Results 71 to 80 of about 925,386 (216)
Advancing Energy Materials by In Situ Atomic Scale Methods
Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.Progress in in situ atomic scale methods leads to an improved understanding of new and advanced energy materials, where a local understanding of complex, inhomogeneous systems or interfaces down to the atomic scale and quantum level is required. Topics from photovoltaics, dissipation losses, phase transitions, and chemical energy conversion are ...
Christian Jooss +21 more
wiley +1 more source
One‐Pot Biphasic Photocatalytic CO2‐to‐Carbonylation Cascades
Angewandte Chemie, EarlyView.Bioinspired biphasic compartmentalization enables one‐pot cascades where photocatalytic CO2 reduction generates CO for carbonylative cross‐couplings to synthesize complex organic products, including a pharmaceutical. ABSTRACT Photosynthesis compartmentalizes reactions across the thylakoid membrane in vivo to upcycle CO2 into complex chemicals that are ...
Sampurna Mitra +3 more
wiley +2 more sources
Sulfide‐Based Electrolytes for All‐Solid‐State Sodium Batteries
Advanced Energy Materials, EarlyView.This review covers the structural features and synthesis strategies of sulfide‐based solid electrolytes, as well as critical challenges related to conductivity, interfacial and moisture stability, and scaling‐up for practical application in Sodium‐based All Solid‐State Batteries.
Han Yang +6 more
wiley +1 more source
Advanced Energy Materials, EarlyView.Replacing toxic NiOx with phenyl‐substituted phosphonic‐acid carbazole monolayers (Ph‐5PACz) yields inverted perovskite solar cells that are efficient and recyclable. The nickel‐free interface reaches 25.3% efficiency and enables closed‐loop ITO recovery with near‐98% performance retention, while life‐cycle and techno‐economic analyses confirm lower ...
Yanxue Wang +17 more
wiley +1 more source
Early Miocene coastal taphonomy: piddock and barnacle inclusions from Chiapas amber [PDF]
Acta Palaeontologica PolonicaPiddocks (Pholadidae) are bivalves adapted for boring in substrates such as wood, rocks, and fossil resins. While the trace fossils associated with their boring behavior (Teredolites and Apectoichnus) are well documented, their body fossils are much ...
Błażej Bojarski +2 more
doaj +1 more source
Developing slurries for carbon capture: From synthetic gas mixtures to flue gas
AIChE Journal, EarlyView.Abstract Deep eutectic solvent (DES)‐based systems have recently emerged as promising alternatives to conventional liquid sorbents for CO2 capture due to their tunable properties and potential for enhanced mass transfer. In this work, two DES‐based slurry systems previously developed for CO2 capture, one aqueous and one non‐aqueous, were further ...
Sahar Foorginezhad +3 more
wiley +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
Advanced Intelligent Discovery, EarlyView.This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source
Geologica Carpathica, 2019 The Untersberg section (Northern Calcareous Alps, Austria) provides an expanded and biostratigraphically well constrained deep-sea record of the Paleocene–Eocene transition in the north-western Tethyan realm.
Uchman Alfred +2 more
doaj +1 more source
An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting
Advanced Intelligent Discovery, EarlyView.Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto +5 more
wiley +1 more source
Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training
Advanced Intelligent Systems, EarlyView.The environmental footprint of spiking neural networks is quantified during dataset encoding and training for autonomous driving regression across three benchmarks. Temporal depth emerges as the dominant driver of energy consumption and CO2 emissions, while the accuracy–energy trade‐off proves dataset‐dependent. On conventional hardware, spiking models
Fernando S. Martínez +3 more
wiley +1 more source