Results 91 to 100 of about 66,807 (266)

Prospective LCA of E‐Methanol Along the Transformation of Steel Industry

Chemie Ingenieur Technik, EarlyView.
The environmental effects of change in steel production route on e‐methanol production are analyzed as they shift from blast furnace route to direct reduction route. Specific hydrogen demand reduces, as do the avoided CO2 emissions. E‐methanol's overall carbon footprint stays in a narrow range of −1 to −1.1 kg‐CO2‐eq./kg‐methanol.
Ankur Gaikwad
wiley   +1 more source

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

The 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, Heleno Bispo, Thiago Vaz da Costa, Sérgio Mauro da Silva Neiro   +3 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

Corporate 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, Tarek Zayed, Zoubeir Lafhaj, Ahmed Maged, Ahmed Farouk Kineber, Jingchao Yang   +5 more
wiley   +1 more source

Perceived importance and didactic difficulty of chemistry education: Insights from Czech teachers

The Curriculum Journal, EarlyView.
Abstract This empirical study examines how chemistry teachers in lower and upper secondary schools in the Czech Republic evaluate the content of the chemistry curriculum, focussing on its perceived importance and didactic difficulty. Based on a quantitative survey (N = 146), the study provides insight into the pedagogical content knowledge of ...
Jitka Lorenzová, Blanka Jirkovská, Martin Čapek Adamec, Jan Havlík, Petr Holzhauser, Daniela Nováková, Karel Němejc   +6 more
wiley   +1 more source

Q-LIME $π$: A Quantum-Inspired Extension to LIME

CoRR
Machine learning models offer powerful predictive capabilities but often lack transparency. Local Interpretable Model-agnostic Explanations (LIME) addresses this by perturbing features and measuring their impact on a model's output. In text-based tasks, LIME typically removes present words (bits set to 1) to identify high-impact tokens.
openaire   +2 more sources

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

Deep 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, Danial Jahed Armaghani, Hossein Afrazi, Hadi Fattahi, Pijush Samui   +4 more
wiley   +1 more source

Uniaxial compressive strength prediction and ratio parameter optimization of titanium tailings composite backfill materials using intelligent hybrid models

Deep Underground Science and Engineering, EarlyView.
Based on the 90 datasets, ERT and four optimization algorithms were used to build four hybrid models to predict the UCS of the backfill body. The SMA‐ERT model was the most effective model, and it can reliably guide the design of the backfill ratio parameters. Abstract This study analyzed the feasibility of using titanium (Ti) tailings as a backfilling
Weijun Liu, Zida Liu, Zhixiang Liu
wiley   +1 more source

Mosaic activation of the zebrafish hsp70l heat shock promoter: Implications for interpreting transgenes

Developmental Dynamics, EarlyView.
Abstract Background The promoters and enhancers of heat shock genes, such as the 1.5‐kb promoter of the zebrafish hsp70l gene, are valuable tools for temporal activation of transgenes. It has been widely purported that heat shock treatments result in ubiquitous expression of hsp70l‐driven transgenes.
Jong‐Su Park, Xiangyun Wei
wiley   +1 more source

Stabilization Strategies for Carbon Based Perovskite Solar Cells Under Light, Heat, and Humidity

EcoEnergy, EarlyView.
Carbon‐based MA1−x(AVA)xPbI3/CsPbBr3 QD heterostructures fabricated under ambient conditions exhibit < 5% loss under ISOS‐D‐3 and reversible photo‐induced degradation, revealing the dual role of QDs in defect passivation and dynamic interfacial stabilization.
Emilie Planes, Fatou Diaw‐Ndiaye, Lara Perrin, Maria Bernechea, Lionel Flandin   +4 more
wiley   +1 more source

Ag‐Induced Phase and Defect Engineering of Co‐Evaporated Sb2Se3 Thin Films for Enhanced Photovoltaic Performance

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
The sequential formation of Ag2Se and AgSbSe2 phases at the Sb2Se3/Mo interface upon Ag incorporation in co‐evaporated Sb2Se3 solar cells promotes grain growth and defect passivation. These newly formed intermediate phases enhance crystallinity and suppress recombination, leading to significant improvements in open‐circuit voltage, fill factor, and ...
Van‐Quy Hoang, Jaebaek Lee, Bashiru Kadiri‐English, Eunkyung Cho, Amanat Ali, Naveen Kumar, Evgeniia Gilshtein, Stela Canulescu, Dae‐Ho Son, Hyesun Yoo, Vo Pham Hoang Huy, Quynh Le‐Van, Dae‐Kue Hwang, Jin‐Kyu Kang, Kee‐Jeong Yang, Shi‐Joon Sung, Dae‐Hwan Kim   +16 more
wiley   +1 more source