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The reformation of catalyst: From a trial-and-error synthesis to rational design
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 …
conversion of various molecules, which is of great importance in the study of chemistry …
[HTML][HTML] Machine learning for advanced energy materials
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 …
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
Carbon quantum dots (CQDs) have versatile applications in luminescence, whereas
identifying optimal synthesis conditions has been challenging due to numerous synthesis …
identifying optimal synthesis conditions has been challenging due to numerous synthesis …
Enhancing biochar-based nonradical persulfate activation using data-driven techniques
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 …
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
Abstract Machine learning (ML)-based prediction of non-linear composition-strength
relationship in concretes requires a large, complete, and consistent dataset. However, the …
relationship in concretes requires a large, complete, and consistent dataset. However, the …
Active Learning-Based Guided Synthesis of Engineered Biochar for CO2 Capture
Biomass waste-derived engineered biochar for CO2 capture presents a viable route for
climate change mitigation and sustainable waste management. However, optimally …
climate change mitigation and sustainable waste management. However, optimally …
Machine-learning-driven synthesis of carbon dots with enhanced quantum yields
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 …
(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
Conspectus Two-dimensional (2D) compound materials are regarded as promising
candidates in many applications, including electronics, optoelectronics, sensors, and flexible …
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 …
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
In the flourishing field of materials science and engineering, ionic liquids (ILs) stand out for
their advantageous features, unique tunable properties, and environmentally friendly …
their advantageous features, unique tunable properties, and environmentally friendly …