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Design and selection of suitable sustainable phase change materials for latent heat thermal energy storage system using data-driven machine learning models
The present study aims to develop and implement data-driven machine learning (ML) models for performance prediction of heat flow and specific heat of...
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A Data-Driven Approach for Predicting Industrial Dyeing Recipes of Polyester Fabrics
Polyester is extensively used in the textile industry for fabricating fibers and fabrics. Dyeing for polyester fabrics has a huge demand. Given that...
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A data-driven approach for the guided regulation of exposed facets in nanoparticles
Nanomaterials with high-index facets have desirable properties but are often challenging to synthesize. One way to realize such structures is by...
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Data-driven designs and multi-scale simulations of enhanced ion transport in low-temperature operation for lithium-ion batteries
The low-temperature operation of lithium-ion batteries (LIBs) is a challenge in achieving high-stability battery technology. Moreover, the design and...
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Data-driven approaches for structure-property relationships in polymer science for prediction and understanding
In this review, recent developments in data-driven approaches for structure-property relationships in polymer science are introduced. Understanding...
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Data-driven fault detection for chemical processes using autoencoder with data augmentation
Process monitoring plays an essential role in safe and profitable operations. Various data-driven fault detection models have been suggested, but...
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Combination of Data-Driven and Physics-Based Models for Thick Sintered Electrode Lithium-Ion Batteries
This work explored the use of physics-based and machine learning models in the context of a promising battery material system. The battery materials...
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Data-driven de-smearing of DSC signals
In heat flux differential scanning calorimetry, a pair of identical crucibles, one empty as reference and the other filled with the sample, is heated...
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Reaction Mechanisms and Plasma-Catalyst Interaction in Plasma-Assisted Oxidation of n-Butane: A Data-Driven Approach
Experimental investigations of n-butane oxidation under atmospheric-pressure plasma conditions and in He-dilution have provided detailed information...
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Elucidating the black-box nature of data-driven models in the adsorption of reactive red M-2BE on activated carbon and multi-walled carbon nanotubes through SHapley Additive exPlanations
The removal of reactive red M-2BE dye textile from aqueous solution was performed using multi-walled carbon nanotubes (MWCN) and powdered activated...
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Integrated data-driven and experimental approaches to accelerate lead optimization targeting SARS-CoV-2 main protease
Identification of potential therapeutic candidates can be expedited by integrating computational modeling with domain aware machine learning (ML)...
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Advancing material property prediction: using physics-informed machine learning models for viscosity
In materials science, accurately computing properties like viscosity, melting point, and glass transition temperatures solely through physics-based...
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Data-driven modeling of residential air source heat pump system for space heating
Air source heat pump systems must operate efficiently during the winter to ensure that energy-saving targets are met and occupants of residential and...
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AI-driven molecular generation of not-patented pharmaceutical compounds using world open patent data
Develo** compounds with novel structures is important for the production of new drugs. From an intellectual perspective, confirming the patent...
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Comparison of data-driven identified hypertension-protective dietary patterns among Chinese adults: based on a nationwide study
PurposeDiet pattern (DP) is a key modifiable and cost-effective factor in hypertension (HTN) management. The current study aimed to identify and...
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Capillary Pressure in Unsaturated Food Systems: Its Importance and Accounting for It in Mathematical Models
Capillary pressure plays a critical role in driving fluid flow in unsaturated porous (pores not saturated with liquids but also containing air/gas)...
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Physics-informed deep learning for data-driven solutions of computational fluid dynamics
Computational fluid dynamics (CFD) is an essential tool for solving engineering problems that involve fluid dynamics. Especially in chemical...