Results 151 to 160 of about 17,173,168 (192)

Reactive Machine Learning Interatomic Potentials for Chemistry and Materials Science. [PDF]

Chem Rev
Kim J, Cho H, Jeon H, Jung J, Han S.
europepmc   +1 more source

Rapid and energy-efficient ultra-large library screening for drug discovery on a SpiNNaker2 neuromorphic chip. [PDF]

Commun Chem
Jimenez Siegert JA, Kelber F, Vogginger B, Eisenhuth P, Beining M, Ehrlich V, Partzsch J, Mayr C, Meiler J.   +8 more
europepmc   +1 more source

Parameter Estimation of Microkinetic Models for Heterogeneous Catalysis. [PDF]

Ind Eng Chem Res
Ahmed MGT, Nath Roy B, Hasan MMF.
europepmc   +1 more source

Rapid Fabrication of Starch-Humic Acid Composite Hydrogel via an Internal Mixer for Dye Adsorption. [PDF]

Polymers (Basel)
Chen X, Cheng A.
europepmc   +1 more source

Simulation of oxytactic microbes in hybrid nanofluid with activation energy and LTNE effects using Bayesian regularization neural network technique. [PDF]

Discov Nano
Abbas M, Alam MM, Ben Hamida MB, Hassani MK.   +3 more
europepmc   +1 more source

London Dispersion in Confined Chiral Ion-Pair Asymmetric Catalysis: From Background Interaction to Design Principle. [PDF]

Acc Chem Res
Baldinelli L, Bistoni G.
europepmc   +1 more source

Adsorptive removal of the cationic dye malachite green from wastewater with an anionic hydrogel. [PDF]

RSC Adv
Safdar S, Ajmal M, Zia MA, Khan KA, Shah A.   +4 more
europepmc   +1 more source

Learning the reaction coordinate: collective variables from physical intuition to generative models.

Digit Discov
Talmazan RA, Chen CG, Tang C, Megías A, Contreras Arredondo S, Chipot C.   +5 more
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

IDENTIFYING CHEMICAL REACTION NETWORK MODELS

IFAC Postprint Volumes IPPV / International Federation of Automatic Control, 2007
In this work, an automated chemical reaction network identification procedure using a genetic algorithm (GA) is introduced. The GA uses chemical species concentration data obtained from batch reactors during process experimentation to build ordinary differential equation (ODE) models that represent the chemical reactions occurring.
M J Willis, A R Wright
exaly   +2 more sources

Autonomous learning of generative models with chemical reaction network ensembles

Journal of the Royal Society Interface
Can a micron-sized sack of interacting molecules autonomously learn an internal model of a complex and fluctuating environment? We draw insights from control theory, machine learning theory, chemical reaction network theory and statistical physics to develop a general architecture whereby a broad class of chemical systems can autonomously learn complex
Thomas Ouldridge, William Poole, Manoj Gopalkrishnan   +2 more
exaly   +5 more sources