Results 231 to 240 of about 27,872 (320)

Machine Learning Paradigm for Advanced Battery Electrolyte Development

open access: yesCarbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su   +4 more
wiley   +1 more source

Shedding Light on Synthetic Autocatalysis: From Conventional Closed‐Shell Chemistries to Overlooked Open‐Shell Occurrences

open access: yesChemistry – A European Journal, EarlyView.
Why add another catalyst when the product itself holds the power to catalyze its own formation? Autocatalysis in synthetic chemistry enhances reaction efficiency and uncovers novel catalytic behavior across both closed‐shell and open‐shell systems, expanding reactivity and enabling innovative design strategies.
Jaspreet Kaur, Joshua P. Barham
wiley   +1 more source

Tunable amylopectin graft copolymers for flocculating and dewatering iron ore tailings

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Abstract Polyacrylamide (PAM), the standard flocculant for mining tailings, often produces turbid supernatants and poorly dewatered sediments, limiting water reuse and tailings densification. We synthesized amylopectin‐graft‐poly[(2‐methacryloyloxy)ethyl]trimethylammonium chloride (AP‐g‐PMETAC) copolymers with systematically varied graft frequency (N = 
Gustavo P. Zago   +2 more
wiley   +1 more source

Integrative bibliometrics and spatial transcriptomics identify CAF-associated genes and immune niches in hepatocellular carcinoma. [PDF]

open access: yesDiscov Oncol
Ma CL   +16 more
europepmc   +1 more source

Hybrid machine learning and genetic algorithm approach for catalyst and process optimization in Fischer–Tropsch synthesis toward sustainable fuel production

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Graphical representation of a data‐driven framework for Fischer‐Tropsch synthesis (FTS) modelling and optimization. Abstract This study presents a data‐driven approach for predicting the relationships between catalyst design, process conditions, and product selectivity in Fischer–Tropsch synthesis (FTS).
Doaa M. Hassan   +2 more
wiley   +1 more source

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