Results 131 to 140 of about 24,298 (249)

Analysis of Ruddlesden‐Popper and Dion‐Jacobson 2D Lead Halide Perovskites Through Integrated Experimental and Computational Analysis

open access: yesBattery Energy, Volume 4, Issue 2, March 2025.
Optimized ML framework for predicting RP and Dj phases in perovskite solar cells. ABSTRACT Two‐dimensional (2D) lead halide perovskites (LHPs) have captured a range of interest for the advancement of state‐of‐the‐art optoelectronic devices, highly efficient solar cells, next‐generation energy harvesting technologies owing to their hydrophobic nature ...
Basir Akbar, Kil To Chong, Hilal Tayara
wiley   +1 more source

Variable annuity portfolio valuation with SHapley Additive exPlanations

open access: yesInsurance: Mathematics and Economics
Gayani Thalagoda   +3 more
openaire   +1 more source

Engineering Biochar‐Derived Functional Materials for High‐Performance Supercapacitors: Design Principles, Mechanisms, and Scalable Strategies

open access: yesCarbon Energy, EarlyView.
ABSTRACT Biochar has emerged as a useful and adaptable source of carbon for supercapacitor electrodes. Its value comes from the way biomass chemistry, thermal conversion, and activation conditions shape the resulting pore network, surface groups, and degree of carbon ordering.
Soumen Mandal   +6 more
wiley   +1 more source

Porous Carbon Materials for Carbon Dioxide Capture

open access: yesCarbon Energy, EarlyView.
This work aims to address the current status and challenges associated with the regulation of pore structures, as well as the influence of pore structures on CO2 capture. Systematic quantitative analysis of structure–property relationships, combined with machine learning approaches, can effectively evaluate the contributions of structural ...
Zhifu Liu   +6 more
wiley   +1 more source

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

Random forest regression for catalyst performance prediction and validation of tri‐reforming of methane (TRM)

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Abstract Carbon dioxide‐reduced hydrogen can be synthesized through various methods such as dry‐reforming (DRM), steam reforming (SMR), and partial oxidation (POX). Tri‐reforming of methane (TRM) is a promising technology which combines all the above‐mentioned processes for the simultaneous production of hydrogen and syngas with high energy efficiency.
Paulo A. L. de Souza   +3 more
wiley   +1 more source

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