From Characterization to Discovery: Artificial Intelligence, Machine Learning and High-Throughput Experiments for Heterogeneous Catalyst Design

ACS Catalysis, Journal Year: 2024, Volume and Issue: 14(15), P. 11749 - 11779

Published: July 24, 2024

This review paper delves into synergistic integration of artificial intelligence (AI) and machine learning (ML) with high-throughput experimentation (HTE) in the field heterogeneous catalysis, presenting a broad spectrum contemporary methodologies innovations. We methodically segmented text three core areas: catalyst characterization, data-driven exploitation, discovery. In characterization part, we outline current prospective techniques used for HTE how AI-driven strategies can streamline or automate their analysis. The exploitation part is divided themes, strategies, that offer flexibility either modular application creation customized solutions. exploration present applications enable areas outside experimentally tested chemical space, incorporating section on computational methods identifying new prospects. concludes by addressing limitations within suggesting possible avenues future research.

Language: Английский

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Exploring artificial intelligence and urban pollution emissions: "Speed bump" or "accelerator" for sustainable development?

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 463, P. 142739 - 142739

Published: May 29, 2024

Language: Английский

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Artificial Intelligence (AI) Can Advance Plastic Sustainability and Circular Economy

ACS Sustainable Resource Management, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 27, 2025

Language: Английский

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Mathematical Model for Combined Toxicity Prediction

Published: Jan. 14, 2025

This chapter delves into the vital realm of combined toxicity prediction, crucial for environmental health and risk assessment. It outlines significance predicting toxicity, exploring different types interactions like synergistic, antagonistic, additive effects their impact on The provides an extensive overview mathematical models used in categorizing them concentration addition (CA), response (RA), independent action (IA), others. evaluates commonly models, such as assessment (RA) interaction-based machine learning/AI-based detailing mechanisms applications. Moreover, it discusses evaluation selection criteria, guiding readers choosing most appropriate model specific scenarios. Future directions research needs are also addressed, highlighting emerging trends potential integration computational approaches prediction. In conclusion, this offers a comprehensive insight aiding hazard across various domains.

Language: Английский

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Enhancing Catalyst Performance Prediction with Hybrid Quantum Neural Networks: A Comparative Study on Data Consistency Variation

ACS Sustainable Chemistry & Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 31, 2025

Data consistency affects the robustness of machine learning-based models. Most experimental and industrial data have low consistency, leading to poor generalization performance. In this study, a hybrid Quantum Neural Network (hybrid QNN) with superior capabilities, was compared established learning models, including artificial neural networks decision-tree-based methods such as CatBoost XGBoost. We evaluated these models by predicting catalyst performance across different data-consistency scenarios using two sets: low-consistency preferential oxidation CO (PROX) high-consistency coupling methane (OCM) catalyst. The QNN performed better in both low- environments, demonstrating robust capabilities. regression tasks, achieved 6.7% lower mean absolute error (MAE) for PROX 35.1% MAE OCM least-performing model. Adaptability is crucial catalysis, where scarcity variability are common. Our research confirms potential comprehensive tool advancing design selection achieving high accuracy predictive power under diverse conditions.

Language: Английский

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USSC-YOLO: Enhanced Multi-Scale Road Crack Object Detection Algorithm for UAV Image

Sensors, Journal Year: 2024, Volume and Issue: 24(17), P. 5586 - 5586

Published: Aug. 28, 2024

Road crack detection is of paramount importance for ensuring vehicular traffic safety, and implementing traditional methods cracks inevitably impedes the optimal functioning traffic. In light above, we propose a USSC-YOLO-based target algorithm unmanned aerial vehicle (UAV) road based on machine vision. The aims to achieve high-precision at all scale levels. Compared with original YOLOv5s, main improvements USSC-YOLO are ShuffleNet V2 block, coordinate attention (CA) mechanism, Swin Transformer. First, address problem large network computational spending, replace backbone YOLOv5s blocks, reducing overhead significantly. Next, reduce problems caused by complex background interference, introduce CA mechanism into network, which reduces missed false rate. Finally, integrate Transformer block end neck enhance accuracy small cracks. Experimental results our self-constructed UAV near-far scene i(UNFSRCI) dataset demonstrate that model giga floating-point operations per second (GFLOPs) compared while achieving 6.3% increase in mAP@50 12% improvement mAP@ [50:95]. This indicates remains lightweight meanwhile providing excellent performance. future work, will assess safety conditions these prioritize maintenance sequences targets facilitate further intelligent management.

Language: Английский

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Advancing Sustainability: Biodegradable Electronics and New Materials through AI and Machine Learning

Published: March 25, 2024

Artificial Intelligence (AI) and machine learning (ML) are revolutionizing science engineering by enabling researchers to analyze vast amounts of data, uncover patterns, make predictions with unprecedented accuracy. The integration AI ML techniques driving innovation across disciplines, paving the way for groundbreaking discoveries technological advancements. On another corner, sustainability in core disciplines is taking hold. Much work has been done on transient technologies, a particular emphasis electronics. research this domain explores new materials, architectures, functionalities devices time-bound lifetime. We present whole landscape view field focus most recent developments, focusing mainly transitory materials such as metals, polymers, semiconducting materials. development optimization commercially viable being accelerated rapid molecular design tools high-throughput experimentation. There discussion difficulties expanding data-driven technologies from small molecules highlighting importance finding designs revamping existing innovative applications. paper emphasizes how crucial it define standardize polymer systems models generate cohesive data collection system automation improvements. It also highlights need improvements methods fully utilize advantages chemistry, significance reliable varied datasets predictive synthesis polymers. article's conclusion addresses necessity fundamental studies classification standardization capitalize potential development.

Language: Английский

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Artificial Intelligence, Smart Applications and Sustainable Consumption: A Theoretical Overview

İktisadi İdari ve Siyasal Araştırmalar Dergisi, Journal Year: 2024, Volume and Issue: 9(25), P. 803 - 820

Published: Oct. 23, 2024

Sustainable consumption means consuming natural resources consciously, considering future generations. In today's technological age, artificial intelligence and smart applications are used to achieve sustainability goals. this context, article examines the impact of (AI) on promoting sustainable behavior. Providing a comprehensive theoretical framework, explores how AI technologies support informed decision-making, maximize resource management, deliver positive environmental across variety industries. Through examples, from energy management plans environmentally friendly retail platforms, effects highlighted. This includes examples promote around world in Türkiye. Natural challenges that need be overcome, such as algorithmic biases, data privacy issues digital divide, also mentioned. The offers recommendations for Türkiye, highlighting importance financing infrastructure, laws, literacy initiatives innovation ecosystems, with aim emphasizing consumption.

Language: Английский

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Comparative Study on the Performance of Gel Grease for High-End Equipment Based on the Synergistic Effect of Friction-Reducing Agents

Gels, Journal Year: 2024, Volume and Issue: 10(9), P. 573 - 573

Published: Sept. 2, 2024

In the field of high-end equipment, synergistic effect friction-reducing agents plays an important role in performance study gel grease. Exploring its tribological and rheological properties can not only significantly reduce coefficient friction mechanical components enhance viscosity at high temperatures but also effectively energy consumption, thus improving service life equipment. this study, Schaeffler Load 460 grease was mixed with polysiloxane modifier (PV611) molybdenum dialkyl dithiocarbamate (RFM3000) according to (3:1, 1:1, 1:3), were investigated by MRS-10G wear tester, MCR302 rotational rheometer, crossover test. Comparative analyses carried out. The results showed that average reduced 57.2%, 60%, 71.9%, respectively, addition two different ratios reducers; diameter abrasive spots 44.5%, 55.4%, 61.3%; shear stress increased 117.94 Pa 1295.02 mPa∙s, compared original grease, which is a good example for lubrication equipment industry. This provides new direction idea research

Language: Английский

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AI‐based R&D for frozen and thawed meat: Research progress and future prospects

Comprehensive Reviews in Food Science and Food Safety, Journal Year: 2024, Volume and Issue: 23(5)

Published: Sept. 1, 2024

Abstract Frozen and thawed meat plays an important role in stabilizing the supply chain extending shelf life of meat. However, traditional methods research development (R&D) struggle to meet rising demands for quality, nutritional value, innovation, safety, production efficiency, sustainability. faces specific challenges, including quality degradation during thawing. Artificial intelligence (AI) has emerged as a promising solution tackle these challenges R&D frozen AI's capabilities perception, judgment, execution demonstrate significant potential problem‐solving task execution. This review outlines architecture applying AI technology meat, aiming make better implement deliver solutions. In comparison methods, current progress application prospects this field are comprehensively summarized, focusing on its addressing key such rapid optimization thawing process. already demonstrated success areas product development, optimization, risk management, control future, AI‐based will also play promoting personalization, intelligent production, sustainable development. remain, need high‐quality data, complex implementation, volatile processes, environmental considerations. To realize full that can be integrated into further is needed develop more robust reliable solutions, general AI, explainable green AI.

Language: Английский

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