Results 181 to 190 of about 4,252,197 (332)

Shape‐Determined Kinetic Pathways in 2D Solid–Solid Phase Transitions

Advanced Science, EarlyView.
By simulating 2D ball‐stick pentagon, hexagon, and octagon systems, the kinetics of solid–solid phase transition is investigated, which is characterized by the loss of body‐orientation order. During which, the local defects of body‐orientation self‐organize into three different patterns, originated from the shape‐determined kinetic pathways, which may ...
Ruijian Zhu, Yi Peng, Yanting Wang
wiley   +1 more source

From Pores to Pavement: Advanced Modeling of Aluminosilicates for Scalable Carbon Capture in Concrete

Advanced Science, EarlyView.
This study presents a transferable modeling framework for carbon capture using aluminosilicates, integrating Universal Isotherm Modeling with experimental data. It reveals how ultramicropores, alumina content, and amine functionalization influence CO2 adsorption energetics.
Pooja Anil Kumar Nair, Jéssica de O. N. Ribeiro, Murilo Daniel de Mello Innocentini, Kevin Paine, Juliana Calabria‐Holley   +4 more
wiley   +1 more source

Investigation of Cement‐Emulsified Asphalt in Plastic Concrete [PDF]

, 2018
Xiaohu Yan, Zaiqin Wang, Meijuan Rao, Mingxia Li   +3 more
openalex   +1 more source

Life‐Cycle Assessment of Printed Electronic Components ‐ Case Study for Organic Electrochemical Transistors

Advanced Electronic Materials, EarlyView.
This tutorial introduces a practical framework for implementing early‐stage Life‐Cycle Assessment (LCA) in flexible and printed electronics. Using organic electrochemical transistors (OECTs) as a case study, the modular Process‐of‐Record and open‐access inventory provides a rich resource adaptable to a plethora of technologies in printed electronics ...
Laura Teuerle, Tommy Meier, Klara Hänisch, Finn Jaekel, Yeohoon Yoon, Andreas Wendel, Hans Kleemann   +6 more
wiley   +1 more source

Mechanical, microstructure, durability, and economic assessment of nano titanium dioxide integrated concrete. [PDF]

Sci Rep
Rahman I, Paruthi S, Dev N, Arif M, Khan AH, Hasan MA, Prasad CVSR, Alyaseen A.   +7 more
europepmc   +1 more source

Impact of Trap Depth on the Steady‐State and Transient Photoluminescence in Halide Perovskite Films

Advanced Energy Materials, EarlyView.
The presence of shallow traps in halide perovskites is frequently postulated by density functional theory calculations. This review studies the implications of recombination‐active shallow traps on steady‐state and transient recombination kinetics. How to identify shallow traps and how the depth of the traps and their density are reflected in different
Jürgen Hüpkes, Uwe Rau, Thomas Kirchartz   +2 more
wiley   +1 more source

Research on mechanical properties and prediction methods of hybrid fiber concrete for airport pavements. [PDF]

PLoS One
Xu W, Zang Z, Liu X, Ji Y, Xu J, Li H.
europepmc   +1 more source

Process Parameter Specification and Control in Solution Processing of Hybrid Perovskite Photovoltaics: From Domain‐Specific Jargon to Evidence‐Based, Unambiguous Description of Experimental Workflows

Advanced Energy Materials, EarlyView.
Hybrid perovskite solar cells are nearing commercial mass production. Therefore, academic research must tackle the remaining barriers for their large‐scale rollout. One of these is consistent manufacturing yield. Here, evidence is reviewed for the impact of process paramters on perovskite solution processes, finding a great potential for better ...
Simon Ternes, Christoph J. Brabec, Luigi A. Castriotta, Thomas Exlager, Karen Forberich, Alessio Gagliardi, Michael Götte, Florian Mathies, Sinclair Ryley Ratnasingham, Lennart K. Reb, Eva Unger, Aldo Di Carlo   +11 more
wiley   +1 more source

EFFECT OF LOADING STAGE ON PEAT COMPRESSION AND DEFLECTION OF BAMBOO GRID WITH CONCRETE PILE

, 2020
Aazokhi Waruwu
openalex   +1 more source

Machine Learning for Accelerating Energy Materials Discovery: Bridging Quantum Accuracy with Computational Efficiency

Advanced Energy Materials, EarlyView.
This perspective highlights how machine learning accelerates sustainable energy materials discovery by integrating quantum‐accurate interatomic potentials with property prediction frameworks. The evolution from statistical methods to physics‐informed neural networks is examined, showcasing applications across batteries, catalysts, and photovoltaics ...
Kwang S. Kim
wiley   +1 more source