Results 101 to 110 of about 17,173,168 (192)

Development of neural network models for predicting chemical reaction yields

Predviđanje prinosa kemijskih reakcija predstavlja jednu od najznačajnijih primjena strojnog učenja u kemijskom inženjerstvu jer omogućava zamjenu dugotrajnog i skupog procesa optimizacije koji se tradicionalno oslanjao na metodu pokušaja i pogreške.
Dabo, Jakov
core  

A Fast, Parallelized, GPU-accelerated Photochemical Model, XODIAC, with Built-in Equilibrium Chemistry and Multiple Chemical Networks for Exoplanetary Atmospheres

The Astrophysical Journal
The launch of the James Webb Space Telescope has delivered high-quality atmospheric observations and expanded the known chemical inventory of exoplanetary atmospheres, opening new avenues for atmospheric chemistry modeling to interpret these data.
Priyankush Ghosh, Sambit Mishra, Shubham Dey, Debayan Das, P. B. Rimmer, Liton Majumdar   +5 more
doaj   +1 more source

A Network Model of Chemical Reactions in Primitive Cells.

Seibutsu Butsuri, 1999
Y. Togashi, K. Kaneko
openaire   +2 more sources

Structured Chemical Reaction Modeling with Multitask Graph Neural Networks

Abstract Modeling chemical reactions requires connecting fine-grained atom–bond edits with broader semantic categories. Yet, most machine learning approaches model these aspects in isolation: atom mapping, reaction center identification, and reaction classification are treated as separate problems.
Astero, Maryam, Li, Anchen, Casiraghi, Elena, Rousu, Juho   +3 more
openaire   +1 more source

CONVERGENCE OF MARKOV CHAIN APPROXIMATIONS TO STOCHASTIC REACTION DIFFUSION EQUATIONS [PDF]

In the context of simulating the transport of a chemical or bacterial contaminant through a moving sheet of water, we extend a well established method of approximating reaction-diffusion equations with Markov chains by allowing convection, certain ...
Michael A. Kouritzin, Hongwei Long
core  

Widespread biochemical reaction networks enable Turing patterns without imposed feedback

Nature Communications
Understanding self-organized pattern formation is fundamental to biology. In 1952, Alan Turing proposed a pattern-enabling mechanism in reaction-diffusion systems containing chemical species later conceptualized as activators and inhibitors that are ...
Shibashis Paul, Joy Adetunji, Tian Hong
doaj   +1 more source

Machine Learning of Temperature-Dependent Chemical Kinetics Using Parallel Droplet Microreactors. [PDF]

Adv Sci (Weinh)
Saita M, Hori Y.
europepmc   +1 more source

Graph-Based Generation and Reduction of Complex Chemical Reaction Networks. [PDF]

J Chem Inf Model
Fite S, Gross Z.
europepmc   +1 more source

Local and global stability of equilibria for a class of chemical reaction networks [PDF]

, 2013
Donnell, Pete, Banaji, Murad
core   +1 more source

A catalyst-aware explainable machine learning framework for biodiesel yield prediction over metal-doped biochar and activated carbon catalysts. [PDF]

RSC Adv
Ebrahim M, Mahmoud M, Ashour FH, Ibrahim OA, Khashaba NH.   +4 more
europepmc   +1 more source