Results 301 to 310 of about 5,659,959 (382)

Searching for physical principles of morphogenesis. [PDF]

Development
Claussen N, Brauns F, Streichan SJ.
europepmc   +1 more source

Spectroscopic and DFT techniques on the mechanism of scavenging •OH radicals by crocin. [PDF]

PLoS One
Qu M, Fang W, Men Z.
europepmc   +1 more source

Polymer Systems with Correlated Activity: Stars Versus Linear Chains. [PDF]

Molecules
Buglakov AI, Chuphal P, Rudyak VY, Chertovich AV, Palyulin VV.   +4 more
europepmc   +1 more source

Hybrid Chemical and Data-Driven Model for Stiff Chemical Kinetics Using a Physics-Informed Neural Network

Matthew Frankel, Mario De Florio, Enrico Schiassi, Lina Sela   +3 more
openalex   +1 more source

Hybrid AI/physics pipeline for miniprotein binder prioritization: application to the BRD3 ET domain.

Chem Commun (Camb)
Gaza J, Roth MJ, Montelione GT, Perez A.
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Chemical Physics

Nature, 1886
Henry E. Armstrong
openaire   +2 more sources

Physics-informed neural networks and functional interpolation for stiff chemical kinetics.

Chaos, 2022
This work presents a recently developed approach based on physics-informed neural networks (PINNs) for the solution of initial value problems (IVPs), focusing on stiff chemical kinetic problems with governing equations of stiff ordinary differential ...
Mario De Florio, E. Schiassi, R. Furfaro
semanticscholar   +1 more source

Multiscale Physics-Informed Neural Networks for Stiff Chemical Kinetics.

Journal of Physical Chemistry A, 2022
In this paper, a multiscale physics-informed neural network (MPINN) approach is proposed based on the regular physics-informed neural network (PINN) for solving stiff chemical kinetic problems with governing equations of stiff ordinary differential ...
Yuting Weng, Dezhi Zhou
semanticscholar   +1 more source