Loriano Storchi, Laura Bellentani, Jeff Hammond, Sergio Orlandini, Leonardo Pacifici, Nicoló Antonini, Leonardo Belpassi
{"title":"Acceleration of the Relativistic Dirac-Kohn-Sham Method with GPU: A Pre-Exascale Implementation of BERTHA and PyBERTHA.","authors":"Loriano Storchi, Laura Bellentani, Jeff Hammond, Sergio Orlandini, Leonardo Pacifici, Nicoló Antonini, Leonardo Belpassi","doi":"10.1021/acs.jctc.4c01759","DOIUrl":"10.1021/acs.jctc.4c01759","url":null,"abstract":"<p><p>In this paper, we present the recent advances in the computation of the Dirac-Kohn-Sham (DKS) method of the BERTHA code. We show here that the simple underlined structure of the FORTRAN code also favors efficient porting of the code to GPUs, leading to a particularly efficient hybrid CPU/GPU implementation (OpenMP/OpenACC), where the most computationally intensive part for DKS matrix evaluation (three-center two-electron integrals evaluated via the McMurchie-Davidson scheme) is efficiently offloaded to the GPU via compiler directives based on the OpenACC programming model. This scheme in combination with the use of a linear algebra library optimized for GPUs (cuBLAS, cuSOLVER) significantly accelerates the DKS calculations. In addition, the low-level integral kernel developed here at FORTRAN level was used to port our real-time DKS (RT-TDDKS) implementation based on Python (PyBERTHART) for the utilization of the GPU. The results obtained on the new Tier-0 EuroHPC supercomputer (LEONARDO) of the CINECA Supercomputing Centre with a single NVIDIA A100 card are very satisfactory. We achieve a speedup up to 30 for Au<sub>16</sub> in a single-point DKS energy calculation and up to 10 for the Au<sub>8</sub> systems in an RT-TDDKS calculation, compared to our OpenMP (i.e., CPU only) parallel implementation (with 32 cores). The approach presented here is very general and, to our knowledge, represents the first port of a Python API to GPUs based on a FORTRAN kernel for the evaluation of two-electron integrals. The implementation is currently limited to the use of a single GPU accelerator, but future paths to an actual exascale implementation are discussed.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3460-3475"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Structure Search with the Strategic Escape Algorithm.","authors":"Jordan Burkhardt, Yinglu Jia, Wan-Lu Li","doi":"10.1021/acs.jctc.4c01746","DOIUrl":"10.1021/acs.jctc.4c01746","url":null,"abstract":"<p><p>This work introduces the Strategic Escape (SE) algorithm, an approach that systematically ensures effective exploration of the potential energy surface during global minimum searches for atomic clusters. The SE algorithm prioritizes the escape from local minima prior to geometry optimization, leveraging a combination of randomized direction vectors, distance-based uniqueness criteria, and covalent bonding heuristics. These principles enhance structural diversity and computational efficiency by reducing redundant geometry optimizations. Additionally, a symmetry-guided seed generation method based on an adaptive polygon is proposed to provide diverse and physically realistic initial configurations. Together, these methods achieve a 2.3-fold improvement in computational efficiency compared to conventional Basin-Hopping approaches. The effectiveness of the SE algorithm is demonstrated through its application to boron, metal clusters, and binary-composition clusters, achieving rapid convergence to global minimum structures with high reliability. These advancements establish the SE algorithm as a robust and scalable tool for exploring complex chemical systems.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3765-3773"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Simple Linear Regression Models for Prediction of Ionization Energies, Electron Affinities, and Fundamental Gaps of Atoms and Molecules.","authors":"Rebecca K Carlson","doi":"10.1021/acs.jctc.4c01591","DOIUrl":"10.1021/acs.jctc.4c01591","url":null,"abstract":"<p><p>Linear regression equations were developed for different density functionals using data from the CCCBDB, along with a test set of 89 ionization energies (IE) and 76 electron affinities (EA) so that experimental IE and EA can be predicted from orbital energies. Separate equations were determined for different classes of atoms and molecules. These relationships were also applied to all occupied orbitals to simulate the photoemission spectra of organic molecules with accuracy similar to that of other computational methods at a fraction of the cost. The error for large molecules (up to 200 atoms) can be below 0.2 eV with many functionals for the prediction of the IE and EA.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3382-3393"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143707746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chen Qu, Paul L Houston, Thomas Allison, Joel M Bowman
{"title":"Targeted Transferable Machine-Learned Potential for Linear Alkanes Trained on C<sub>14</sub>H<sub>30</sub> and Tested for C<sub>4</sub>H<sub>10</sub> to C<sub>30</sub>H<sub>62</sub>.","authors":"Chen Qu, Paul L Houston, Thomas Allison, Joel M Bowman","doi":"10.1021/acs.jctc.4c01793","DOIUrl":"10.1021/acs.jctc.4c01793","url":null,"abstract":"<p><p>Given the great importance of linear alkanes in fundamental and applied research, an accurate machine-learned potential (MLP) would be a major advance in computational modeling of these hydrocarbons. Recently, we reported a novel, many-body permutationally invariant model that was trained specifically for the 44-atom hydrocarbon C<sub>14</sub>H<sub>30</sub> on roughly 250,000 B3LYP energies (Qu, C.; Houston, P. L.; Allison, T.; Schneider, B. I.; Bowman, J. M. <i>J. Chem. Theory Comput.</i> <b>2024</b>, <i>20</i>, 9339-9353). Here, we demonstrate the accuracy of the transferability of this potential for linear alkanes ranging from butane C<sub>4</sub>H<sub>10</sub> up to C<sub>30</sub>H<sub>62</sub>. Unlike other approaches for transferability that aim for universal applicability, the present approach is targeted for linear alkanes. The mean absolute error (MAE) for energy ranges from 0.26 kcal/mol for butane and rises to 0.73 kcal/mol for C<sub>30</sub>H<sub>62</sub> over the energy range up to 80 kcal/mol for butane and 600 kcal/mol for C<sub>30</sub>H<sub>62</sub>. These values are unprecedented for transferable potentials and indicate the high performance of a targeted transferable potential. The conformational barriers are shown to be in excellent agreement with high-level ab initio calculations for pentane, the largest alkane for which such calculations have been reported. Vibrational power spectra of C<sub>30</sub>H<sub>62</sub> from molecular dynamics calculations are presented and briefly discussed. Finally, the evaluation time for the potential is shown to vary linearly with the number of atoms.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3552-3562"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143717639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rudraditya Sarkar, Carmelo Naim, Karan Ahmadzadeh, Robert Zaleśny, Denis Jacquemin, Josep M Luis
{"title":"Simulations of Two-Photon Absorption Spectra of Fluorescent Dyes: The Impact of Non-Condon Effects.","authors":"Rudraditya Sarkar, Carmelo Naim, Karan Ahmadzadeh, Robert Zaleśny, Denis Jacquemin, Josep M Luis","doi":"10.1021/acs.jctc.4c01545","DOIUrl":"10.1021/acs.jctc.4c01545","url":null,"abstract":"<p><p>Computer simulations play a pivotal role in interpreting experimental two-photon absorption (2PA) spectra. One of the key aspects of the simulation of these spectra is to take into account the vibrational fine structure of the bands in electronic spectra. This is typically done by employing Franck-Condon (FC) term and low-order terms in the Herzberg-Teller (HT) expansion. In this work, we present a systematic study of first-order HT effects on the vibronic structure of π → π* electronic bands in 2PA spectra of 13 common fluorophores. We begin by evaluating the performance of several density functional approximations (DFAs) against the second-order coupled cluster singles and doubles model (CC2) for reproducing two-photon transition moments and their first- and second-order derivatives with respect to normal modes of vibration on a set of six donor-acceptor molecules. Our findings reveal that most DFAs produce inaccurate values for these derivatives, with the exception of the LC-BLYP functionals with range-separation parameters of 0.33 and 0.47. Although these functionals underestimate the HT contribution to the 2PA total intensities of the π → π* electronic bands, they offer a reasonable qualitative reproduction of the HT vibrational fine structure of the reference spectra. We further explore HT effects on fluorescent chromophores, finding that HT contributions are secondary to FC effects, leading to small shifts of the wavelengths peaks, and minimal changes in the intensities. Additionally, the adiabatic Hessian, vertical Hessian, and vertical gradient vibronic models are assessed. The general agreement among these models confirms that the harmonic approximation is suitable for studying the selected fluorophores.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3587-3599"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143727088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Patrick Ettenhuber, Mads Bøttger Hansen, Pier Paolo Poier, Irfansha Shaik, Stig Elkjaer Rasmussen, Niels Kristian Madsen, Marco Majland, Frank Jensen, Lars Olsen, Nikolaj Thomas Zinner
{"title":"Calculating the Energy Profile of an Enzymatic Reaction on a Quantum Computer.","authors":"Patrick Ettenhuber, Mads Bøttger Hansen, Pier Paolo Poier, Irfansha Shaik, Stig Elkjaer Rasmussen, Niels Kristian Madsen, Marco Majland, Frank Jensen, Lars Olsen, Nikolaj Thomas Zinner","doi":"10.1021/acs.jctc.5c00022","DOIUrl":"10.1021/acs.jctc.5c00022","url":null,"abstract":"<p><p>Quantum computing (QC) provides a promising avenue for enabling quantum chemistry calculations, which are classically impossible due to computational complexity that increases exponentially with system size. As fully fault-tolerant algorithms and hardware, for which an exponential speedup is predicted, are currently out of reach, recent research efforts have been dedicated to developing and scaling algorithms for Noisy Intermediate-Scale Quantum (NISQ) devices to showcase the practical usefulness of such machines. To demonstrate the usefulness of NISQ devices in the field of chemistry, we apply our recently developed FAST-VQE algorithm and a state-of-the-art quantum gate reduction strategy based on propositional satisfiability together with standard optimization tools for the simulation of the rate-determining proton transfer step for CO<sub>2</sub> hydration catalyzed by carbonic anhydrase resulting in the first application of a quantum computing device for the simulation of an enzymatic reaction. To this end, we have combined classical force field simulations with quantum mechanical methods on classical and quantum computers in a hybrid calculation approach. The presented technique significantly enhances the accuracy and capabilities of QC-based molecular modeling and finally pushes it into compelling and realistic applications. The framework is general and can be applied beyond the case of computational enzymology.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3493-3503"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143750259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Dynamic Programming for Chain Propagator Computation of Branched Block Copolymers in Polymer Field Theory Simulations.","authors":"Daeseong Yong, Jaeup U Kim","doi":"10.1021/acs.jctc.5c00103","DOIUrl":"10.1021/acs.jctc.5c00103","url":null,"abstract":"<p><p>We present an algorithmic approach to optimize chain propagator computations in polymer field theory simulations, including self-consistent field theory (SCFT) calculations and field-theoretic simulations (FTSs). Propagator calculations for branched block copolymers often involve recursive structures and overlapping subproblems, resulting in redundant computations. By employing dynamic programming (DP) and encoding computational dependencies as strings, our method systematically eliminates these redundancies in mixtures of branched polymers. The algorithm achieves optimal time complexity for various polymeric systems, including star-shaped, comb, dendrimer polymers, and homopolymer mixtures, by reusing and aggregating propagators for symmetric and repetitive structures. This enhances computational efficiency and reduces memory usage, addressing a key limitation in developing versatile polymer field theory simulation software. Our approach streamlines the simulation of complex branched polymers without requiring manual software adjustments, facilitating more efficient workflows for polymer researchers. Furthermore, the method enables automated searches for inverse design by optimizing computations across diverse branched polymer architectures, contributing to the discovery and design of novel polymeric materials. The algorithm is implemented in open-source software, ensuring accessibility for further development and broader application in computational polymer science.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3676-3690"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143750260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Reconstruction of the On-Top Two-Electron Density from Natural Orbitals and Their Occupation Numbers.","authors":"Jerzy Cioslowski, Krzysztof Strasburger","doi":"10.1021/acs.jctc.5c00024","DOIUrl":"https://doi.org/10.1021/acs.jctc.5c00024","url":null,"abstract":"<p><p>Spatial derivatives of the natural orbitals (NOs) at their nodal surfaces are shown to encode information about the on-top two-electron density Φ<sub>2</sub>(<i>r⃗</i>) in an approximate manner. This encoding, which becomes exact at the limit of an infinite number of nodal surfaces, allows the reconstruction of Φ<sub>2</sub>(<i>r⃗</i>) up to a multiplicative constant that can be retrieved from an identity involving the NO in question and its occupation number. This reconstruction provides a new consistency check for electronic structure formalisms, such as the one-electron reduced density matrix theory, that employ NOs as primary quantities.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143810054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cheng-Han Li, Mehmet Cagri Kaymak, Maksim Kulichenko, Nicholas Lubbers, Benjamin T Nebgen, Sergei Tretiak, Joshua Finkelstein, Daniel P Tabor, Anders M N Niklasson
{"title":"Shadow Molecular Dynamics with a Machine Learned Flexible Charge Potential.","authors":"Cheng-Han Li, Mehmet Cagri Kaymak, Maksim Kulichenko, Nicholas Lubbers, Benjamin T Nebgen, Sergei Tretiak, Joshua Finkelstein, Daniel P Tabor, Anders M N Niklasson","doi":"10.1021/acs.jctc.5c00062","DOIUrl":"10.1021/acs.jctc.5c00062","url":null,"abstract":"<p><p>We present an extended Lagrangian shadow molecular dynamics scheme with an interatomic Born-Oppenheimer potential determined by the relaxed atomic charges of a second-order charge equilibration model. To parametrize the charge equilibration model, we use machine learning with neural networks to determine the environment-dependent electronegativities and chemical hardness parameters for each atom, in addition to the charge-independent energy and force terms. The approximate shadow molecular dynamics potential in combination with the extended Lagrangian formulation improves the numerical stability and reduces the number of Coulomb potential calculations required to evaluate accurate conservative forces. We demonstrate efficient and accurate simulations with excellent long-term stability of the molecular dynamics trajectories. The significance of choosing fixed or environment-dependent electronegativities and chemical hardness parameters is evaluated. Finally, we compute the infrared spectrum of molecules via the dipole autocorrelation function and compare to experiments to highlight the accuracy of the shadow molecular dynamics scheme with a machine learned flexible charge potential.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3658-3675"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Diabatic States of Charge Transfer with Constrained Charge Equilibration.","authors":"Sohang Kundu, Hong-Zhou Ye, Timothy C Berkelbach","doi":"10.1021/acs.jctc.4c01604","DOIUrl":"10.1021/acs.jctc.4c01604","url":null,"abstract":"<p><p>Charge transfer (CT) processes that are electronically nonadiabatic are ubiquitous in chemistry, biology, and materials science, but their theoretical description requires diabatic states or adiabatic excited states. For complex systems, these latter states are more difficult to calculate than the adiabatic ground state. Here, we propose a simple method to obtain diabatic states, including energies and charges, by constraining the atomic charges within the charge equilibration framework. For two-state systems, the exact diabatic coupling can be determined, from which the adiabatic excited-state energy can also be calculated. The method can be viewed as an affordable alternative to constrained density functional theory (CDFT), and so we call it constrained charge equilibration (CQEq). We test the CQEq method on the anthracene-tetracyanoethylene CT complex and the reductive decomposition of ethylene carbonate on a lithium metal surface. We find that CQEq predicts diabatic energies, charges, and adiabatic excitation energies in good agreement with CDFT, and we propose that CQEq is promising for combination with machine learning force fields to study nonadiabatic CT in the condensed phase.</p>","PeriodicalId":45,"journal":{"name":"Journal of Chemical Theory and Computation","volume":" ","pages":"3545-3551"},"PeriodicalIF":5.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143668484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}