Ultra-fast computation of electronic spectra for large systems by tight-binding based simplified Tamm-Dancoff approximation (sTDA-xTB)

Screening potential dye sensitizers for water splitting photocatalysts using a genetic algorithm

Addressing the global fossil energy crisis necessitates the efficient utilization of sustainable energy sources. Hydrogen, a green fuel, can be generated using sunlight, water, and a photocatalyst. Employing sensitizers holds promise for enhancing photocatalyst performance, enabling high rates of hydrogen evolution through increased visible light absorption. However, sifting through millions of diverse molecules to identify suitable dyes for specific photocatalysts poses a significant challenge. In this study, we integrate genetic algorithm and geometry-frequency-noncovalent extended tight binding methods to efficiently screen 2.6 million potential sensitizers with a D-π-A-π-AA structure within a short timeframe. Subsequently, these optimized sensitizers are rigorously reassessed by using DFT/TDDFT methods, elucidating why they may serve as superior dyes compared to the reference dye WS5F, particularly in terms of light absorption, driving force, binding energy, etc. Additionally, our methodology uncovers molecular motifs of particular interest, including the furan π-bridge and the double cyano anchoring acceptor, which are prevalent in the most promising set of molecules. The developed genetic algorithm workflow and dye design principles can be extended to various compelling projects, such as dye-sensitized solar cells, organic photovoltaics, photo-induced redox reactions, pharmaceuticals, and beyond.

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.

The eXact integral simplified time-dependent density functional theory (XsTD-DFT)

In the framework of simplified quantum chemistry methods, we introduce the eXact integral simplified time-dependent density functional theory (XsTD-DFT). This method is based on the simplified time-dependent density functional theory (sTD-DFT), where all semi-empirical two-electron integrals are replaced by exact one- and two-center two-electron integrals, while other approximations from sTD-DFT are kept. The performance of this new parameter-free XsTD-DFT method was benchmarked on excited state and (non)linear response properties, including ultra-violet/visible absorption, first hyperpolarizability, and two-photon absorption (2PA). For a set of 77 molecules, the results from the XsTDA approach were compared to the TDA data. XsTDA/B3LYP excitation energies only deviate on average by 0.14 eV from TDA while drastically cutting computational costs by a factor of 20 or more depending on the energy threshold chosen. The absolute deviations of excitation energies with respect to the full scheme are decreasing with increasing system size, showing the suitability of XsTDA/XsTD-DFT to treat large systems. Comparing XsTDA and its predecessor sTDA, the new scheme generally improves excitation energies and oscillator strengths, in particular, for charge transfer states. TD-DFT first hyperpolarizability frequency dispersions for a set of push-pull π-conjugated molecules are faithfully reproduced by XsTD-DFT, while the previous sTD-DFT method provides redshifted resonance energy positions. Excellent performance with respect to the experiment is observed for the 2PA spectrum of the enhanced green fluorescent protein. The obtained robust accuracy similar to TD-DFT at a fraction of the computational cost opens the way for a plethora of applications for large systems and in high throughput screening studies.

MISATO: machine learning dataset of protein-ligand complexes for structure-based drug discovery

Large language models have greatly enhanced our ability to understand biology and chemistry, yet robust methods for structure-based drug discovery, quantum chemistry and structural biology are still sparse. Precise biomolecule-ligand interaction datasets are urgently needed for large language models. To address this, we present MISATO, a dataset that combines quantum mechanical properties of small molecules and associated molecular dynamics simulations of ~20,000 experimental protein-ligand complexes with extensive validation of experimental data. Starting from the existing experimental structures, semi-empirical quantum mechanics was used to systematically refine these structures. A large collection of molecular dynamics traces of protein-ligand complexes in explicit water is included, accumulating over 170 μs. We give examples of machine learning (ML) baseline models proving an improvement of accuracy by employing our data. An easy entry point for ML experts is provided to enable the next generation of drug discovery artificial intelligence models.

Second-order nonlinear optical properties of X-shaped pyrazine derivatives

This work reports an investigation of the second-order NLO properties of two isomer series of X-shaped pyrazine derivatives, by means of HRS measurements and DFT calculations. The systems differ in the relative position of the donor and acceptor substituents with respect to the axis formed by the nitrogen atoms of the central pyrazine ring. Although the magnitude of the second harmonic signal is similar, HRS measurements revealed that the anisotropy of the NLO response strongly differs in the two chromophore series, the one of the 2,3-isomers being strikingly dipolar, while the one of the 2,6-isomers is mostly octupolar. The experimental observations are well supported by DFT calculations. In particular, the sum-over-states approach allows us to rationalize the different NLO anisotropies observed in the two isomer series through a detailed analysis of the symmetry of the low-lying excited states.

Searching the Chemical Space of Bicyclic Dienes for Molecular Solar Thermal Energy Storage Candidates

Photoswitches are molecular systems that are chemically transformed subsequent to interaction with light and they find potential application in many new technologies. The design and discovery of photoswitch candidates require intricate molecular engineering of a range of properties to optimize a candidate to a specific applications, a task which can be tackled efficiently using quantum chemical screening procedures. In this paper, we perform a large scale screening of approximately half a million bicyclic diene photoswitches in the context of molecular solar thermal energy storage using ab initio quantum chemical methods. We further device an efficient strategy for scoring the systems based on their predicted solar energy conversion efficiency and elucidate potential pitfalls of this approach. Our search through the chemical space of bicyclic dienes reveals systems with unprecedented solar energy conversion efficiencies and storage densities that show promising design guidelines for next generation molecular solar thermal energy storage systems.

Determining best practices for using genetic algorithms in molecular discovery

Genetic algorithms (GAs) are a powerful tool to search large chemical spaces for inverse molecular design. However, GAs have multiple hyperparameters that have not been thoroughly investigated for chemical space searches. In this tutorial, we examine the general effects of a number of hyperparameters, such as population size, elitism rate, selection method, mutation rate, and convergence criteria, on key GA performance metrics. We show that using a self-termination method with a minimum Spearman's rank correlation coefficient of 0.8 between generations maintained for 50 consecutive generations along with a population size of 32, a 50% elitism rate, three-way tournament selection, and a 40% mutation rate provides the best balance of finding the overall champion, maintaining good coverage of elite targets, and improving relative speedup for general use in molecular design GAs.

Development of NOTCH, an all-electron, beyond-NDDO semiempirical method: Application to diatomic molecules

In this work, we develop a new semiempirical method, dubbed NOTCH (Natural Orbital Tied Constructed Hamiltonian). Compared to existing semiempirical methods, NOTCH is less empirical in its functional form as well as parameterization. Specifically, in NOTCH, (1) the core electrons are treated explicitly; (2) the nuclear-nuclear repulsion term is calculated analytically, without any empirical parameterization; (3) the contraction coefficients of the atomic orbital (AO) basis depend on the coordinates of the neighboring atoms, which allows the size of AOs to depend on the molecular environment, despite the fact that a minimal basis set is used; (4) the one-center integrals of free atoms are derived from scalar relativistic multireference equation-of-motion coupled cluster calculations instead of empirical fitting, drastically reducing the number of necessary empirical parameters; (5) the (AA|AB) and (AB|AB)-type two-center integrals are explicitly included, going beyond the neglect of differential diatomic overlap approximation; and (6) the integrals depend on the atomic charges, effectively mimicking the "breathing" of AOs when the atomic charge varies. For this preliminary report, the model has been parameterized for the elements H-Ne, giving only 8 empirical global parameters. Preliminary results on the ionization potentials, electron affinities, and excitation energies of atoms and diatomic molecules, as well as the equilibrium geometries, vibrational frequencies dipole moments, and bond dissociation energies of diatomic molecules, show that the accuracy of NOTCH rivals or exceeds those of popular semiempirical methods (including PM3, PM7, OM2, OM3, GFN-xTB, and GFN2-xTB) as well as the cost-effective ab initio method Hartree-Fock-3c.

Cocrystallization of Two Negatively Charged Dimercaptomaleonitrile-Stabilized Silver Nanoclusters

Studies on the assembly of atomically precise metal nanoclusters (NCs) are of great significance in the nanomaterial field, which has attracted increasing interest in the last few decades. Herein, we report the cocrystallization of two negatively charged atom-precise silver nanoclusters, the octahedral [Ag₆₂(MNT)₂₄(TPP)₆]^8- (Ag₆₂) and the truncated-tetrahedral [Ag₂₂(MNT)₁₂(TPP)₄]^4- (Ag₂₂) in a 1:2 ratio (MNT^2- = dimercaptomaleonitrile, TPP = triphenylphosphine). As far as we know, a cocrystal containing two negatively charged NCs has seldom been reported. Single-crystal structure determinations reveal that the component Ag₂₂ and Ag₆₂ NCs both adopt core-shell structures. In addition, the component NCs were separately obtained by adjusting the synthetic conditions. This work enriches the structural diversity of silver NCs and extends the family of cluster-based cocrystals.

Histidine-Mediated Synthesis of Chiral Cobalt Oxide Nanoparticles for Enantiomeric Discrimination and Quantification

Chiral transition metal oxide nanoparticles (CTMOs) are attracting a lot of attention due to their fascinating properties. Nevertheless, elucidating the chirality induction mechanism often remains a major challenge. Herein, the synthesis of chiral cobalt oxide nanoparticles mediated by histidine (Co₃ O₄ @L-His and Co₃ O₄ @D-His for nanoparticles synthesized in the presence of L- and D-histidine, respectively) is investigated. Interestingly, these CTMOs exhibit remarkable and tunable chiroptical properties. Their analysis by x-ray photoelectron, Fourier transform infrared, and ultraviolet-visible absorption spectroscopy indicates that the ratio of Co²⁺ /Co³⁺ and their interactions with the imidazole groups of histidine are behind their chiral properties. In addition, the use of chiral Co₃ O₄ nanoparticles for the development of sensitive, rapid, and enantioselective circular dichroism-based sensors is demonstrated, allowing direct molecular detection and discrimination between cysteine or penicillamine enantiomers. The circular dichroism response of the chiral Co₃ O₄ exhibits a limit of detection and discrimination of cysteine and penicillamine enantiomers as low as 10 µm. Theoretical calculations suggest that the ligand exchange and the coexistence of both species adsorbed on the oxide surface are responsible for the enantiomeric discrimination. This research will enrich the synthetic approaches to obtain CTMOs and enable the extension of the applications and the discovery of new chiroptical properties.

Electronic circular dichroism from real-time propagation in state space

In this paper, we propose to compute the electronic circular dichroism (ECD) spectra of chiral molecules using a real-time propagation of the time-dependent Schrödinger equation (TDSE) in the space of electronic field-free eigenstates, by coupling TDSE with a given treatment of the electronic structure of the target. The time-dependent induced magnetic moment is used to compute the ECD spectrum from an explicit electric perturbation. The full matrix representing the transition magnetic moment in the space of electronic states is generated from that among pairs of molecular orbitals. In the present work, we show the ECD spectra of methyloxirane, of several conformers of L-alanine, and of the Λ-Co(acac)₃ complex, computed from a singly excited ansatz of time-dependent density functional theory eigenstates. The time-domain ECD spectra properly reproduce the frequency-domain ones obtained in the linear-response regime and quantitatively agree with the available experimental data. Moreover, the time-domain approach to ECD allows us to naturally go beyond the ground-state rotationally averaged ECD spectrum, which is the standard outcome of the linear-response theory, e.g., by computing the ECD spectra from electronic excited states.

Minimal Auxiliary Basis Set Approach for the Electronic Excitation Spectra of Organic Molecules

We report a minimal auxiliary basis model for time-dependent density functional theory (TDDFT) with hybrid density functionals that can accurately reproduce excitation energies and absorption spectra from TDDFT while reducing cost by about 2 orders of magnitude. Our method, dubbed TDDFT-ris, employs the resolution-of-the-identity technique with just one s-type auxiliary basis function per atom for the linear response operator, where the Gaussian exponents are parametrized across the periodic table using tabulated atomic radii with a single global scaling factor. By tuning on a small test set, we determine a single functional-independent scale factor that balances errors in excitation energies and absorption spectra. Benchmarked on organic molecules and compared to standard TDDFT, TDDFT-ris has an average energy error of only 0.06 eV and yields absorption spectra in close agreement with TDDFT. Thus, TDDFT-ris enables simulation of realistic absorption spectra in large molecules that would be inaccessible from standard TDDFT.

SQMBox: Interfacing a semiempirical integral library to modular ab initio electronic structure enables new semiempirical methods

Ab initio and semiempirical electronic structure methods are usually implemented in separate software packages or use entirely different code paths. As a result, it can be time-consuming to transfer an established ab initio electronic structure scheme to a semiempirical Hamiltonian. We present an approach to unify ab initio and semiempirical electronic structure code paths based on a separation of the wavefunction ansatz and the needed matrix representations of operators. With this separation, the Hamiltonian can refer to either an ab initio or semiempirical treatment of the resulting integrals. We built a semiempirical integral library and interfaced it to the GPU-accelerated electronic structure code TeraChem. Equivalency between ab initio and semiempirical tight-binding Hamiltonian terms is assigned according to their dependence on the one-electron density matrix. The new library provides semiempirical equivalents of the Hamiltonian matrix and gradient intermediates, corresponding to those provided by the ab initio integral library. This enables the straightforward combination of semiempirical Hamiltonians with the full pre-existing ground and excited state functionality of the ab initio electronic structure code. We demonstrate the capability of this approach by combining the extended tight-binding method GFN1-xTB with both spin-restricted ensemble-referenced Kohn-Sham and complete active space methods. We also present a highly efficient GPU implementation of the semiempirical Mulliken-approximated Fock exchange. The additional computational cost for this term becomes negligible even on consumer-grade GPUs, enabling Mulliken-approximated exchange in tight-binding methods for essentially no additional cost.

Long-range corrected fragment molecular orbital density functional tight-binding method for excited states in large molecular systems

Herein, we present a new method to efficiently calculate electronically excited states in large molecular assemblies, consisting of hundreds of molecules. For this purpose, we combine the long-range corrected tight-binding density functional fragment molecular orbital method (FMO-LC-DFTB) with an excitonic Hamiltonian, which is constructed in the basis of locally excited and charge-transfer configuration state functions calculated for embedded monomers and dimers and accounts explicitly for the electronic coupling between all types of excitons. We first evaluate both the accuracy and efficiency of our fragmentation approach for molecular dimers and aggregates by comparing it with the full LC-TD-DFTB method. The comparison of the calculated spectra of an anthracene cluster shows a very good agreement between our method and the LC-TD-DFTB reference. The effective computational scaling of our method has been explored for anthracene clusters and for perylene bisimide aggregates. We demonstrate the applicability of our method by the calculation of the excited state properties of pentacene crystal models consisting of up to 319 molecules. Furthermore, the participation ratio of the monomer fragments to the excited states is analyzed by the calculation of natural transition orbital participation numbers, which are verified by the hole and particle density for a chosen pentacene cluster. The use of our FMO-LC-TDDFTB method will allow for future studies of excitonic dynamics and charge transport to be performed on complex molecular systems consisting of thousands of atoms.

An efficient protocol for excited states of large biochromophores

Efficient energy transport in photosynthetic antenna is a long-standing source of inspiration for artificial light harvesting materials. However, characterizing the excited states of the constituent chromophores poses a considerable challenge to mainstream quantum chemical and semiempirical excited state methods due to their size and complexity and the accuracy required to describe small but functionally important changes in their properties. In this paper, we explore an alternative approach to calculating the excited states of large biochromophores, exemplified by a specific method for calculating the Q_y transition of bacteriochlorophyll a, which we name Chl-xTB. Using a diagonally dominant approximation to the Casida equation and a bespoke parameterization scheme, Chl-xTB can match time-dependent density functional theory's accuracy and semiempirical speed for calculating the potential energy surfaces and absorption spectra of chlorophylls. We demonstrate that Chl-xTB (and other prospective realizations of our protocol) can be integrated into multiscale models, including concurrent excitonic and point-charge embedding frameworks, enabling the analysis of biochromophore networks in a native environment. We exploit this capability to probe the low-frequency spectral densities of excitonic energies and interchromophore interactions in the light harvesting antenna protein LH2 (light harvesting complex 2). The impact of low-frequency protein motion on interchromophore coupling and exciton transport has routinely been ignored due to the prohibitive costs of including it in simulations. Our results provide a more rigorous basis for continued use of this approximation by demonstrating that exciton transition energies are unaffected by low-frequency vibrational coupling to exciton interaction energies.

Ultrafast Evaluation of Two-Photon Absorption with Simplified Time-Dependent Density Functional Theory

This work presents the theoretical background to evaluate two-photon absorption (2PA) cross-sections in the framework of simplified time-dependent density functional theory (sTD-DFT). Our new implementation allows the ultrafast evaluation of 2PA cross-sections for large molecules based on a regular DFT ground-state determinant as well as a variant employing our tight-binding sTD-DFT-xTX flavor for very large systems. The method is benchmarked against higher-level calculations for trans-stilbene and typical fluorescent protein chromophores. For eGFP, a quadrupolar chromophore and its branched version, the flavine mono-nucleotide, and the iLOV protein, we compare sTD-DFT 2PA spectra to experimental ones. This includes extension and testing of our all-atom quantum chemistry methodology for the evaluation of 2PA for a system of ∼2000 atoms, providing striking agreement with the experimental spectrum.

Evaluating fast methods for static polarizabilities on extended conjugated oligomers

Given the importance of accurate polarizability calculations to many chemical applications, coupled with the need for efficiency when calculating the properties of sets of molecules or large oligomers, we present a benchmark study examining possible calculation methods for polarizable materials. We first investigate the accuracy of the additive model used in GFN2, a highly-efficient semi-empirical tight-binding method, and the D4 dispersion model, comparing its predicted additive polarizabilities to ωB97XD results for a subset of PubChemQC and a compiled benchmark set of molecules spanning polarizabilities from approximately 3 ų to 600 ų, with some compounds in the range of approximately 1200-1400 ų. Although we find additive GFN2 polarizabilities, and thus D4, to have large errors with polarizability calculations on large conjugated oligomers, it would appear an empirical quadratic correction can largely remedy this. We also compare the accuracy of DFT polarizability calculations run using basis sets of varying size and level of augmentation, determining that a non-augmented basis set may be used for large, highly polarizable species in conjunction with a linear correction factor to achieve accuracy extremely close to that of aug-cc-pVTZ.

Excited-State Properties for Extended Systems: Efficient Hybrid Density Functional Methods

Time-dependent density functional theory has become state-of-the-art for describing photophysical and photochemical processes in extended materials because of its affordable cost. The inclusion of exact exchange was shown to be essential for the correct description of the long-range asymptotics of electronic interactions and thus a well-balanced description of valence, Rydberg, and charge-transfer excitations. Several approaches for an efficient treatment of exact exchange have been established for the ground state, while implementations for excited-state properties are rare. Furthermore, the high computational costs required for excited-state properties in comparison to ground-state computations often hinder large-scale applications on periodic systems with hybrid functional accuracy. We therefore propose two approximate schemes for improving computational efficiency for the treatment of exact exchange. Within the auxiliary density matrix method (ADMM), exact exchange is estimated using a relatively small auxiliary basis and the introduced basis set incompleteness error is compensated by an exchange density functional correction term. Benchmark results for a test set of 35 molecules demonstrate that the mean absolute error introduced by ADMM is smaller than 0.3 pm for excited-state bond lengths and in the range of 0.02-0.04 eV for vertical excitation, adiabatic excitation, and fluorescence energies. Computational timings for a series of covalent-organic frameworks demonstrate that a speed-up of at least 1 order of magnitude can be achieved for excited-state geometry optimizations in comparison to conventional hybrid functionals. The second method is to use a semiempirical tight binding approximation for both Coulomb and exchange contributions to the excited-state kernel. This simplified Tamm-Dancoff approximation (sTDA) achieves an accuracy comparable to approximated hybrid density functional theory when referring to highly accurate coupled-cluster reference data. We find that excited-state bond lengths deviate by 1.1 pm on average and mean absolute errors in vertical excitation, adiabatic excitation, and fluorescence energies are in the range of 0.2-0.5 eV. In comparison to ADMM-approximated hybrid functional theory, sTDA accelerates the computation of broad-band excitation spectra by 1 order of magnitude, suggesting its potential use for large-scale screening purposes.

Simplified GW/BSE Approach for Charged and Neutral Excitation Energies of Large Molecules and Nanomaterials

Inspired by Grimme's simplified Tamm-Dancoff density functional theory approach [Grimme, S. J. Chem. Phys. 2013, 138, 244104], we describe a simplified approach to excited-state calculations within the GW approximation to the self-energy and the Bethe-Salpeter equation (BSE), which we call sGW/sBSE. The primary simplification to the electron repulsion integrals yields the same structure as with tensor hypercontraction, such that our method has a storage requirement that grows quadratically with system size and computational timing that grows cubically with system size. The performance of sGW is tested on the ionization potential of the molecules in the GW100 test set, for which it differs from ab initio GW calculations by only 0.2 eV. The performance of sBSE (based on the sGW input) is tested on the excitation energies of molecules in Thiel's set, for which it differs from ab initio GW/BSE calculations by about 0.5 eV. As examples of the systems that can be routinely studied with sGW/sBSE, we calculate the band gap and excitation energy of hydrogen-passivated silicon nanocrystals with up to 2650 electrons in 4678 spatial orbitals and the absorption spectra of two large organic dye molecules with hundreds of atoms.

Directional Doping and Cocrystallizing an Open-Shell Ag39 Superatom via Precursor Engineering

Metal precursors employed in the bottom-up synthesis of metal nanoclusters (NCs) are of great importance in directing their composition and geometrical structure. In this work, a silver nanocluster co-protected by phosphine and thiolate, namely, [Ag₃₉(PFBT)₂₄(TPP)₈]^2- (Ag₃₉, PFBT = pentafluorobenzenethiol, TPP = triphenylphosphine), was isolated and structurally characterized. It adopts a three-layered Ag₁₃@Ag₁₈@Ag₈S₂₄P₈ core-shell structure. The Ag₁₃@Ag₁₈ kernel is unusual in multilayer noble metal NCs. By introducing a copper precursor in the synthesis, a bimetallic nanocluster [Ag₃₇Cu₂(PFBT)₂₄(TPP)₈]^2- (Ag₃₇Cu₂) with an identical structure to Ag₃₉ apart from two outer Ag atoms being substituted by Cu atoms was obtained. Astoundingly, the Cu precursor used in the synthesis was found to be critical in determining the final structure. The alteration of the Cu precursor led to the cocrystallization of the above alloy nanocluster with a Ag₁₄ nanocluster, namely, [Ag₃₇Cu₂(PFBT)₂₄(TPP)₈]^2-·[Ag₁₄(PFBT)₆(TPP)₈] (Ag₃₇Cu₂·Ag₁₄). The electronic structure analyzed by theoretical calculation reveals that Ag₃₉ is a 17-electron open-shell superatom. The optical absorption of Ag₃₉, Ag₃₇Cu₂, and Ag₃₇Cu₂·Ag₁₄ was compared and studied in detail. This work not only enriches the family of alloy metallic nanoclusters but also provides a metal NC-based cocrystal platform for in-depth study of its crystal growth and photophysical property.

Machine learned calibrations to high-throughput molecular excited state calculations

Understanding the excited state properties of molecules provides insight into how they interact with light. These interactions can be exploited to design compounds for photochemical applications, including enhanced spectral conversion of light to increase the efficiency of photovoltaic cells. While chemical discovery is time- and resource-intensive experimentally, computational chemistry can be used to screen large-scale databases for molecules of interest in a procedure known as high-throughput virtual screening. The first step usually involves a high-speed but low-accuracy method to screen large numbers of molecules (potentially millions), so only the best candidates are evaluated with expensive methods. However, use of a coarse first-pass screening method can potentially result in high false positive or false negative rates. Therefore, this study uses machine learning to calibrate a high-throughput technique [eXtended Tight Binding based simplified Tamm-Dancoff approximation (xTB-sTDA)] against a higher accuracy one (time-dependent density functional theory). Testing the calibration model shows an approximately sixfold decrease in the error in-domain and an approximately threefold decrease in the out-of-domain. The resulting mean absolute error of ∼0.14 eV is in line with previous work in machine learning calibrations and out-performs previous work in linear calibration of xTB-sTDA. We then apply the calibration model to screen a 250k molecule database and map inaccuracies of xTB-sTDA in chemical space. We also show generalizability of the workflow by calibrating against a higher-level technique (CC2), yielding a similarly low error. Overall, this work demonstrates that machine learning can be used to develop a cost-effective and accurate method for large-scale excited state screening, enabling accelerated molecular discovery across a variety of disciplines.

Small symmetry-breaking triggering large chiroptical responses of Ag70 nanoclusters

The origins of the chiroptical activities of inorganic nanostructures have perplexed scientists, and deracemization of high-nuclearity metal nanoclusters (NCs) remains challenging. Here, we report a single-crystal structure of Rac-Ag₇₀ that contains enantiomeric pairs of 70-nuclearity silver clusters with 20 free valence electrons (Ag₇₀), and each of these clusters is a doubly truncated tetrahedron with pseudo-T symmetry. A deracemization method using a chiral metal precursor not only stabilizes Ag₇₀ in solution but also enables monitoring of the gradual enlargement of the electronic circular dichroism (CD) responses and anisotropy factor g_abs. The chiral crystals of R/S-Ag₇₀ in space group P2₁ containing a pseudo-T-symmetric enantiomeric NC show significant kernel-based and shell-based CD responses. The small symmetry breaking of T_d symmetry arising from local distortion of Ag−S motifs and rotation of the apical Ag₃ trigons results in large chiroptical responses. This work opens an avenue to construct chiral medium/large-sized NCs and nanoparticles, which are promising for asymmetric catalysis, nonlinear optics, chiral sensing, and biomedicine.

Having control over the chirality of metal nanoclusters is challenging. Here, the authors report the deracemization of silver nanoclusters and monitor the chiroptical responses.

CalcUS: An Open-Source Quantum Chemistry Web Platform

Computational chemistry is an increasingly active field due to the improvement of computing resources and theoretical tools. However, its use remains usually limited to technically inclined users due to the technical challenges of preparing, launching, and analyzing calculations. In this context, we have developed CalcUS, an open-source platform to streamline quantum chemistry studies. Its objective is to democratize access to computational chemistry by providing a user-friendly web interface to simplify running and analyzing quantum mechanical calculations. It is freely available, expandable, and customizable. It promotes connectivity to multiple software packages and algorithms, thus providing state-of-the-art techniques to all practitioners. We propose CalcUS as a standalone tool and infrastructure to support other open-source packages.

Interrogation of solution conformation of complex macrocyclic peptides utilizing a combined SEC-HDX-MS, circular dichroism, and NMR workflow

Recent technological and synthetic advances have led to a resurgence in the exploration of peptides as potential therapeutics. Understanding peptide conformation in both free and protein-bound states remains one of the most critical areas for successful development of peptide drugs. In this study it was demonstrated that the combination of Size-Exclusion Chromatography with Hydrogen-Deuterium Exchange Mass Spectrometry (SEC-HDX-MS) and Circular Dichroism Spectroscopy (CD) can be used to guide the selection of peptides for further NMR analysis. Moreover, the insights from this workflow guide the choice of the best biologically relevant conditions for NMR conformational studies of peptide ligands in a free state in solution. Combined information about solution conformation character and stability across temperatures and co-solvent compositions greatly expedites selection of optimal conditions for NMR analysis. In total, the combination of SEC-HDX-MS, CD, and NMR into a single complementary workflow greatly accelerates conformational analysis of peptides in the drug discovery lead optimization process.

Computational and data driven molecular material design assisted by low scaling quantum mechanics calculations and machine learning

Electronic structure methods based on quantum mechanics (QM) are widely employed in the computational predictions of the molecular properties and optoelectronic properties of molecular materials. The computational costs of these QM methods, ranging from density functional theory (DFT) or time-dependent DFT (TDDFT) to wave-function theory (WFT), usually increase sharply with the system size, causing the curse of dimensionality and hindering the QM calculations for large sized systems such as long polymer oligomers and complex molecular aggregates. In such cases, in recent years low scaling QM methods and machine learning (ML) techniques have been adopted to reduce the computational costs and thus assist computational and data driven molecular material design. In this review, we illustrated low scaling ground-state and excited-state QM approaches and their applications to long oligomers, self-assembled supramolecular complexes, stimuli-responsive materials, mechanically interlocked molecules, and excited state processes in molecular aggregates. Variable electrostatic parameters were also introduced in the modified force fields with the polarization model. On the basis of QM computational or experimental datasets, several ML algorithms, including explainable models, deep learning, and on-line learning methods, have been employed to predict the molecular energies, forces, electronic structure properties, and optical or electrical properties of materials. It can be conceived that low scaling algorithms with periodic boundary conditions are expected to be further applicable to functional materials, perhaps in combination with machine learning to fast predict the lattice energy, crystal structures, and spectroscopic properties of periodic functional materials.

Virtual screening of norbornadiene-based molecular solar thermal energy storage systems using a genetic algorithm

We present a computational methodology for the screening of a chemical space of 10²⁵ substituted norbornadiene molecules for promising kinetically stable molecular solar thermal (MOST) energy storage systems with high energy densities that absorb in the visible part of the solar spectrum. We use semiempirical tight-binding methods to construct a dataset of nearly 34 000 molecules and train graph convolutional networks to predict energy densities, kinetic stability, and absorption spectra and then use the models together with a genetic algorithm to search the chemical space for promising MOST energy storage systems. We identify 15 kinetically stable molecules, five of which have energy densities greater than 0.45 MJ/kg, and the main conclusion of this study is that the largest energy density that can be obtained for a single norbornadiene moiety with the substituents considered here, while maintaining a long half-life and absorption in the visible spectrum, is around 0.55 MJ/kg.

Insights into Ergochromes of the Plant Pathogen Claviceps purpurea

Claviceps purpurea is an ergot fungus known for its neurotropic alkaloids, which have been identified as the main cause of ergotism, a livestock and human disease triggered by ergot consumption. Tetrahydroxanthone dimers, the so-called ergopigments, presumably also contribute to this toxic effect. Overexpression of the cluster-specific transcription factor responsible for the formation of these pigments in C. purpurea led to the isolation of three new metabolites (8-10). The new pigments were characterized utilizing HRMS, NMR techniques, and CD spectroscopy and shown to be xanthone dimers. Secalonic acid A and its 2,4'- and 4,4'-linked isomers were also isolated, and their absolute configuration was investigated. The contribution of secalonic acid A, its isomers, and new metabolites to the toxicity of C. purpurea was investigated in HepG2 and CCF-STTG1 cells. Along with cytotoxic properties, secalonic acid A was found to inhibit topoisomerase I and II activity.

MOLGENGO: Finding Novel Molecules with Desired Electronic Properties by Capitalizing on Their Global Optimization

The discovery of novel and favorable fluorophores is critical for understanding many chemical and biological studies. High-resolution biological imaging necessitates fluorophores with diverse colors and high quantum yields. The maximum oscillator strength and its corresponding absorption wavelength of a molecule are closely related to the quantum yields and the emission spectrum of fluorophores, respectively. Thus, the core step to design favorable fluorophore molecules is to optimize the desired electronic transition properties of molecules. Here, we present MOLGENGO, a new molecular property optimization algorithm, to discover novel and favorable fluorophores with machine learning and global optimization. This study reports novel molecules from MOLGENGO with high oscillator strength and absorption wavelength close to 200, 400, and 600 nm. The results of MOLGENGO simulations have the potential to be candidates for new fluorophore frameworks.

Carboxylation of a Palladacycle Formed via C(sp3 )-H Activation: Theory-Driven Reaction Design

Theory-driven organic synthesis is a powerful tool for developing new organic transformations. A palladacycle(II), generated from 8-methylquinoline via C(sp³ )-H activation, is frequently featured in the scientific literature, albeit that the reactivity toward CO₂ , an abundant, inexpensive, and non-toxic chemical, remains elusive. We have theoretically discovered potential carboxylation pathways using the artificial force induced reaction (AFIR) method, a density-functional-theory (DFT)-based automated reaction path search method. The thus obtained results suggest that the reduction of Pd(II) to Pd(I) is key to promote the insertion of CO₂ . Based on these computational findings, we employed various one-electron reductants, such as Cp*₂ Co, a photoredox catalyst under blue LED irradiation, and reductive electrolysis ((+)Mg/(-)Pt), which afforded the desired carboxylated products in high yields. After screening phosphine ligands under photoredox conditions, we discovered that bidentate ligands such as dppe promoted this carboxylation efficiently, which was rationally interpreted in terms of the redox potential of the Pd(II)-dppe complex as well as on the grounds of DFT calculations. We are convinced that these results could serve as future guidelines for the development of Pd(II)-catalyzed C(sp³ )-H carboxylation reactions with CO₂ .

All-Atom Quantum Mechanical Calculation of the Second-Harmonic Generation of Fluorescent Proteins

Fluorescent proteins (FPs) are biotags of choice for second-harmonic imaging microscopy (SHIM). Because of their large size, computing their second-harmonic generation (SHG) response represents a great challenge for quantum chemistry. In this contribution, we propose a new all-atom quantum mechanics methodology to compute SHG of large systems. This is now possible because of two recent implementations: the tight-binding GFN2-xTB method to optimize geometries and a related version of the simplified time-dependent density functional theory (sTD-DFT-xTB) to evaluate quadratic response functions. In addition, a new dual-threshold configuration selection scheme is introduced to reduce the computational costs while retaining overall similar accuracy. This methodology was tested to evaluate the SHG of the proteins iLOV and bacteriorhodopsin (bR). In the case of bR, quantitative agreement with respect to experiment was reached for the out-of-resonance low-energy part of the β_HRS frequency dispersion. This work paves the way toward an accurate prediction of the SHG of large structures-a requirement for the design of new and improved SHIM biotags.

Hydrogen Bonds and n → π* Interactions in the Acetylation of Propranolol Catalyzed by Candida antarctica Lipase B: A QTAIM Study

Enzyme-substrate interactions play a crucial role in enzymatic catalysis. Quantum theory of atoms in molecules (QTAIM) calculations are extremely useful in computational studies of these interactions because they provide very detailed information about the strengths and types of molecular interactions. QTAIM also provides information about the intramolecular changes that occur in the catalytic reaction. Here, we analyze the enzyme-substrate interactions and the topological properties of the electron density in the enantioselective step of the acylation of (R,S)-propranolol, an aminoalcohol with therapeutic applications, catalyzed by Candida antarctica lipase B. Eight reaction paths (four for each enantiomer) are investigated and the energies, atomic charges, hydrogen bonds, and n → π* interactions of propranolol, the catalytic triad (composed of D187, H224, and S105), and the oxyanion hole are analyzed. It is found that D187 acts as an electron density reservoir for H224, and H224 acts as an electron density reservoir for the active site of the protein. It releases electron density when the tetrahedral intermediate is formed from the Michaelis complex and receives it when the enzyme-product complex is formed. Hydrogen bonds can be grouped into noncovalent and covalent hydrogen bonds. The latter are stronger and more important for the reaction than the former. We also found weak n → π* interactions, which are characterized by QTAIM and the natural bond orbital (NBO) analysis.

Brevianthrones, bianthrones from a Chinese isolate of the endophytic fungus Colletotrichum brevisporum

Seven undescribed bianthrones, the brevianthrones, together with two known anthraquinones, were isolated from the plant-derived fungus Colletotrichum brevisporum, obtained from the plant Piper sarmentosum Roxb., collected in Guangxi, China. This is the first report of the isolation of bianthrones from the Colletotrichum genus. The structures of the compounds were elucidated by a combination of NMR and MS spectroscopic analysis, while the absolute configurations were determined by X-ray crystallography and by simulation of ECD spectra.

New insight into the mechanism of carbon dioxide activation on copper-based catalysts: A theoretical study

A combination of Artificial Bee Colony algorithm, eXtended Tight Binding and Density functional theory methods were performed to study the activation process of carbon dioxide (CO₂) over copper (Cu₄ cluster) based catalytic systems. The findings revealed that the activation of the C-O bond resulted from the electron transfer to σ*, π* - MO of CO₂. The more the electrons are transferred to CO₂, the more the C-O bond is activated and elongated. The suitability of several metal oxide supports (Fe₂O₃, Al₂O₃, MgO, ZnO) is estimated using calculated electronic parameters (global electrophilicity index, vertical ionization potential and vertical electron affinity). Aside from demonstrating the appropriateness of Al₂O₃ and ZnO, a thorough examination of MgO revealed that, due to the formation of stable carbonate products, this oxide is not really appropriate as a support for copper-based catalysts in CO₂ conversion. Our studies have also shown that the electron enrichment of copper atoms plays a key role in the activation of C-O bonds. Alkali metal doping (Li, K, Cs) significantly improves the catalytic efficiency of the Cu₄ cluster. Based on the results of electron transfer to the CO₂ molecule, the effect of doping alkali metal atoms may be organized in the following order: Cs > K > Li. A new core/shell catalytic system with potassium atoms in the core and copper atoms in the shell has been proposed and has proven to be a promising, efficient catalytic system in the CO₂ adsorption and activation.

Stabilization mechanism of arsenic-sulfide slag by density functional theory calculation of arsenic-sulfide clusters

Stabilization of arsenic sulfur slag (As‒S slag) is of high importance to prevent the release of deadly As pollutants into environment. However, the molecular understanding on the stability of As‒S slag is missing, which in turn restricts the development of robust approach to solve the challenge. In this work, we investigated the structure-stability relationship of As‒S slag with adopting various As‒S clusters as prototypes by density functional theory (DFT). Results showed that the configuration of S multimers-covering-(As₂S₃)_n is the most stable structure amongst the candidates by the analysis of energies and bonding characteristics. The high stability is explained by orbital composition that the 4p-orbital (As) binding with 3p-orbital (S) decreases energy level of highest occupied molecular orbital (HOMO). Inspired from the calculations, an excess-S-based hydrothermal method was successfully proposed and achieved to promote the stabilization of As‒S slag. Typically, the As concentration from the leaching test of stabilized As‒S slag is only 0.8 mg/L, which is much lower than the value from other stabilized slag.

Perspective on Simplified Quantum Chemistry Methods for Excited States and Response Properties

We review recent developments in the framework of simplified quantum chemistry for excited state and optical response properties (sTD-DFT) and present future challenges for new method developments to improve accuracy and extend the range of application. In recent years, the scope of sTD-DFT was extended to molecular response calculations of the polarizability, optical rotation, first hyperpolarizability, two-photon absorption (2PA), and excited-state absorption for large systems with hundreds to thousands of atoms. The recently introduced spin-flip simplified time-dependent density functional theory (SF-sTD-DFT) variant enables an ultrafast treatment for diradicals and related strongly correlated systems. A few drawbacks were also identified, specifically for the computation of 2PA cross sections. We propose solutions to this problem and how to generally improve the accuracy of simplified schemes. New possible simplified schemes are also introduced for strongly correlated systems, e.g., with a second-order perturbative correlation correction. Interpretation tools that can extract chemical structure-property relationships from excited state or response calculations are also discussed. In particular, the recently introduced method-agnostic RespA approach based on natural response orbitals (NROs) as the key concept is employed.

Graphitic carbon nitrides as platforms for single-atom photocatalysis

Herein we demonstrate that adding single atoms of selected transition metals to graphitic carbon nitrides allows the tailoring of the electronic and chemical properties of these 2D nanomaterials, directly impacting their usage in photocatalysis. These single-atom photocatalysts were successfully prepared with Ni²⁺, Pt²⁺ or Ru³⁺ by cation exchange, using poly(heptazine imides) (PHI) as the 2D layered platform. Differences in photocatalytic performance for these metals were assessed using rhodamine-B (RhB) and methyl orange (MO) as model compounds for degradation. We have demonstrated that single atoms may either improve or impair the degradation of RhB and MO, depending on the proper matching of the net charge of these molecules and the surface potential of the catalyst, which in turn is responsive to the metal incorporated into the PHI nanostructures. Computer simulations demonstrated that even one transition metal cation caused dramatic changes in the electronic structure of PHI, especially regarding light absorption, which was extended all along the visible up to the near IR region. Besides introducing new quantum states, the metal atoms strongly polarized the molecular orbitals across the PHI and electrostatic fields arising from the electronic transitions became at least tenfold stronger. This simple proof of concept demonstrates that these new materials hold promise as tools for many important photocatalytic reactions that are strongly dependent on our ability to control surface charge and its polarization under illumination, such as H₂ evolution, CO₂ reduction and photooxidation in general.

Fine control of the molecular weight and polymer dispersity via a latent monomeric retarder

A latent monomeric retarder was used for a one-shot polymerization with a defined MW and Đ.

Reversible Soft Mechanochemical Control of Biaryl Conformations through Crosslinking in a 3D Macromolecular Network

Tuning the dihedral angle (DA) of axially chiral compounds can impact biological activity, catalyst efficiency, molecular motor performance, or chiroptical properties. Herein, we report gradual, controlled, and reversible changes in molecular conformation of a covalently linked binaphthyl moiety within a 3D polymeric network by application of a macroscopic stretching force. We managed direct observation of DA changes by measuring the circular dichroism signal of an optically pure BINOL-crosslinked elastomer network. Stretching the elastomer resulted in a widening of the DA between naphthyl rings when the BINOL was doubly grafted to the elastomer network; no effect was observed when a single naphthyl ring of the BINOL was grafted to the elastomer network. We have determined that ca. 170 % extension of the elastomers led to the transfer of a mechanical force to the BINOL moiety of 2.5 kcal mol^-1  Å^-1 (ca. 175 pN) in magnitude and results in the opening of the DA of BINOL up to 130°.

Ultra-Fast Computation of Excited-States Spectra for Large Systems: Ultraviolet and Fluorescence Spectra of Proteins

A workable approach named xTB-sTDDFT was selected to investigate the excited-state spectra of oxytocin (135 atoms), GHRP-6 (120 atoms) and insulin (793 atoms). Three different Hartree-Fock components functionals (wB97XD3: 51%, LC-BLYP: 53%, wB97X: 57%) were used to calculate the excitation spectra, and the results calculated by wB97XD3 functional well agree with the experiments. It's a deep impression that computed time cost reduced by more than 80%. For polypeptide (oxytocin and GHRP-6), both UV and fluorescence spectra were obtained, and the errors between the calculated and experimental values approximately were 20 nm. For Insulin, the errors are within 15 nm. UV spectrum peak is λ_cal = 262 nm (λ_exp = 277 nm, Δλ = 15 nm), and fluorescence spectrum peak is λ_cal = 294 nm (λ_exp = 304 nm, Δλ = 10 nm). In summary, a suitable theoretical model is established to ultra-fast calculate the electronic excitation spectra of large systems, such as proteins and biomacromolecules, with good calculation accuracy, fast calculation speed and low cost.

Theoretical Research on Excited States: Ultraviolet and Fluorescence Spectra of Aromatic Amino Acids

Using Gaussian and Orca, UV and fluorescence spectra of three amino acids (Tyr: Tyrosine, Trp: Tryptophan, Phe: Phenylalanine) were calculated by different functionals (B3LYP, BP86, wB97X). The spectra calculated by BP86 are consistent with the experiments. UV spectra peak of Tyr is 255 nm (Exp. 275 nm, Δλ = 20 nm), Trp is 279 nm (Exp. 277 nm, Δλ = 2 nm), and Phe is 275 nm (Exp. 257 nm, Δλ = 18 nm). Fluorescence spectra peak of Trp is 341 nm (Exp. 350 nm, Δλ = 9 nm), Tyr is 295 nm (Exp. 306 nm, Δλ = 11 nm), and Phe is 285 nm (Exp. 302 nm, Δλ = 17 nm). Moreover, a theoretical model for calculating the excited states of biomolecules is established. Compared with Gaussian's results, Orca is more quickly and effectively for calculating excited state spectra with the same accuracy.

Chiroptical Properties in Thin Films of π-Conjugated Systems

Chiral π-conjugated molecules provide new materials with outstanding features for current and perspective applications, especially in the field of optoelectronic devices. In thin films, processes such as charge conduction, light absorption, and emission are governed not only by the structure of the individual molecules but also by their supramolecular structures and intermolecular interactions to a large extent. Electronic circular dichroism, ECD, and its emission counterpart, circularly polarized luminescence, CPL, provide tools for studying aggregated states and the key properties to be sought for designing innovative devices. In this review, we shall present a comprehensive coverage of chiroptical properties measured on thin films of organic π-conjugated molecules. In the first part, we shall discuss some general concepts of ECD, CPL, and other chiroptical spectroscopies, with a focus on their applications to thin film samples. In the following, we will overview the existing literature on chiral π-conjugated systems whose thin films have been characterized by ECD and/or CPL, as well other chiroptical spectroscopies. Special emphasis will be put on systems with large dissymmetry factors (g_abs and g_lum) and on the application of ECD and CPL to derive structural information on aggregated states.