The reformation of catalyst: From a trial-and-error synthesis to rational design

L Wang, J Wu, S Wang, H Liu, Y Wang, D Wang - Nano Research, 2024‏ - Springer
The appropriate catalysts can accelerate the reaction rate and effectively boost the efficient
conversion of various molecules, which is of great importance in the study of chemistry …

[HTML][HTML] Machine learning for advanced energy materials

Y Liu, OC Esan, Z Pan, L An - Energy and AI, 2021‏ - Elsevier
The screening of advanced materials coupled with the modeling of their quantitative
structural-activity relationships has recently become one of the hot and trending topics in …

Machine learning-guided realization of full-color high-quantum-yield carbon quantum dots

H Guo, Y Lu, Z Lei, H Bao, M Zhang, Z Wang… - Nature …, 2024‏ - nature.com
Carbon quantum dots (CQDs) have versatile applications in luminescence, whereas
identifying optimal synthesis conditions has been challenging due to numerous synthesis …

Enhancing biochar-based nonradical persulfate activation using data-driven techniques

R Wang, S Zhang, H Chen, Z He, G Cao… - Environmental …, 2023‏ - ACS Publications
Converting biomass into biochar (BC) as a functional biocatalyst to accelerate persulfate
activation for water remediation has attracted much attention. However, due to the complex …

Prediction of concrete strengths enabled by missing data imputation and interpretable machine learning

GA Lyngdoh, M Zaki, NMA Krishnan, S Das - Cement and concrete …, 2022‏ - Elsevier
Abstract Machine learning (ML)-based prediction of non-linear composition-strength
relationship in concretes requires a large, complete, and consistent dataset. However, the …

Active Learning-Based Guided Synthesis of Engineered Biochar for CO2 Capture

X Yuan, M Suvarna, JY Lim… - Environmental …, 2024‏ - ACS Publications
Biomass waste-derived engineered biochar for CO2 capture presents a viable route for
climate change mitigation and sustainable waste management. However, optimally …

Machine-learning-driven synthesis of carbon dots with enhanced quantum yields

Y Han, B Tang, L Wang, H Bao, Y Lu, C Guan… - ACS …, 2020‏ - ACS Publications
Knowing the correlation of reaction parameters in the preparation process of carbon dots
(CDs) is essential for optimizing the synthesis strategy, exploring exotic properties, and …

Chemical vapor deposition growth of two-dimensional compound materials: controllability, material quality, and growth mechanism

L Tang, J Tan, H Nong, B Liu… - Accounts of Materials …, 2020‏ - ACS Publications
Conspectus Two-dimensional (2D) compound materials are regarded as promising
candidates in many applications, including electronics, optoelectronics, sensors, and flexible …

Intelligent control of nanoparticle synthesis on microfluidic chips with machine learning

X Chen, H Lv - NPG Asia Materials, 2022‏ - nature.com
Nanoparticles play irreplaceable roles in optoelectronic sensing, medical therapy, material
science, and chemistry due to their unique properties. There are many synthetic pathways …

[HTML][HTML] Revolutionizing inverse design of ionic liquids through the multi-property prediction of over 300,000 novel variants using ensemble deep learning

T Lemaoui, T Eid, AS Darwish, HA Arafat… - Materials Science and …, 2024‏ - Elsevier
In the flourishing field of materials science and engineering, ionic liquids (ILs) stand out for
their advantageous features, unique tunable properties, and environmentally friendly …