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ISSN: 2666-9528
CN: 10-1713/TQ
p-ISSN: 2096-9147

Critical evaluation of feature importance assessment in FFNN-based models for predicting Kamlet-Taft parameters

Mohan et al. developed a feed-forward neural network (FFNN) model to predict Kamlet-Taft parameters using quantum chemically derived features, achieving notable predictive accuracy. However, this study...

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pH-tuneable simultaneous and selective dye wastewater remediation with digestate-derived biochar: adsorption behaviour, mechanistic insights and potential application

The use of biochar for organic pollutants adsorption has emerged as a key component in wastewater remediation research. In this study, biochar prepared from digestate was subjected to nitric acid functionalization...

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Optimization strategies and diagnostic techniques for water management in proton exchange membrane fuel cells

Proton exchange membrane fuel cells (PEMFCs) are efficient and zero emission energy conversion technology with promising application prospects towards carbon neutrality. The PEMFC's performance is largely...

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Exploring the chemical space of ionic liquids for CO2 dissolution through generative machine learning models

For discovering uncharted chemical space of ionic liquids (ILs) for CO2 dissolution, a reliable generative framework combining re-balanced variational autoencoder (VAE), artificial neural network (ANN),...

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Efficient removal and reusage of acid soluble oil in waste H2SO4 of isobutane alkylation by low-temperature carbonization process

Waste H2SO4 from industrial isobutane alkylation, a hazardous thick liquid with a high concentration of acid soluble oil (ASO) impurities, poses challenges in the regeneration process. Herein, an innovative...

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Synergistic enhancement of pollutant removal from high-salt wastewater using coagulation-flotation combined process

Sufficient treatment of industrial organic wastewater with high salt and large amounts of suspended particulate matter remains a challenge worldwide. In this work, a novel coagulation-flotation combined...

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Oxoammonium salt mediated conversion of cyclohexylamine toward cyclohexanone with water as the oxygen source

Cyclohexylamine is a key byproduct during the production of cyclohexanone oxime, which is an important bulk chemical in material industry. Here we report a highly efficient approach to oxidize cyclohexylamine...

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Screening HFC/HFO and ionic liquid for absorption refrigeration at the atomic scale by the prediction model of machine learning

Absorption refrigeration is a highly effective method for utilizing renewable energy, as it can be driven by low-grade heat sources such as industrial waste heat, solar energy, and geothermal energy....

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Synergistic coordination-regulated separation of nickel and cobalt from spent Ni(II) and Co(II) bearing choline chloride/ethylene glycol electrolyte: theoretical and experimental investigations

Developing efficient and environmentally friendly metal recovery technologies from secondary resources is crucial for enhancing resource utilization and promoting environmental sustainability. However,...

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Constructing potassium and hydroxyl co-doped dual-dipole structures on highly active 3D g-C3N4 surfaces for highly boosting photocatalytic hydrogen peroxide production efficiency in pure water

Producing hydrogen peroxide (H2O2) through visible-light-driven photocatalytic oxygen reduction in pure water is crucial for sustainable ecological applications but poses significant challenges. It...

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Establishing a generalized model for accurate prediction of higher heating values of substances with large ash fractions

The higher heating value (HHV) of biomass is a crucial property for design calculations and numerical simulations in bioenergy utilization. However, existing models for HHV prediction faced challenges...

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Evaluation of gum arabic and gelatine coacervated microcapsule morphology and core oil encapsulation efficiency by combining the spreading coefficient and two component surface energy theory

Microcapsules containing various flavour/fragrance oils with different properties were fabricated using gelatine and gum arabic by complex coacervation. The surface properties (surface polarity and...

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CO2 capture and conversion using graphene-based materials: a review on recent progresses and future outlooks

Rapidly increasing global atmospheric carbon dioxide (CO2) concentration poses a serious threat to life on Earth. Conventional CO2 capture methodologies which rely on using sorbents to capture CO2 from...

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OFC: Outside Front Cover

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COSMO-RS screening of organic mixtures for membrane extraction of aromatic amines: TOPO-based mixtures as promising solvents

Aromatic amines are crucial in pharmaceuticals, but their synthesis is challenging due to unfavorable reaction equilibria and the use of costly, environmentally unfriendly methods. This study presents...

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Physics-informed machine learning to predict solvatochromic parameters of designer solvents with case studies in CO2 and lignin dissolution

The polarity of solvents plays a critical role in various research applications, particularly in their solubilities. Polarity is conveniently characterized by the Kamlet-Taft parameters that is, the...

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Artificial intelligence for chemical engineering

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Multi-criteria computational screening of [BMIM][DCA]@MOF composites for CO2 capture

Ionic liquid (IL) can be inserted into metal organic framework (MOF) to form IL@MOF composite with enhanced properties. In this work, hypothetical IL@MOFs were computationally constructed and screened...

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Advanced data-driven techniques in AI for predicting lithium-ion battery remaining useful life: a comprehensive review

As artificial intelligence (AI) technology evolves, data-driven approaches are gaining attention in predicting lithium-ion battery's remaining useful life (RUL). Indeed, accurate RUL prediction is challenging,...

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OFC: Outside Front Cover

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Integration of physical information and reaction mechanism data for surrogate prediction model and multi-objective optimization of glycolic acid production

With the continuous development of the chemical industry, the concept of advocating green development has become increasingly popular. Glycolic acid (GA), serving as the monomer for biodegradable plastic...

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Machine learning-assisted prediction and optimization of solid oxide electrolysis cell for green hydrogen production

The solid oxide electrolysis cell (SOEC) holds great promise to efficiently convert renewable energy into hydrogen. However, traditional modeling methods are limited to a specific or reported SOEC system....

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Deep learning-based prediction of velocity and temperature distributions in metal foam with hierarchical pore structure

Constrained by the substantial computational time required for numerical simulation, a deep learning technique is applied to investigate fluid flow and heat transfer processes in metal foam with a hierarchical...

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Machine learning models coupled with ionic fragment σ-profiles to predict ammonia solubility in ionic liquids

Emitting NH3 into the atmosphere leads to significant air pollution, while NH3 itself serves as an essential component for fertilizers and refrigerants in industry. Thus, recovering and reusing NH3...

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Pressure swing adsorption process modeling using physics-informed machine learning with transfer learning and labeled data

Pressure swing adsorption (PSA) modeling remains a challenging task since it exhibits strong dynamic and cyclic behavior. This study presents a systematic physics-informed machine learning method that...

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