden energy gap of the hybrids. The sensor response of the hybrids containing halogenated phthalocyanines was lower by one or two orders of magnitude, depending on the number of substituents, compared to the hybrid with unsubstituted zinc phthalocyanine. This result was obtained by calculations performed using the nonequilibrium Green's functions (NEGF) method, which demonstrated a change in the electrical conductivity of the hybrids upon the adsorption of ammonia molecules. The analysis showed that in order to improve the sensor characteristics of CNT-based hybrid materials, preference should be given to those phthalocyanines in which substituents contribute to an increase in HOMO energy relative to the unsubstituted macrocycles.

Understanding the synergistic interaction between a 1,3,4-thiadiazole derivative and amphotericin B using spectroscopic and theoretical studies

We present a comprehensive spectroscopic study supported by theoretical quantum chemical calculations conducted on a molecular system (4-(5-methyl-1,3,4-thiadiazol-2-yl)benzene-1,3-diol (C1) and the antibiotic Amphotericin B (AmB)) that exhibits highly synergistic properties. We previously reported the strong synergism of this molecular system and now wish to present related stationary measurements of UV-Vis absorption, fluorescence, and fluorescence anisotropy in a polar, aprotic solvent (DMSO and a PBS buffer), followed by time-resolved fluorescence intensity and anisotropy decay studies using different ratios of the selected 1,3,4-thiadiazole derivative to Amphotericin B. Absorption spectra measured for the system revealed discrepancies in terms of the shapes of absorption bands, particularly in PBS. Fluorescence emission spectra revealed that the addition of C1 molecules triggered significant changes in the emission spectra of the system. Measurements of the fluorescence lifetimes and fluorescence anisotropy supported by synchronous spectra clearly showed evidence of disaggregation. The AmB molecular aggregates indicated interaction of C1 with the antibiotic at points responsible for the formation of dimer structures. The spectroscopic results were further corroborated, analyzed, and interpreted using the methods of quantum mechanical modelling. Analyses based on the density functional tight-binding and time-dependent density functional theory confirmed that molecular interactions between "small" molecules and AmB lead to a significant increase in the clinical efficacy of the antibiotic.

Photoinduced Electron-Nuclear Dynamics of Fullerene and Its Monolayer Networks in Solvated Environments

The recently synthesized monolayer fullerene network in a quasi-hexagonal phase (qHP-C60) exhibits superior electron mobility and optoelectronic properties compared to molecular fullerene (C60), making it highly promising for a variety of applications. However, the microscopic carrier dynamics of qHP-C60 remain unclear, particularly in realistic environments, which are of significant importance for applications in optoelectronic devices. Unfortunately, traditional ab initio methods are prohibitive for capturing the real-time carrier dynamics of such large systems due to their high computational cost. In this work, we present the first real-time electron-nuclear dynamics study of qHP-C60 using velocity-gauge density functional tight binding, which enables us to perform several picoseconds of excited-state electron-nuclear dynamics simulations for nanoscale systems with periodic boundary conditions. When applied to C60, qHP-C60, and their solvated counterparts, we demonstrate that water/moisture significantly increases the electron-hole recombination time in C60 but has little impact on qHP-C60. Our excited-state electron-nuclear dynamics calculations show that qHP-C60 is extremely unique and enable exploration of time-resolved dynamics for understanding excited-state processes of large systems in complex, solvated environments.

Susceptibility formulation of density matrix perturbation theory

Density matrix perturbation theory based on recursive Fermi-operator expansions provides a computationally efficient framework for time-independent response calculations in quantum chemistry and materials science. From a perturbation in the Hamiltonian, we can calculate the first-order perturbation in the density matrix, which then gives us the linear response in the expectation values for some chosen set of observables. We present an alternative, dual formulation, where we instead calculate the static susceptibility of an observable, which then gives us the linear response in the expectation values for any number of different Hamiltonian perturbations. We show how the calculation of the susceptibility can be performed with the same expansion schemes used in recursive density matrix perturbation theory, including generalizations to fractional occupation numbers and self-consistent linear response calculations, i.e., similar to density functional perturbation theory. As with recursive density matrix perturbation theory, the dual susceptibility formulation is well suited for numerically thresholded sparse matrix algebra, which has linear scaling complexity for sufficiently large sparse systems. Similarly, the recursive computation of the susceptibility also seamlessly integrates with the computational framework of deep neural networks used in artificial intelligence (AI) applications. This integration enables the calculation of quantum response properties that can leverage cutting-edge AI-hardware, such as NVIDIA Tensor Cores or Google Tensor Processing Units. We demonstrate performance for recursive susceptibility calculations using NVIDIA Graphics Processing Units and Tensor Cores.

Canonical coupled cluster binding benchmark for nanoscale noncovalent complexes at the hundred-atom scale

In this study, we introduce two datasets for nanoscale noncovalent binding, featuring complexes at the hundred-atom scale, benchmarked using coupled cluster with single, double, and perturbative triple [CCSD(T)] excitations extrapolated to the complete basis set (CBS) limit. The first dataset, L14, comprises 14 complexes with canonical CCSD(T)/CBS benchmarks, extending the applicability of CCSD(T)/CBS binding benchmarks to systems as large as 113 atoms. The second dataset, vL11, consists of 11 even larger complexes, evaluated using the local CCSD(T)/CBS method with stringent thresholds, covering systems up to 174 atoms. We compare binding energies obtained from local CCSD(T) and fixed-node diffusion Monte Carlo (FN-DMC), which have previously shown discrepancies exceeding the chemical accuracy threshold of 1 kcal/mol in large complexes, with the new canonical CCSD(T)/CBS results. While local CCSD(T)/CBS agrees with canonical CCSD(T)/CBS within binding uncertainties, FN-DMC consistently underestimates binding energies in π-π complexes by over 1 kcal/mol. Potential sources of error in canonical CCSD(T)/CBS are discussed, and we argue that the observed discrepancies are unlikely to originate from CCSD(T) itself. Instead, the fixed-node approximation in FN-DMC warrants further investigation to elucidate these binding discrepancies. Using these datasets as reference, we evaluate the performance of various electronic structure methods, semi-empirical approaches, and machine learning potentials for nanoscale complexes. Based on computational accuracy and stability across system sizes, we recommend MP2+aiD(CCD), PBE0+D4, and ωB97X-3c as reliable methods for investigating noncovalent interactions in nanoscale complexes, maintaining their promising performance observed in smaller systems.

Insights into Carvone: Fatty Acid Hydrophobic NADES for Alkane Solubilization

The urge to adopt cleaner technologies drives the search for novel and sustainable materials such as Hydrophobic Natural Deep Eutectic Solvents (HNADESs), a new class of green solvents characterized by their low toxicity, biodegradability, and tunable properties, aiming to be applied in various fields for handling non-polar substances. In this work, the solubilization of hydrocarbons in type V HNADESs (non-ionic organic molecules) formed by mixing carvone, a natural monoterpenoid, with organic acids (hexanoic to decanoic acids) is examined by applying both experimental and theoretical approaches. The synthesis and physicochemical characterization of different HNADESs allowed us to tailor their properties, aiming for optimal interactions with desired hydrocarbons. The solubilization of hydrocarbons in CAR:C10AC (1:1) HNADES is evaluated in terms of HNADES content, temperature, and the structure of the hydrocarbon itself (C6, C10, and C14 being the selected ones). To gain deeper insights into the underlying mechanisms of interactions between the solvents and the alkanes, a comprehensive multiscale computational study was carried out to analyze the nature of the interactions, the changes upon formation of HNADESs and hydrocarbon solubilization in the fluid's nanostructure, and the possible toxicological effects of the solvents. The findings hold the potential to significantly impact the realm of hydrocarbon exploration and utilization.

Advanced Charge Extended Hückel (CEH) Model and a Consistent Adaptive Minimal Basis Set for the Elements Z = 1-103

The Charge Extended Hückel (CEH) model, initially introduced for adaptive atomic orbital (AO) basis set construction (J. Chem. Phys. 2023, 159, 164108), has been significantly revised to enhance accuracy and robustness, particularly in challenging electronic situations. This revision includes an extension toward f-elements, covering actinoids with their f-electrons in the valence space. We present a novel noniterative approximation for the electrostatic contribution to the effective Fock matrix, which substantially improves performance in polar or charged systems. Additionally, the training data set for elements Z = 1-103 has been expanded to encompass even more chemically diverse reference molecules as well as dipole moments and shell populations in addition to atomic charges. It includes a greater variety of "mindless" molecules (MLMs) as well as more complex electronic structures through open-shell and highly charged species. The revised method achieves mean absolute errors for atomic charges q of approximately 0.02 e- for randomly selected (mostly organic) molecules and 0.09 e- for MLMs, outperforming both classical charge models and established tight-binding methods. Furthermore, the revised CEH model has been validated through density functional theory calculations with the updated adaptive q-vSZP AO basis set on common thermochemical databases. Consistent with the extension of the CEH model, q-vSZP has also been variationally optimized and tested for elements Z = 58-71 and 87-103. The original versions of both CEH and q-vSZP are now considered deprecated.

Heavy-boundary mode patterning and dynamics of topological phonons in polymer chains and supramolecular lattices on surfaces

In topological band theory, phonon boundary modes consequence of a topologically non-trivial  band structure feature desirable properties for atomically-precise technologies, such as robustness against defects, waveguiding, and one-way transport. These topological phonon boundary modes remain to be studied both theoretically and experimentally in synthetic materials, such as polymers and supramolecular assemblies at the atomistic level under thermal fluctuations. Here we show by means of molecular simulations, that surface-confined Su-Schrieffer-Heeger (SSH) phonon analogue models express robust topological phonon boundary modes at heavy boundaries and under thermal fluctuations. The resulting bulk-heavy boundary correspondence enables patterning of boundary modes in polymer chains and weakly-interacting supramolecular lattices. Moreover, we show that upon excitation of a single molecule, propagation along heavy-boundary modes differs from free boundary modes. Our work is an entry to topological vibrations in supramolecular systems, and may find applications in the patterning of phonon circuits and realization of Hall effect phonon analogues at the molecular scale.

Non-adiabatic Couplings in Surface Hopping with Tight Binding Density Functional Theory: The Case of Molecular Motors

Nonadiabatic molecular dynamics (NAMD) has become an essential computational technique for studying the photophysical relaxation of molecular systems after light absorption. These phenomena require approximations that go beyond the Born-Oppenheimer approximation, and the accuracy of the results heavily depends on the electronic structure theory employed. Sophisticated electronic methods, however, make these techniques computationally expensive, even for medium size systems. Consequently, simulations are often performed on simplified models to interpret the experimental results. In this context, a variety of techniques have been developed to perform NAMD using approximate methods, particularly density functional tight binding (DFTB). Despite the use of these techniques on large systems, where ab initio methods are computationally prohibitive, a comprehensive validation has been lacking. In this work, we present a new implementation of trajectory surface hopping combined with DFTB, utilizing nonadiabatic coupling vectors. We selected the methaniminium cation and furan systems for validation, providing an exhaustive comparison with the higher-level electronic structure methods. As a case study, we simulated a system from the class of molecular motors, which has been extensively studied experimentally but remains challenging to simulate with ab initio methods due to its inherent complexity. Our approach effectively captures the key photophysical mechanism of dihedral rotation after the absorption of light. Additionally, we successfully reproduced the transition from the bright to dark states observed in the time-dependent fluorescence experiments, providing valuable insights into this critical part of the photophysical behavior in molecular motors.

The seventh blind test of crystal structure prediction: structure ranking methods

A seventh blind test of crystal structure prediction has been organized by the Cambridge Crystallographic Data Centre. The results are presented in two parts, with this second part focusing on methods for ranking crystal structures in order of stability. The exercise involved standardized sets of structures seeded from a range of structure generation methods. Participants from 22 groups applied several periodic DFT-D methods, machine learned potentials, force fields derived from empirical data or quantum chemical calculations, and various combinations of the above. In addition, one non-energy-based scoring function was used. Results showed that periodic DFT-D methods overall agreed with experimental data within expected error margins, while one machine learned model, applying system-specific AIMnet potentials, agreed with experiment in many cases demonstrating promise as an efficient alternative to DFT-based methods. For target XXXII, a consensus was reached across periodic DFT methods, with consistently high predicted energies of experimental forms relative to the global minimum (above 4 kJ mol-1 at both low and ambient temperatures) suggesting a more stable polymorph is likely not yet observed. The calculation of free energies at ambient temperatures offered improvement of predictions only in some cases (for targets XXVII and XXXI). Several avenues for future research have been suggested, highlighting the need for greater efficiency considering the vast amounts of resources utilized in many cases.

Quantum Simulations of Radiation Damage in a Molecular Polyethylene Analog

An atomic-level understanding of radiation-induced damage in simple polymers like polyethylene is essential for determining how these chemical changes can alter the physical and mechanical properties of important technological materials such as plastics. Ensembles of quantum simulations of radiation damage in a polyethylene analog are performed using the Density Functional Tight Binding method to help bind its radiolysis and subsequent degradation as a function of radiation dose. Chemical degradation products are categorized with a graph theory approach, and occurrence rates of unsaturated carbon bond formation, crosslinking, cycle formation, chain scission reactions, and out-gassing products are computed. Statistical correlations between product pairs show significant correlations between chain scission reactions, unsaturated carbon bond formation, and out-gassing products, though these correlations decrease with increasing atom recoil energy. The results present relatively simple chemical descriptors as possible indications of network rearrangements in the middle range of excitation energies. Ultimately, the work provides a computational framework for determining the coupling between nonequilibrium chemistry in polymers and potential changes to macro-scale properties that can aid in the interpretation of future radiation damage experiments on plastic materials.