The journal of physical chemistry letters
Oct 2, 2023
Brain-inspired neuromorphic computing is currently being investigated for effective artificial intelligence (AI) systems. The development of artificial neurons and synapses is imperative to creating efficient computational biomimetic networks. Here w...
The journal of physical chemistry letters
Jul 17, 2023
Hydrogen bonding interactions with chromophores in chemical and biological environments play a key role in determining their electronic absorption and relaxation processes, which are manifested in their linear and multidimensional optical spectra. Fo...
The journal of physical chemistry letters
Mar 16, 2023
The human brain completes intelligent behaviors such as the generation, transmission, and storage of neural signals by regulating the ionic conductivity of ion channels in neuron cells, which provides new inspiration for the development of ion-based ...
The journal of physical chemistry letters
Feb 16, 2023
Predicting protein-ligand binding affinities (PLAs) is a core problem in drug discovery. Recent advances have shown great potential in applying machine learning (ML) for PLA prediction. However, most of them omit the 3D structures of complexes and ph...
The journal of physical chemistry letters
Dec 29, 2022
Currently, computational materials science involves human-computer interaction through coding in software or neural networks. There is still no direct way for human intelligence endorsement. The digitalization of human intelligence should be the ulti...
The journal of physical chemistry letters
Nov 11, 2022
Nonadiabatic coupling (NAC) plays a central role in driving nonadiabatic dynamics in various photophysical and photochemical processes. However, the high computational cost of NAC limits the time scale and system size of quantum dynamics simulation. ...
The journal of physical chemistry letters
Oct 24, 2022
Reconstructing force fields (FFs) from atomistic simulation data is a challenge since accurate data can be highly expensive. Here, machine learning (ML) models can help to be data economic as they can be successfully constrained using the underlying ...
The journal of physical chemistry letters
Oct 21, 2022
We have introduced a machine learning workflow that allows for optimizing electronic properties in the density functional tight binding method (DFTB). The workflow allows for the optimization of electronic properties by generating two-center integral...
The journal of physical chemistry letters
Oct 19, 2022
We have trained the Extreme Minimum Learning Machine (EMLM) machine learning model to predict chemical potentials of individual conformers of multifunctional organic compounds containing carbon, hydrogen, and oxygen. The model is able to predict chem...
The journal of physical chemistry letters
Sep 29, 2022
Optical spectroscopy plays an important role in disease detection. Improving the sensitivity and specificity of spectral detection has great importance in the development of accurate diagnosis. The development of artificial intelligence technology pr...