Results 221 to 230 of about 36,148 (258)

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

Artificial intelligence in enzyme catalysis: Emerging trends and applications in biocatalyst engineering

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Schematic representation of artificial intelligence approaches in enzyme catalysis, integrating bibliometric analysis, emerging research trends, and machine learning tools for enzyme design, prediction, and industrial biocatalytic applications. Abstract This study systematically explores the applications of artificial intelligence (AI) in enzyme ...
Misael Bessa Sales   +6 more
wiley   +1 more source

Orchestrating Green Transformation: How AI Adoption Enables Corporate Carbon Neutrality

open access: yesCorporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT As carbon neutrality has become a central goal of global climate governance, how firms achieve low‐carbon transformation has emerged as a critical research issue. However, prior studies have primarily focused on macro‐ or industry‐level analyses, offering limited and fragmented insights into how digital technologies—particularly AI—affect firm‐
Xiaonan Dong, Sungjin Son
wiley   +1 more source

EventFlow: Real‐time neuromorphic event‐driven classification of two‐phase boiling flow regimes

open access: yesDroplet, EarlyView.
We present a real‐time flow regime classification framework that integrates neuromorphic event‐driven sensing with deep recurrent neural networks. Unlike traditional frame‐based approaches, our system captures sparse event streams from an event‐based camera, representing only the dynamic brightness changes at the individual pixel level.
Sanghyeon Chang   +9 more
wiley   +1 more source

Gaborlet‐guided sparse filtering: A novel intelligent method for lithology identification by vibration signals while drilling

open access: yesDeep Underground Science and Engineering, EarlyView.
The flowchart illustrates rock specimen testing, vibration signal acquisition, and feature extraction with Gaborlet and sparse filtering for classification. Abstract Traditional lithology identification methods mainly rely on core sampling and well‐logging data.
Jian Hao   +5 more
wiley   +1 more source

Advancing mine pillar design: Evaluating traditional methods and integrating AI for enhanced stability of pillars in the Great Dyke, Zimbabwe

open access: yesDeep Underground Science and Engineering, EarlyView.
B1 is bord width 1, B2 is bord width 2, L is the pillar length, W is the pillar width, red color and letter A represent the pillars, and white color and number 1 represent excavated areas. Pstress is the average pillar stress; σv is the vertical component of the virgin stress, MPa; and e is the areal extraction ratio. e = B o B o + B P ${\rm{e}}=\frac{{
Tawanda Zvarivadza   +4 more
wiley   +1 more source

Dynamic geo‐hydrogeological monitoring‐driven situational awareness for real‐time floor water inrush risk prediction in deep mining

open access: yesDeep Underground Science and Engineering, EarlyView.
The fused data extracted from the distributed monitoring system as the data basis, combined with dynamic geological data, are imported into a deep learning model. As the geological conditions of mining and excavation change, the risk of water inrush at the working face is retrieved in real time.
Yongjie Li   +4 more
wiley   +1 more source

A Review of Grain Boundaries: Formation Mechanism, Synthesis Strategy, and Application in Electrocatalysis

open access: yesEcoEnergy, EarlyView.
An overview of grain boundary engineering in the field of electrocatalysis. ABSTRACT Key electrocatalytic reactions such as HER, OER, ORR, CO2RR, and NRR offer promising routes for storing renewable energy as chemical fuels. However, their widespread application is constrained due to the lack of highly active and stable catalysts. Grain boundaries (GBs)
Jingyu Gao   +8 more
wiley   +1 more source

Nanophotonic Biosensors and the Paradigm of Trans‐Scale Autonomous Bio‐Integrated Diagnostics for Addressing Health Complexities

open access: yesElectron, EarlyView.
Physics‐driven advances in optical nanobiosensors for rapid, miniaturized, and point‐of‐care diagnostics for next‐generation decentralized and personalized healthcare based on sensor intelligence. ABSTRACT Public health emergencies and the escalating burden of chronic diseases necessitate a paradigm shift from centralized laboratory testing to rapid ...
Vishal Chaudhary   +5 more
wiley   +1 more source

Artificial intelligence for adaptive neuromodulation in drug‐resistant epilepsy

open access: yesEpilepsia, EarlyView.
Abstract Drug‐resistant epilepsy (DRE) affects nearly one third of people with epilepsy and is associated with substantial cognitive, psychiatric, and mortality burdens. For patients who are not candidates for resection or laser interstitial thermal therapy, neuromodulation therapies such as vagus nerve stimulation, deep brain stimulation, and ...
Amir Hossein Daraie   +10 more
wiley   +1 more source

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