Results 11 to 20 of about 1,192,891 (278)

Modeling and Simulating Chemical Reactions [PDF]

open access: yesSIAM Review, 2008
The author presents basic concepts in modelling, using the example of coupled chemical reactions. Four points are examplified: the necessity of modeling assumptions, the need of a multiscale analysis in order to cope with very different characteristic times of the system, a good understanding of deterministic versus probabilistic source of the models ...
Desmond J. Higham, Martínez-Urreaga J.
openaire   +10 more sources

Accelerating the inference of string generation-based chemical reaction models for industrial applications [PDF]

open access: yesJournal of Cheminformatics
Transformer-based, template-free SMILES-to-SMILES translation models for reaction prediction and single-step retrosynthesis are of interest to computer-aided synthesis planning systems, as they offer state-of-the-art accuracy.
Mikhail Andronov   +4 more
doaj   +2 more sources

Chemical knowledge-informed framework for privacy-aware retrosynthesis learning [PDF]

open access: yesNature Communications
Chemical reaction data is a pivotal asset, driving advances in competitive fields such as pharmaceuticals, materials science, and industrial chemistry.
Guikun Chen   +5 more
doaj   +2 more sources

Evaluation of mental models of prospective science teachers on chemical reactions [PDF]

open access: yesJournal of Pedagogical Research, 2021
The aim of this study is to examine prospective science teachers' (PSTs) mental models and meanings for the concept of chemical reaction. For this purpose, this study adopted a phenomenological research design including 48 PSTs.
Volkan Bilir, Sedat Karaçam
doaj   +1 more source

The SIR dynamic model of infectious disease transmission and its analogy with chemical kinetics [PDF]

open access: yesPeerJ Physical Chemistry, 2020
Mathematical models of the dynamics of infectious disease transmission are used to forecast epidemics and assess mitigation strategies. In this article, we highlight the analogy between the dynamics of disease transmission and chemical reaction kinetics ...
Cory M. Simon
doaj   +2 more sources

On Quantitative Comparison of Chemical Reaction Network Models [PDF]

open access: yesElectronic Proceedings in Theoretical Computer Science, 2019
Chemical reaction networks (CRNs) provide a convenient language for modelling a broad variety of biological systems. These models are commonly studied with respect to the time series they generate in deterministic or stochastic simulations. Their dynamic
Ozan Kahramanoğulları
doaj   +1 more source

The GRETOBAPE Gas-phase Reaction Network: The Importance of Being Exothermic

open access: yesThe Astrophysical Journal Supplement Series, 2023
The gas-phase reaction networks are the backbone of astrochemical models. However, due to their complexity and nonlinear impact on the astrochemical modeling, they can be the first source of error in the simulations if incorrect reactions are present ...
Lorenzo Tinacci   +7 more
doaj   +1 more source

Comparison of chemical reaction kinetic models for corn cob pyrolysis

open access: yesEnergy Reports, 2020
This study used thermogravimetric analysis to investigate activation energy and pre-exponential factor of corn cob pyrolysis via various model-free methods.
Kiattikhoon Phuakpunk   +2 more
doaj   +1 more source

Conceitos de química dos ingressantes nos cursos de graduação do Instituto de Química da Universidade de São Paulo Chemistry concepts held by freshmen students of the Institute of Chemistry, University of São Paulo

open access: yesQuímica Nova, 2008
A diagnostic instrument was developed to evaluate the basic chemistry concepts held by freshmen students of the three Chemistry undergraduate courses offered by the University of São Paulo.
Carmen Fernandez   +3 more
doaj   +1 more source

Fuelling the Digital Chemistry Revolution with Language Models

open access: yesCHIMIA, 2023
The RXN for Chemistry project, initiated by IBM Research Europe – Zurich in 2017, aimed to develop a series of digital assets using machine learning techniques to promote the use of data-driven methodologies in synthetic organic chemistry.
Antonio Cardinale   +12 more
doaj   +1 more source

Home - About - Disclaimer - Privacy