Article
Chemistry, Physical
Lucas M. Everhart, Julio A. Derteano, Jefferson E. Bates
Summary: This study explores the connection between the adiabatic excitation energy of time-dependent density functional theory and the ground state correlation energy from the adiabatic connection fluctuation-dissipation theorem (ACFDT) in the limiting case of one excited state. The results show that there is a tension between predicting an accurate excitation energy and an accurate potential contribution to correlation, particularly in systems with strong correlation. The exact adiabatic (AE) approximation is capable of accurately predicting both quantities in weakly correlated systems, while the random phase approximation (RPA) tends to be unable to predict these properties accurately. However, the AE approximation greatly overestimates the excitation energy in strongly correlated systems.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Chemistry, Physical
Karno Schwinn, Felipe Zapata, Antoine Levitt, Eric Cances, Eleonora Luppi, Julien Toulouse
Summary: This article explores the merits of linear-response range-separated time-dependent density-functional theory (TDDFT) for calculating photoionization spectra. Two variants of range-separated TDDFT are considered and compared with standard methods. The article demonstrates the calculation of photoionization spectra using the Sternheimer approach and applies it to the photoionization spectrum of the Be atom. The results show significant improvement over traditional methods.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Chemistry, Physical
Daniel Gibney, Jan-Niklas Boyn, David A. Mazziotti
Summary: By using a semidefinite programming approach, improvements have been made in accurately describing strongly correlated and open shell systems in Kohn-Sham density functional theory, resulting in enhanced singlet-triplet gaps for local density approximation and generalized gradient approximation functionals. Additionally, flaws in modern meta and hybrid GGA functionals were revealed, showing no significant improvements even with accurate electron density provided.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2021)
Article
Chemistry, Physical
Jannis Erhard, Steffen Fauser, Egor Trushin, Andreas Goerling
Summary: The recently introduced sigma-functionals provide a new type of functionals for the Kohn-Sham correlation energy. They are based on the adiabatic-connection fluctuation-dissipation theorem and are computationally related to the direct random phase approximation (dRPA). However, a shortcoming of sigma-functionals is their inability to accurately describe processes involving a change in the electron number. This problem is tackled by introducing a scaling of the eigenvalues of the KS response function, resulting in scaled sigma-functionals that retain accuracy and computational efficiency.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Chemistry, Physical
Wenna Ai, Wei-Hai Fang, Neil Qiang Su
Summary: The short-range corrected reduced density matrix functional omega P22 is developed to utilize the advantages of functionals in KS-DFT and RDMFT without double-counting, outperforming other 1-RDM functionals in tests of thermochemistry, nonbonded interactions, and bond dissociation energy. Omega P22 shows less systematic error for systems involving fractional spins and can accurately predict the energies for different single and multiple bonds, filling a gap left by commonly used KS-DFT and RDMFT functionals.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2022)
Article
Chemistry, Physical
Yi Xie, Daniel G. A. Smith, C. David Sherrill
Summary: This study presents an implementation of a symmetry-adapted perturbation theory algorithm based on density functional theory, utilizing density-fitting treatment of hybrid exchange-correlation kernels for describing monomers with hybrid functionals. The algorithm shows improved numerical stability and computational efficiency, performing well for systems with up to 3000 basis functions.
JOURNAL OF CHEMICAL PHYSICS
(2022)
Article
Materials Science, Multidisciplinary
Charles J. C. Scott, George H. Booth
Summary: Extended Density Matrix Embedding Theory (EDMET) overcomes the limitations of traditional embedding methods by self-consistently treating local two-body physics. It accurately describes phase transitions and dynamics, and can provide good agreement with experimental results for ab initio systems.
Article
Chemistry, Physical
Edoardo Spadetto, Pier Herman Theodoor Philipsen, Arno Foerster, Lucas Visscher
Summary: Pair atomic density fitting (PADF) is a promising strategy to decrease the scaling of quantum chemical methods for calculating correlation energy, but it can introduce large errors. This study introduces an alternative methodology to overcome the problem associated with PADF, using regularization and projection techniques. The accuracy and efficiency of this approach are assessed numerically using different basis sets, and the results demonstrate its effectiveness and computational efficiency.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Chemistry, Physical
Rajender Prasad Tiwari
Summary: In this study, the many-body effects on the exciton binding energy, electronic structure, and optical absorption spectra of oxychalcogenide perovskite materials were investigated using the many-body perturbation theory. The results showed that increasing doping concentration can enhance the exciton binding energy and photoconversion efficiency, while electron-electron interaction can significantly modify the band topology. This study provides valuable insights into the many-body effects in oxychalcogenide perovskite materials and their potential applications as photoactive materials.
JOURNAL OF PHYSICAL CHEMISTRY C
(2023)
Article
Chemistry, Physical
Egor Trushin, Adrian Thierbach, Andreas Goerling
Summary: The introduced sigma-Functionals are based on the ACFD theorem and optimized for reaction and transition state energies, achieving accuracies close to 1 kcal/mol and approaching chemical accuracy. With mean absolute deviation of 1.25 kcal/mol for 10,966 reactions, the approach is more accurate than dRPA methods and comparable to high-level wave function methods. Non-covalent binding energies are also accurately predicted to within a few tenths of a kcal/mol. The method is highly efficient, requiring less computational time than a density-functional calculation with a hybrid functional and can be easily implemented in existing dRPA codes.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Chemistry, Physical
Yunfei Hong, Junkai Deng, Xiangdong Ding, Jun Sun, Jefferson Zhe Liu
Summary: In this study, the ferroelectric polarization in bismuthene nanoribbons was investigated using first-principles calculations, and a width size limiting effect arising from edge effects was discovered. The decrease in width led to the spontaneous transformation of the zigzag and armchair paired nanoribbons into high-symmetric nonpolarized nanoribbons. The phase transition mechanism involving depolarization field and edge stress provides insights for achieving phase transition and ultrahigh piezoelectricity in Bi nanoribbons through strain engineering, which could enable new applications for 2D ferroelectric devices.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2023)
Article
Materials Science, Multidisciplinary
Aaron D. Kaplan, Carl A. Kukkonen
Summary: Analytic mathematical models for the static spin and density local field factors of the uniform electron gas are developed and shown to closely fit recent quantum Monte Carlo data. These models have a wide range of applications and are recommended for use in practical time-dependent density functional theory calculations of simple metallic systems. A revised model of the spin susceptibility enhancement is also developed that fits the QMC data and does not show a ferromagnetic instability at low density.
Article
Materials Science, Multidisciplinary
Jiyang Yan, Lifeng Ma, Juan Wang
Summary: In this paper, a model is proposed to analyze zirconia toughened alumina (ZTA) reinforced metal matrix composites, which involves a coated inhomogeneous circular inclusion concentrically embedded within a finite matrix. The model is based on the equivalent eigenstrain principle and the superposition principle, and the general solution is derived. The influence of thermal strains on stress distribution and the toughening mechanism associated with zirconia transformation are investigated using the model, providing insights for stress estimation and structure design of ZTA reinforced metal composites.
MECHANICS OF MATERIALS
(2023)
Article
Chemistry, Physical
Daria Drwal, Pavel Beran, Micha Hapka, Marcin Modrzejewski, Adam Sokol, Libor Veis, Katarzyna Pernal
Summary: In this work, a new approach based on adiabatic connection is proposed to accurately describe the electronic structure, especially for systems with strong electron correlation. It is more efficient than existing ab initio multireference dynamic correlation methods.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2022)
Article
Chemistry, Physical
Christian Neiss, Steffen Fauser, Andreas Goerling
Summary: Recently, sigma-functionals have been introduced as new correlation functionals in Kohn-Sham (KS) methods. When used in a post-self-consistent field manner in a Gaussian basis set framework, sigma-functional methods are computationally efficient and highly accurate for main group chemistry. They can reach a chemical accuracy of 1 kcal/mol for reaction and transition state energies. Sigma-functional methods yield accurate geometries and vibrational frequencies for main group molecules superior to conventional KS methods and RPA methods.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
Tomas Bucko, Monika Gesvandtnerova, Dario Rocca
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2020)
Article
Chemistry, Physical
T. Ayadi, L. Debbichi, M. Badawi, M. Said, D. Rocca, S. Lebegue
Summary: This study investigated the electronic properties of the bidimensional ferroelectric heterostructure In2Se3/Bi2Se3 using ab initio calculations. The material was found to have varying bandgap types and band alignments depending on the direction of the polarization vector, with the potential for tuning these properties with an external electric field. This suggests promising applications in electronic and optoelectronic systems.
APPLIED SURFACE SCIENCE
(2021)
Article
Chemistry, Physical
Monika Gesvandtnerova, Dario Rocca, Tomas Bucko
Summary: In this study, a detailed ab initio investigation of the carbonylation reaction of methoxy groups in zeolite mordenite was conducted using full molecular dynamics simulations. The results indicate a preference for the reaction in the side pocket, which was further supported by calculations using various density functional theory approximations with or without dispersion corrections. This research also introduced a new approach combining thermodynamic perturbation theory with machine learning to reduce computational costs.
JOURNAL OF CATALYSIS
(2021)
Article
Physics, Multidisciplinary
Mauricio Chagas da Silva, Michael Lorke, Balint Aradi, Meisam Farzalipour Tabriz, Thomas Frauenheim, Angel Rubio, Dario Rocca, Peter Deak
Summary: Super cell models are commonly employed to calculate the electronic structure of local deviations from ideal periodicity. A correction scheme for artificially repeated charges is proposed and successfully tested for bulk and slab calculations, especially important in preventing spurious states in the vacuum.
PHYSICAL REVIEW LETTERS
(2021)
Article
Physics, Condensed Matter
M. Barhoumi, D. Rocca, M. Said, S. Lebegue
Summary: Elastic constants play a central role in regulating the thermo-mechanical and anisotropic response of materials. In this study, diamond and silicon's elastic constants were obtained using density functional theory and the random phase approximation, showing excellent agreement with experimental data. The mechanical properties of these materials were studied, and 3D and 2D plots were visualized for Young's modulus, Poisson's ratio, and others.
SOLID STATE COMMUNICATIONS
(2021)
Article
Chemistry, Multidisciplinary
Bastien Casier, Mauricio Chagas da Silva, Michael Badawi, Fabien Pascale, Tomas Bucko, Sebastien Lebegue, Dario Rocca
Summary: The combination of electronic structure and machine learning techniques is a powerful tool for predicting chemical and physical properties. A novel descriptor based on molecular graphs has been proposed in this work, showing improved accuracy in energy predictions through the hybridization of two kernel functions.
JOURNAL OF COMPUTATIONAL CHEMISTRY
(2021)
Article
Physics, Applied
Koussai Lazaar, Saber Gueddida, Ali Abboud, Moncef Said, Dario Rocca, Sebastien Lebegue
Summary: The properties of these two-dimensional quaternary compounds are suitable for water splitting, their heterostructures facilitate efficient electron-hole separation, and graphene heterostructures with these compounds exhibit a p-type nature.
JOURNAL OF APPLIED PHYSICS
(2021)
Article
Chemistry, Physical
Alekos Segalina, Sebastien Lebegue, Dario Rocca, Simone Piccinin, Mariachiara Pastore
Summary: Level alignment plays a crucial role in dye-sensitized photoelectrodes. Accurately predicting the interface structure through first-principles calculations is crucial for optimizing the device. By combining experimental and computational methods, this study successfully describes the structure and level alignment of the C343-sensitized NiO surface in water.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2021)
Article
Chemistry, Physical
Basile Herzog, Mauricio Chagas da Silva, Bastien Casier, Michael Badawi, Fabien Pascale, Tomas Bucko, Sebastien Lebegue, Dario Rocca
Summary: Machine learning thermodynamic perturbation theory (MLPT) is a promising approach for computing finite temperature properties, especially when comparing different levels of theory or using expensive computational methods. This study evaluates the accuracy of MLPT for calculating ensemble total energies and enthalpies of adsorption, and proposes a machine-learning-based Monte Carlo resampling method to recover target-level results within chemical accuracy.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)
Article
Chemistry, Physical
Federico Coppola, Martina Nucci, Marco Marazzi, Dario Rocca, Mariachiara Pastore
Summary: In this study, we investigated the photophysics and photochemistry of a molecular switch for solar energy storage and release. We characterized the valence and Rydberg states of norbornadiene (NBD) and quadricyclane (QC) using CASPT2//CASSCF theory, and found good agreement with experimental results. We studied the NBD <-> QC thermal and photochemical valence isomerization reactions and identified low energy crossing points between excited states. The doubly excited valence state was found to play a crucial role in the photoreactivity of both NBD and QC.
Article
Chemistry, Multidisciplinary
Dong Seob Kim, Di Huang, Chunhao Guo, Kejun Li, Dario Rocca, Frank Y. Gao, Jeongheon Choe, David Lujan, Ting-Hsuan Wu, Kung-Hsuan Lin, Edoardo Baldini, Li Yang, Shivani Sharma, Raju Kalaivanan, Raman Sankar, Shang-Fan Lee, Yuan Ping, Xiaoqin Li
Summary: A long-standing pursuit in materials science is to identify suitable magnetic semiconductors for integrated information storage, processing, and transfer. Van der Waals magnets have brought forth new material candidates for this purpose. Recently, sharp exciton resonances in antiferromagnet NiPS3 have been reported to correlate with magnetic order, that is, the exciton photoluminescence intensity diminishes above the Neel temperature. Here, it is found that the polarization of maximal exciton emission rotates locally, revealing three possible spin chain directions. This study shows that anisotropic exciton photoluminescence can be used to read out local spin chain directions in antiferromagnets and realize multi-functional devices via spin-photon transduction.
ADVANCED MATERIALS
(2023)
Article
Chemistry, Physical
Basile Herzog, Bastien Casier, Sebastin Lebegue, Dario Rocca
Summary: The configuration interaction approach is a powerful method for solving the Schrödinger equation in realistic molecules and materials, but it has a scalability issue that limits its practical use. In this study, we propose a machine learning approach to selectively generate important configurations, which leads to faster convergence to chemical accuracy compared to random sampling or Monte Carlo configuration interaction method. This work opens up new possibilities for using generative models to solve electronic structure problems.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2023)
Article
Chemistry, Multidisciplinary
Bin Liu, Dario Rocca, He Yan, Ding Pan
Summary: It has been found that the sulfur-nitrogen noncovalent interaction may reduce the band gaps of polymers and enhance charge transfer more significantly than other noncovalent interactions, a discovery consistent with experimental data. This interaction may further influence the electronic structure of coplanar conjugated polymers beyond just improving molecular planarity, suggesting a new mechanism for manipulating the electronic properties of polymers for high-performance solar cells.
Article
Chemistry, Physical
Minho Kim, Tim Gould, Ekaterina I. Izgorodina, Dario Rocca, Sebastien Lebegue
Summary: This study tests various dispersion corrected versatile Generalized Gradient Approximation (GGA) and meta-GGA functionals for predicting interactions of ionic liquids, finding that most can predict energies accurately. Additionally, it shows that PBE calculations and GTO methods have negligible differences in evaluating ionic liquids. Furthermore, explicit van der Waals density functionals show higher success rates compared to traditional dispersion models, indicating a need for improvements in low-cost dispersion correction models for ions.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2021)
Article
Chemistry, Physical
Fernanda C. Bononi, Zekun Chen, Dario Rocca, Oliviero Andreussi, Ted Hullar, Cort Anastasio, Davide Donadio
JOURNAL OF PHYSICAL CHEMISTRY A
(2020)