Results 171 to 180 of about 97,140 (256)

Machine Learning Accelerated Computational Design of Bio‐Inspired Catalysts in the Nitrogen Reduction Reaction

Advanced Materials, EarlyView.
We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano, Zihan You, Haoran Chen, Qifan Zhong, Rong‐Zhen Liao, Shaoqi Zhan   +5 more
wiley   +1 more source

Modeling the distribution of soil organic carbon in salt marshes dominated by various plant species along Egypt's Delta coast. [PDF]

BMC Plant Biol
Eid EM, Shahawy AA, Al-Sodany YM, El-Khalafy MM.   +3 more
europepmc   +1 more source

Deep Learning Inverse Design of Phase‐Change Reconfigurable Terahertz Metadevices for Multidimensional Secure Communication

Advanced Materials, EarlyView.
A deep learning inverse‐design framework is established to create versatile reconfigurable terahertz metadevices. By synergizing deep learning with phase‐change materials, this approach enables on‐demand customization of multidimensional electromagnetic responses.
Yisheng Dong, Xieyu Chen, Aarthy Nagarajan, Yi Yang, Zhihao Wang, Rui Yu, Chuang Zheng, Chunmei Ouyang, Xueqian Zhang, Tun Cao, Ranjan Singh, Zhen Tian   +11 more
wiley   +1 more source

Quasi-Power Law Ensembles: Nonextensive Statistics or Superstatistics. [PDF]

Entropy (Basel)
Rybczyński M, Wilk G, Włodarczyk Z.
europepmc   +1 more source

Oppositely Charged Single Enzyme Nanogels Form Versatile Coacervates for Efficient Enzyme Cascade Catalysis

Advanced Materials, EarlyView.
Oppositely charged single enzyme nanogels (SENs) phase‐separate into bi‐enzymatic coacervate microdroplets, acting as both scaffold and functional units. By tuning SEN ratios, these coacervates create specific microenvironments that enable selective small‐molecule enrichment and efficient intermediate diffusion.
Andoni Rodriguez‐Abetxuko, Nadia A. Erkamp, Neshat Moslehi, Yannick H. A. Leurs, Lars Paffen, Işil Yeşil Gür, Jana Stojanović, Hugo Brasselet, Laura van der Weel, Ulf Hanefeld, Ilja K. Voets, Jan C. M. van Hest   +11 more
wiley   +1 more source

A new family of alpha power-G using cosine function with applications and regression modeling. [PDF]

Sci Rep
Alghamdi AS, ALoufi SF.
europepmc   +1 more source

Ferroelectric Dynamic‐Field‐Driven Nucleation and Growth Model for Predictive Materials‐To‐Circuit Co‐Design

Advanced Materials, EarlyView.
This study presents a compact dynamic‐field‐driven nucleation and growth (DFNG) model that captures ferroelectric switching behavior under arbitrary voltage waveforms. It enables extraction of time‐dependent domain wall velocity and growth dimensionality, which can then be extended to device‐level modeling.
Yi Liang, Soohyeon Kim, Tony Chiang, Megan K. Lenox, Ian Mercer, John J. Plombon, Jon‐Paul Maria, Jon F. Ihlefeld, Wenhao Sun, Wei Lu, John T. Heron   +10 more
wiley   +1 more source

Real-Time Transient Voltage and Frequency Sensing Strategy for Resilience Enhancement of PV-Storage Systems in Weak Grids. [PDF]

Sensors (Basel)
Ji Y, Liu Z, Gu X, Huo C, Zhang Z, Tang S, Mei J, Huang C.   +7 more
europepmc   +1 more source

E. coli Extracellular Matrix: A Tunable Composite With Hierarchical Structure

Advanced Materials, EarlyView.
The complex composite‐like mechanical behavior of E. coli biofilm matrix is the result of a synergic contribution of the rigid curli and swelling pEtN‐cellulose, and emerges from specific ratio and assembly conditions. The interactions between the two fibers govern biofilm hydration and characteristic wrinkling patterns, providing crucial insights for ...
Macarena Siri, Agustín Mangiarotti, Anne Seewald, Nikolai Rosenthal, Shahrouz Amini, Emeline Raguin, Peter Fratzl, Cécile M. Bidan   +7 more
wiley   +1 more source

Tracking Performance Limits Using Multi-Timescale Maximal Mean Power Ratios. [PDF]

Eur J Sport Sci
Zignoli A, Giorgi A, Kolodziej F, Martinez-Gonzalez B, Leo P, Laursen PB.   +5 more
europepmc   +1 more source