化学物理
We present an original multi-state projective diabatization scheme based on the Green's function formalism that allows the systematic mapping of many-body ab initio calculations onto effective excitonic models. This method inherits the…
Non-thermal molecular plasmas play a crucial role in numerous industrial processes and hold significant potential for driving essential chemical transformations. Accurate information about the molecular composition of the plasmas and the…
Bayesian optimization (BO) protocol based on Active Learning (AL) principles has garnered significant attention due to its ability to optimize black-box objective functions efficiently. This capability is a prerequisite for guiding…
Plasma-activated chemical transformations promise the efficient synthesis of salient chemical products. However, the reaction pathways that lead to desirable products are often unknown, and key quantum-state-resolved information regarding…
In a world made of atoms, the computer simulation of molecular systems, such as proteins in water, plays an enormous role in science. Software packages that perform these computations have been developed for decades. In molecular…
Electronic structures are fully determined by the exchange-correlation (XC) potential. In this work, we develop a new method to construct reliable XC potentials by properly mixing the exact exchange and the local density approximation…
We present a new method for introducing stable non-equilibrium concentration gradients in molecular dynamics simulations of mixtures. This method extends earlier Reverse Non-Equilibrium Molecular Dynamics (RNEMD) methods which use kinetic…
The conversion of biomass-derived materials into value-added products via photocatalysis holds significant promise in driving the development of renewable resources. However, since catalytic processes often require high temperatures and…
The Ryabinkin-Kohut-Staroverov (RKS) and Kanungo-Zimmerman-Gavini (KZG) methods offer two approaches to find exchange-correlation (XC) potentials from ground state densities. The RKS method utilizes the one- and two-particle reduced density…
Using Time-Dependent Density Functional Theory (TDDFT) nonlinear nonperturbative response of the molecular system is studied for photoisomerization reaction. The 1,3-cyclohexadiene photoisomerization is probed by the high-harmonic…
High-strength composite hydrogels cellulose-polyacrylamide were synthesized by free-radical polymerization of acrylamide conducted inside the previously formed physical network of regenerated plant cellulose. Partial hydrolysis of the amide…
Sustainable aviation fuels have the potential for reducing emissions and environmental impact. To help identify viable sustainable aviation fuels and accelerate research, several machine learning models have been developed to predict…
Chemical representation learning has gained increasing interest due to the limited availability of supervised data in fields such as drug and materials design. This interest particularly extends to chemical language representation learning,…
Ultrafast electron diffraction (UED) instruments typically operate at kHz or lower repetition rates and rely on indirect detection of electrons. However, these experiments encounter limitations because they are required to use electron…
Molecular relaxation, finding the equilibrium state of a non-equilibrium structure, is an essential component of computational chemistry to understand reactivity. Classical force field (FF) methods often rely on insufficient local energy…
Recently, Trepte et al. [J. Chem. Phys., vol. 155, 2021] pointed out the importance of analyzing dipole moments in the Fermi-L\"owdin orbital (FLO) self-interaction correction (SIC) for cyclic, planar molecules. In this manuscript, the…
We present an interface of the wavefunction-based quantum-chemical software CFOUR to the multiscale modeling framework MiMiC. Electrostatic embedding of the quantummechanical (QM) part is achieved by analytic evaluation of one-electron…
In recent years, conventional chemistry techniques have faced significant challenges due to their inherent limitations, struggling to cope with the increasing complexity and volume of data generated in contemporary research endeavors.…
In condensed matter physics, particularly in perovskite materials, the rotational motion of molecules and ions is associated with important issues such as ion conduction mechanism. Constrained Molecular Dynamics (MD) simulations offer a…
Easy and effective usage of computational resources is crucial for scientific calculations. Following our recent work of machine-learning (ML) assisted scheduling optimization [Ref: J. Comput. Chem. 2023, 44, 1174], we further propose 1)…