Results 161 to 170 of about 85,695 (269)

Predicting solar cell efficiencies using historical data from a manufacturing process

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Abstract The solar cell manufacturing data of a passivated emitter and rear cell solar cell manufacturing plant was studied to assess the effects of tool usage and the processing time spent on each tool on the solar cell efficiency. Since manufacturing processes involve several steps with multiple tools, tracing their quality parameters back to the ...
Sushmita Mittra, Vinay Prasad
wiley   +1 more source

Random forest regression for catalyst performance prediction and validation of tri‐reforming of methane (TRM)

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Abstract Carbon dioxide‐reduced hydrogen can be synthesized through various methods such as dry‐reforming (DRM), steam reforming (SMR), and partial oxidation (POX). Tri‐reforming of methane (TRM) is a promising technology which combines all the above‐mentioned processes for the simultaneous production of hydrogen and syngas with high energy efficiency.
Paulo A. L. de Souza   +3 more
wiley   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos   +3 more
wiley   +1 more source

Safety soft sensor development for pilot‐scale ilmenite electric arc furnace using long short‐term memory‐based architecture

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Abstract Ilmenite electric arc furnaces (EAFs) are used for smelting titanium‐iron oxide ore at high temperatures generated by electrical arcs to produce titanium slag and pig iron. As these units are pushed to their limits, ensuring safe and reliable operation becomes challenging.
Antony Gareau‐Lajoie   +4 more
wiley   +1 more source

Bridging Theory and Prediction: A Hybrid SEM and Machine Learning Approach to Optimize Lean Construction for Megaproject Sustainability in China

open access: yesCorporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Construction megaprojects, large‐scale, complex, and capital‐intensive, are particularly prone to inefficiencies, cost overruns, delays, and environmental degradation due to fragmented workflows, stakeholder misalignment, and resource intensity.
Abdelazim Ibrahim   +5 more
wiley   +1 more source

Neural Network‐Based Detection of Adulterants in Opioid Samples Using IR Absorption Spectroscopy

open access: yesDrug Testing and Analysis, EarlyView.
We construct a neural network for the classification of bromazolam and fluorofentanyl in illicit opioid samples. The model outperforms a random forest classifier and shows elevated performance for low concentration samples. ABSTRACT Community‐based drug checking services are challenged in their ability to reliably detect low concentration adulterants ...
Joshua Jai   +4 more
wiley   +1 more source

Real‐time monitoring of tunnel structures using digital twin and artificial intelligence: A short overview

open access: yesDeep Underground Science and Engineering, EarlyView.
How artificial intelligence (AI) and digital twin (DT) technologies are revolutionizing tunnel surveillance, offering proactive maintenance strategies and enhanced safety protocols. It explores AI's analytical power and DT's virtual replicas of infrastructure, emphasizing their role in optimizing maintenance and safety in tunnel management.
Mohammad Afrazi   +4 more
wiley   +1 more source

AI‐Driven Precision Annealing for High Performance Fe‐Based Amorphous Alloys

open access: yesENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
The four stages of the research process are as follows: First, data is collected and a database is constructed. This is followed by feature selection and analysis, then the establishment of machine learning models, and finally formulation design and preparation.
Yichuan Tang   +13 more
wiley   +1 more source

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