化学物理
Machine learning potentials (MLPs) are widely applied as an efficient alternative way to represent potential energy surfaces (PES) in many chemical simulations. The MLPs are often evaluated with the root-mean-square errors on the test set…
Strong/static electronic correlation mediates the emergence of remarkable phases of matter, and underlies the exceptional reactivity properties in transition metal-based catalysts. Modeling strongly correlated molecules and solids calls for…
The vacuum Rabi splitting (VRS) in molecular polaritons stands as a fundamental measure of collective light-matter coupling. Despite its significance, the impact of molecular disorder on VRS is not fully understood yet. This study delves…
Large molecular representation models pre-trained on massive unlabeled data have shown great success in predicting molecular properties. However, these models may tend to overfit the fine-tuning data, resulting in over-confident predictions…
Fluctuations in the energy gap and coupling constants in and between chromophores can play important role in the absorption and energy transfer across a collection of two level systems. In a noisy environment, fluctuations can control…
Tropospheric ozone, known as a concerning air pollutant, has been associated with health issues including asthma, bronchitis, and impaired lung function. The rates at which peroxy radicals react with NO play a critical role in the overall…
New technology for energy storage is necessary for the large-scale adoption of renewable energy sources like wind and solar. The ability to discover suitable catalysts is crucial for making energy storage more cost-effective and scalable.…
A model potential previously developed for the ammonia molecule is treated in a single-center partial-wave approximation in analogy with a self-consistent field method developed by Moccia. The latter was used in a number of collision…
Extracting consistent statistics between relevant free-energy minima of a molecular system is essential for physics, chemistry and biology. Molecular dynamics (MD) simulations can aid in this task but are computationally expensive,…
Dissociative electron attachment (DEA) is one of the processes that shows a strong coupling between the nuclear and electronic degrees of freedom in a molecule. This coupling results in an efficient transformation of the kinetic energy of…
Dissociative electron attachment (DEA) shows functional group-dependent site selectivity in the $H^-$ ion channel. In this context, the thiol functional group has yet to be studied in great detail, although this functional group carries…
The velocity Slice Imaging technique has revolutionised electron molecule interaction studies. Multiple electrostatic lens assemblies are often used in spectrometers for resolving low kinetic energy fragments. However, in a crossed-beam…
Dissociative electron attachment (DEA) is an important tool for investigating negative ion resonances. We have studied the negative ion resonances of H2 at 10 eV and 14 eV using the improved velocity slice imaging technique. We obtained…
This paper presents the inversion symmetry breaking observed in ion-pair formation from molecular hydrogen on electron impact. We explain these observations using quantum interference of two dissociation paths coherently accessed by…
We present a quantum algorithm based on the Tensor-Train Thermo-Field Dynamics (TT-TFD) method to simulate the open quantum system dynamics of intramolecular charge transfer modulated by an optical cavity on noisy intermediate-scale quantum…
We analyze the real-time electron-photon dynamics in long-range polariton-mediated energy transfer using a real-time quantum electrodynamics coupled cluster (RT-QED-CC) model, which allows for spatial and temporal visualization of transport…
In this article, we present an interpolative separable density fitting (ISDF) based algorithm to calculate exact exchange in periodic mean field calculations. In the past, decomposing the two-electron integrals into tensor hypercontraction…
Machine learning interatomic potentials (MLIPs) enables molecular dynamics (MD) simulations with ab initio accuracy and has been applied to various fields of physical science. However, the performance and transferability of MLIPs are…
A mathematical model is developed, to jointly analyze elastic and inelastic scattering data of fluctuating membranes within a single theoretical framework. The model builds on a non-homogeneously clipped time-dependent Gaussian random…
Molecular docking (MD) is a crucial task in drug design, which predicts the position, orientation, and conformation of the ligand when bound to a target protein. It can be interpreted as a combinatorial optimization problem, where quantum…