Results 71 to 80 of about 29,740 (183)

Why Compressed Hydrides Are Near‐Room‐Temperature Superconductors

Annalen der Physik, EarlyView.
A constant magnitude surface with vector directions indicated of the non‐rigid electronic potential of one displaced lithium atom in a Li crystal. The upper figure is of the calculated gauge‐dependent field, the bottom gives its rotation (curl operator) of the physical field that describes amplitude shift from the front of the displaced atom to behind ...
Warren E. Pickett
wiley   +1 more source

Ionic Liquid‐Enhanced Solvent‐Based Fractional Crystallization for Separation of Fatty Acids From Tallow fat—A Modelling Approach

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT In industrial practice, fats and oils that contain triglycerides when subjected to high‐temperature and high‐pressure aqueous hydrolysis, yield sweet water as the bottom product and fatty acid mixtures as the top product in a separating column.
K. ShyamSundar, M. Helen Kalavathy, Rames C. Panda   +2 more
wiley   +1 more source

Modeling Acoustic Attenuation, Sound Velocity and Wave Propagation in Lithium‐Ion Batteries via a Transfer Matrix

Batteries &Supercaps, Volume 8, Issue 3, March 2025.
“A simple 1D transfer matrix model of a battery is introduced and parametrized using harvested individual cell components at 0 % and 100 % SoC. This model allows for the calculation of group velocity and attenuation. The results of the model show good agreement with measured values, highlighting increased attenuation and group velocity at the ...
Simon Feiler, Lukas Gold, Sarah Hartmann, Guinevere A. Giffin   +3 more
wiley   +1 more source

Generative Deep Learning for Advanced Battery Materials

Batteries &Supercaps, EarlyView.
This review explores the role of generative deep learning (DL) in battery materials analysis and highlights the fundamental principles of generative DL and its applications in designing battery materials. The importance of using multimodal data is underscored to effectively address the challenges faced during the development of battery materials across
Deepalaxmi Rajagopal, Adrian Cierpka, Britta Nestler, Arnd Koeppe   +3 more
wiley   +1 more source

Adaptive Algal Cultivation Enabled by a Monthly Biomass Forecasting System

Biotechnology and Bioengineering, EarlyView.
The developed monthly algal forecasting system used to predict biomass production for two algal strains (A and B) at two pond water depths (low and high). The highest predicted production, achieved with strain A at a low pond water depth, is selected as the cultivation strategy to guide the next month's algal growth.
Hongxiang Yan, Song Gao, Mark S. Wigmosta, Andre M. Coleman, Ning Sun, Michael H. Huesemann   +5 more
wiley   +1 more source

Artificial intelligence‐assisted design, synthesis and analysis of smart biomaterials

BMEMat, EarlyView.
Smart biomaterials are rapidly emerging as tools for tissue engineering, and artificial intelligence has played essential roles in biomaterial studies. By bridging the literature gap in AI‐based design, synthesis and analysis of smart biomaterials, the current review shares perspectives on how biomaterial scientists can practically incorporate AI for ...
Pengfei Jiang, Yefei Dai, Yujun Hou, Joshua Stein, Shichen Steven Lin, Chaochen Zhou, Yannan Hou, Rongrong Zhu, Ki‐Bum Lee, Letao Yang   +9 more
wiley   +1 more source

Integrating Life Cycle Assessment, Monetised Externalities and Value Alignment for Strategic Reconfiguration of Circular Business Models: The Case of Smartphones

Business Strategy and the Environment, EarlyView.
ABSTRACT The smartphone industry faces sustainability challenges from greenhouse gas emissions and resource depletion to growing e‐waste volumes. Circular business models have been proposed as a pathway to address these issues, yet their adoption remains limited, lacking integrative assessment frameworks that connect environmental performance with ...
Philipp Rittershaus, Venkat Aryan, David Sánchez, Manfred Renner, Jens Poeppelbuss   +4 more
wiley   +1 more source

Artificial intelligence and machine learning‐assisted digital applications for biopharmaceutical manufacturing

Biotechnology Progress, EarlyView.
Abstract Artificial intelligence and automation are no longer just buzzwords in the biopharmaceutical industry. The manufacturing of a class of biologics, comprising monoclonal antibodies, cell therapies, and gene therapies, is far more complex than that of traditional small molecule drugs.
Shyam Panjwani, Hao Wei, John Mason
wiley   +1 more source

Development of a Novel Aedes aegypti Repellent: An Integrated Approach Combining In Silico and Bioassays

Chemistry &Biodiversity, EarlyView.
OBP1 plays an essential role in the behavior response of Aedes aegypti. The computational approaches employed herein suggest a compound with repellency activity in the ZINC database, which was confirmed by bioassays. ABSTRACT Aedes aegypti is the most important vector of arboviruses, which are responsible for 3.9 billion cases worldwide.
Moysés Fagundes de Araujo Neto, Jânio Rodrigo de Jesus Santos, Ana Luiza Pontes Silva de Oliveira, Antonio Wanderson Vieira Gois, Ingrid Bernardes Santana Martins, Vitor Barbanti Pereira Leite, Adriano Figueiredo Monte Alegre, Jairo Torres Magalhães Junior, Franco Henrique Andrade Leite   +8 more
wiley   +1 more source

Engineering Catalysts at the Multiscale: Past, Present, and Future of Catalyst Manufacturing and Shaping Processes

ChemCatChem, EarlyView.
The image illustrates the journey of catalyst engineering across scales, emphasizing the design, shaping, and manufacturing of technical catalysts. It highlights how hierarchical structuring bridges properties and process innovation, showcasing the continuum between fundamental science and industrial practice that defines modern catalyst engineering ...
Ali M. Alkadhem, Eduardo Perez‐Botella, Swantje Pietsch‐Braune, Hend Omar Mohamed, Carlos A. Grande, Stefan Heinrich, Pedro Castaño   +6 more
wiley   +1 more source