Search
Search Results
-
Surrogate Models of Hydrogen Oxidation Kinetics based on Deep Neural Networks
AbstractThe paper presents a data based surrogate model of the chemical kinetics of hydrogen oxidation by air using recurrent and feed-forward neural...
-
Two-Stage MCMC with Surrogate Models for Efficient Uncertainty Quantification in Multiphase Flow
We present a novel two-stage Markov Chain Monte Carlo (MCMC) method that improves the efficiency of MCMC sampling while maintaining its sampling...
-
Conceptual process and surrogate optimization of acrylonitrile production from glycerol via green propylene
Acrylonitrile is a commodity currently produced from petrochemical propylene, with significant economic importance. The development of a sustainable...
-
Kinetic Models of Gasoline Combustion
AbstractThe current state of research on the development of kinetic models of the combustion of gasoline and its components is considered. Surrogate...
-
Development of a surrogate and its comprehensive compact chemical kinetic mechanism for the combustion of Alcohol-To-Jet fuel
This study develops a compact high-fidelity chemical kinetic mechanism for a proposed surrogate of Alcohol-To-Jet fuel, capable of modelling ignition...
-
An optimised and validated surrogate analyte A-TEEM–PARAFAC–PLS technique for detecting and quantifying the biological oxygen demand in surface water
A 5-day test duration makes BOD 5 measurement unsatisfactory and hinders the development of a quick technique. Protein-like fluorescence peaks show a...
-
Surrogate modeling of the effective elastic properties of spherical particle-reinforced composite materials
This paper focuses on the development of a surrogate model to predict the macroscopic elastic properties of polymer composites doped with spherical...
-
Generation of surrogate goldfish Carassius auratus progeny from common carp Cyprinus carpio parents
Surrogate broodstock technology can increase the production efficiency of commercially important fishes that are difficult to breed in confinement...
-
Optimization design of trapezoidal flow field proton exchange membrane fuel cell combined with computational fluid dynamics, surrogate model, and multi-objective optimization algorithm
The flow field structure plays the key roles in the operating reliability and power output of proton exchange membrane fuel cell (PEMFC). This study...
-
A parallel hybrid model for integrating protein adsorption models with deep neural networks
Accurate modeling of mass front evolution in fixed beds is determined by considering equilibrium data for adsorbed component concentrations. While...
-
Rethinking the applicability domain analysis in QSAR models
Notwithstanding the wide adoption of the OECD principles (or best practices) for QSAR modeling, disparities between in silico predictions and...
-
Supercharging hydrodynamic inundation models for instant flood insight
Floods are one of the most frequent and devastating natural disasters for human communities. Currently, flood response management globally commonly...
-
De novo drug design as GPT language modeling: large chemistry models with supervised and reinforcement learning
In recent years, generative machine learning algorithms have been successful in designing innovative drug-like molecules. SMILES is a sequence-like...
-
Primary Predictive Models of Microbial Growth
Foodborne illness occurs when food or beverages are contaminated with pathogenic bacteria, chemicals, or toxins. Understanding microbial physiology...
-
Germicidal efficacy of continuous and pulsed ultraviolet-C radiation on pathogen models and SARS-CoV-2
Ultraviolet radiation’s germicidal efficacy depends on several parameters, including wavelength, radiant exposure, microbial physiology, biological...
-
Rapid and efficient column separation of Re(VII) as a surrogate for Tc(VII) with benzimidazole-based cross-linked poly(ionic liquid)s
In this study, the imidazole-based poly(ionic liquid)s (PILs) synthesized by one step method has been applied for the enrichment and recovery of...
-
Deep Kernel learning for reaction outcome prediction and optimization
Recent years have seen a rapid growth in the application of various machine learning methods for reaction outcome prediction. Deep learning models...
-
A numerical compass for experiment design in chemical kinetics and molecular property estimation
Kinetic process models are widely applied in science and engineering, including atmospheric, physiological and technical chemistry, reactor design,...
-
DTA/TGA/DSC and densification data for iron phosphate glasses having natural UO2.67 or surrogate Bi2O3 added
A new set of iron-uranium phosphate glasses containing (1–20) UO 2.67 . (10–20) Fe 2 O 3 . (55–68) P 2 O 5 (mass/%) were melted adequately. They were tested...
-
Adaptive language model training for molecular design
The vast size of chemical space necessitates computational approaches to automate and accelerate the design of molecular sequences to guide...
