AIMC Topic: Hot Temperature

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Multi-functionalities of citric acid assisted thermal hydrolysis for sludge pretreatment: A novel method assisting in sludge treatment targeting multiple-objectives.

Journal of hazardous materials
Pretreatment is essential for enhancing sludge treatment efficiency, including anaerobic digestion, phosphorus recovery, sludge dewatering, and heavy metal removal. However, few techniques simultaneously address multiple treatment objectives. In this...

Electronic nose, HS-GC-IMS, HS-SPME-GC-MS, and deep learning model were used to analyze and predict the changes and contents of VOCs in in-shell walnut kernels under different roasting conditions.

Food chemistry
Roasting imparts walnuts with an increased amount of hedonic aromas. Consequently, this study comprehensively analyzed aroma characteristics of in-shell walnut kernels during roasting at different conditions using quantitative descriptive analysis, E...

Joint control and machine learning prediction of co-formation and kinetic profiles of typical hazardous Maillard reaction products by catechin treatment in air-fried potato chips.

Food chemistry
The Maillard reaction generates hazardous processing contaminants, including acrylamide (AA) and Nε-(carboxymethyl)lysine (CML), necessitating effective inhibitors. Here we use machine learning approaches to predict how catechin treatment reduces sim...

Heat loss evaluation for heating building envelope based on relevance vector machine.

PloS one
Due to the influence of many factors, there is no reasonable evaluation method for the heat loss evaluation of the envelope, which leads to the deviation of the evaluation results of building energy consumption. By comparing different regression anal...

Flow and heat transfer of Poly Dispersed SiO2 Nanoparticles in Aqueous Glycerol in a Horizontal pipe: Application of ensemble and evolutionary machine learning for model-prediction.

PloS one
Stable nanofluid dispersion with SiO2 particles of 15, 50, and 100 nm is generated in a base liquid composed of water and glycerol in a 7:3 ratio and tested for physical characteristics in the temperature range of 20-100oC. The nanofluid showed excel...

Predicting the tensile properties of heat treated and non-heat treated LPBFed AlSi10Mg alloy using machine learning regression algorithms.

PloS one
In this study, the ability of machine learning algorithms to predict tensile properties of both heat-treated and non-heat treated LPBFed AlSi10Mg alloy is investigated. The data was analyzed using various Machine Learning Regression (MLR) models such...

Deep learning-based spatial optimization of green and cool roof implementation for urban heat mitigation.

Journal of environmental management
Intensifying urban heat extremes require efficient mitigation strategies; therefore, we propose a methodological framework for optimizing the implementation of urban green and cool roofs to reduce heat stress while maximizing their cost-effectiveness...

AI-based forecasting of dynamic behaviors of Ag and ZnO nanoparticles-enhanced milk in an electromagnetic channel with exponential heating: dairy decontamination.

The European physical journal. E, Soft matter
Electromagnetic plates can be used to heat milk and other dairy products rapidly and uniformly. The use of electromagnetic fields enables precise thermal control, which is crucial for safe pasteurization while retaining the nutritional and sensory qu...

Heat Capacity of Ionic Liquids: Toward Interpretable Chemical Structure-Based Machine Learning Approaches.

Journal of chemical information and modeling
This study focuses on predicting the heat capacity of pure liquid-phase ionic liquids (ILs) using machine learning models from various categories, including support vector machines, instance-based learning, ensemble learning, and neural networks, wit...

Developing a seasonal-adjusted machine-learning-based hybrid time‑series model to forecast heatwave warning.

Scientific reports
Heatwaves pose a significant threat to environmental sustainability and public health, particularly in vulnerable regions and rapidly growing cities. They cause water shortages, stress on plants, and an overall drying out of landscapes, reducing plan...