Results 101 to 110 of about 2,248,852 (247)

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Investigation of Cubic EOS Models for HFO-1234yf Refrigerant Used In Automotive application [PDF]

, 2012
The need for a consistent and reliable calculation of thermodynamic property of refrigerants has been a topic of research since the past decade. This paper reports a study of various cubic equations of state (EOS) for a refrigerant to be used in ...
Cornelio, Avi Anthony, Limperich, Dirk, Agrawal, Anant   +2 more
core  

Energetic Offset in Organic Solar Cells‐ Importance, Confusion and Outlook

Advanced Materials, EarlyView.
Energetic offsets in organic solar cells (OSCs) remain a subject of debate due to measurement‐ and lab‐dependent discrepancies. This Perspective clarifies the physical origins of these variations and identifies temperature‐dependent electro‐optical methods as a reliable approach to obtain consistent offset values.
Nakul Jain, Xian'e Li, Mats Fahlman, Olle Inganäs, Koen Vandewal, Feng Gao   +5 more
wiley   +1 more source

Energy, entropy and work in computational ecosystems: a thermodynamic account

, 2008
Recently, computer scientists have begun to build computational ecosystems in which multiple autonomous agents interact locally to achieve globally efficient organised behaviour. Here we present a thermodynamic interpretation of these systems.
Jacyno, Mariusz, Bullock, Seth
core   +1 more source

Thermodynamic Optimization for an Endoreversible Dual-Miller Cycle (DMC) with Finite Speed of Piston. [PDF]

Entropy (Basel), 2018
Wu Z, Chen L, Feng H.
europepmc   +1 more source

Evidence for Itinerant Ferromagnetic Flat Bands Producing Large Transverse Responses

Advanced Materials, EarlyView.
Itinerant ferromagnetic flat bands are demonstrated in GdCo5 with a high Curie temperature of 940K, a stacked honeycomb–kagome lattice, through angle‐resolved photoemission spectroscopy and magneto‐thermoelectric measurements. These topological flat bands generate large Berry curvaturte, producing gigantic anomalous Nernst effect with record‐high ...
Susumu Minami, Yangming Wang, Seigo Souma, Hiroto Nakamura, Akito Sakai, Takumi Osumi, Hang Su, Hikaru Watanabe, Shun'ichiro Kurosawa, Rikuto Oiwa, Daisuke Nishio‐Hamane, Kosuke Nakayama, Takuya Nomoto, Ryotaro Arita, Takafumi Sato, Satoru Nakatsuji   +15 more
wiley   +1 more source

Thermodynamic Investigation of Several Natural Polyols (III) Heat Capacities and Thermodynamic Properties of Erythritol

, 2008
Thermodynamic Investigation of Several Natural Polyols (III) Heat Capacities and Thermodynamic Properties of ...
张景楠, 童波, 谭志诚
core  

Entropy Generation Analysis and Thermodynamic Optimization of Jet Impingement Cooling Using Large Eddy Simulation. [PDF]

Entropy (Basel), 2019
Ries F, Li Y, Nishad K, Janicka J, Sadiki A.   +4 more
europepmc   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source