Results 161 to 170 of about 14,978 (262)

Separating Hydrogen Evolution From Electroplating in Zn Metal Batteries Using Scanning Electrochemical Microscopy

Advanced Energy Materials, EarlyView.
Operando SECM decouples hydrogen evolution from other degradation pathways in Zn metal batteries by quantifying its contribution during Zn electrodeposition. Although HER is shown to account for only a minor fraction of the irreversible charge loss, it remains a key indicator of interfacial evolution and by‐product formation governing cycling ...
J. T. Simon, Anna B. Gunnarsdóttir, Esther Lilian Gray, Debashis Tripathy, Farheen N Sayed, Manish Chhowalla, Stuart M. Clarke, Clare P. Grey, Svetlana Menkin   +8 more
wiley   +1 more source

Ruthenium Speciation during Acidification of Alkaline Solution. [PDF]

ACS Omega
Leblanc M, Baghdadi S, Martin PM, Prieur D, Quemet A, Aupiais J.   +5 more
europepmc   +1 more source

Electric Double Layer Engineering Induces O‐Down Interfacial Water Reorientation for Efficient and Long‐Term Seawater Electrolysis

Advanced Energy Materials, EarlyView.
The additive EDTMPS inhibits hydroxides deposition by chelating with Ca2+/Mg2+. It also disrupts the hydrogen bond network of interfacial water and expands the thickness of electric double layer, promoting more free water to flip into adsorbable O‐down configuration.
Tongzhou Li, Yutong Zhao, Hongjie Zhang, Yangkai Han, Zhiwei Ren, Feng Xie, Zongping Shao, Zhigang Shao   +7 more
wiley   +1 more source

Effect of Pressure-Assisted Heat Treatment on the Crystalline Phase of Titanium Dioxide, Niobium Pentoxide, and Ruthenium-Modified Oxides. [PDF]

ACS Omega
Pires PB, Fuziki MEK, Lenzi GG, Sabino SDRF, Novatski A, Tebcherani SM, Dias DT.   +6 more
europepmc   +1 more source

FastCat: Autonomous Discovery of Multielement Layered Double Hydroxide Alloy Catalysts for Alkaline Oxygen Evolution Reaction

Advanced Intelligent Discovery, EarlyView.
A machine learning‐guided self‐driving laboratory screened over 500 nickel‐based layered double‐hydroxide catalysts for alkaline oxygen evolution. Out of the eight metals, the robot uncovered a quaternary Ni–Fe–Cr–Co catalysts requiring only 231 mV overpotential to reach 20 mA cm−2.
Nis Fisker‐Bødker, Enzo Raffaele Moretti, Jin Hyun Chang, Tejs Vegge   +3 more
wiley   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

Reclaiming Ruthenium: A Comprehensive Review of Hydrometallurgical Strategies for Precious Metal Recovery. [PDF]

Materials (Basel)
Rudnik E.
europepmc   +1 more source

Machine Learning‐Assisted Second‐Order Perturbation Theory for Chemical Potential Correction Toward Hubbard U Determination

Advanced Intelligent Discovery, EarlyView.
In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun, Tong Wu, Baian Chen, Zikang Li, Qiuyang Lu, Lu Lu, Hon Ho Wong, Cheuk Hei Chan, Bolong Huang   +8 more
wiley   +1 more source

Multifaceted Applications of Ruthenocene and Its Derivatives in Biomedicine, Energy Storage and Electrochemical Sensing. [PDF]

Biosensors (Basel)
Shahid A, Sabahat S, Naeem A.
europepmc   +1 more source

A Memristor‐Based In‐Memory Computing System‐on‐Chip with Efficient Depthwise Convolution

Advanced Intelligent Systems, EarlyView.
We present a memristor‐based in‐memory computing (IMC) architecture that enables efficient depthwise convolution (DWC) acceleration. Fabricated in a system‐on‐chip with crossbar arrays, the design improves memory utilization. Experimental validation demonstrates the first hardware acceleration of DWC in IMC, achieving a digital comparable inference ...
Wenhao Song, Fuxi Cai, Sangsu Park, Zhaoyan Li, Seonghun Lee, Mingyi Rao, Woohyung Choi, Seungin Shin, Yan Zhu, Sujin Chae, Myoungsub Kim, Mingche Wu, Hyejung Choi, Yuan Dao, Jaeyun Yi, Youngman Cho, Seon Yong Cha, Ning Ge, Qiangfei Xia, Soo Gil Kim, Miao Hu, J. Joshua Yang   +21 more
wiley   +1 more source