Results 161 to 170 of about 746,368 (310)

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

Advanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani, Surabhi Nadigotti, Erfan Fatehi, Derek Aranguren van Egmond, Behnam Ashrafi   +4 more
wiley   +1 more source

Defining the Pediatric Spinal Thoracoscopy Learning Curve

, 2000
Peter O. Newton, Kevin G. Shea, Kirk F. Granlund   +2 more
openalex   +1 more source

Active Hydrogen for Electrochemical Ammonia Synthesis

Advanced Functional Materials, EarlyView.
This review provides a comprehensive overview of the active hydrogen (H*) for electrochemical ammonia synthesis with particular attention given to the regulation of H* generation and consumption to suppress the competition of hydrogen evolution reaction and enhance the yield, selectivity, and Faradaic efficiency of ammonia.
Guoqiang Gan, Guo Hong, Wenjun Zhang
wiley   +1 more source

The learning curve of selective salpingography and tubal catheterization [PDF]

, 2002
Spyros Papaioannou, M Afnan, Alan Girling, Bolarinde Ola, Nehed Hammadieh, A Coomarasamy, Kaldoun Sharif   +6 more
openalex   +1 more source

Internal Temperature Evolution Metrology and Analytics in Li‐Ion Cells

Advanced Functional Materials, EarlyView.
This study investigates the non‐linear evolution of internal temperatures across diverse operating conditions, highlighting the disparities between internal and external measurements and the resulting thermal asymmetries. The coupled thermo‐electrochemical modeling framework provides a comprehensive analysis of various heat generation modes, examining ...
Anuththara S. J. Alujjage, Bairav S. Vishnugopi, Avijit Karmakar, David P. Magee, Yevgen Barsukov, Partha P. Mukherjee   +5 more
wiley   +1 more source

Is There a Learning Curve Associated with the Use of Remifentanil?

, 2000
Girish P. Joshi, Brenda D. Jamerson, Michael F. Roizen, Lee A. Fleisher, Rebecca S. Twersky, David S. Warner, Michael W. Colopy   +6 more
openalex   +1 more source

Biomimetic Design of Biocompatible Neural Probes for Deep Brain Signal Monitoring and Stimulation: Super Static Interface for Immune Response‐Enhanced Contact

Advanced Functional Materials, EarlyView.
Ultrathin, flexible neural probes are developed with an innovative, biomimetic design incorporating brain tissue‐compatible materials. The material system employs biomolecule‐based encapsulation agents to mitigate inflammatory responses, as demonstrated through comprehensive in vitro and in vivo studies.
Jeonghwa Jeong, Gyeonghwa Heo, Young Woo Kwon, Seon Yeong Chae, Min Jae Kim, Ki Jun Yu, Hwa Kyoung Shin, Suck Won Hong   +7 more
wiley   +1 more source

Learning curve of transanal minimally invasive surgery for rectal neoplasm. [PDF]

Front Oncol
Li X, Guo S, Yao K, Ge Z, Li Y, Hu J, Xia H.   +6 more
europepmc   +1 more source

Lessons on Learning About Learning Curves

, 2000
J. G. Reves
openalex   +1 more source

Electroplating of Wear‐ and Corrosion‐Resistant CrCoNi Medium‐Entropy Alloys beyond Hard Chromium Coatings

Advanced Functional Materials, EarlyView.
The electroplating of a CrCoNi medium‐entropy alloy is achieved using a mixture of an ionic liquid and an aqueous solution containing metal salts. The CrCoNi medium‐entropy alloy thin film exhibits high wear and corrosion resistance superior to conventional hard chromium coatings. Abstract High‐entropy alloys (HEAs) and medium‐entropy alloys (MEAs) are
Yuki Murakami, Shuhei Yoshida, Kosuke Ishii, Naoya Nishi, Akiyuki Ryoki, Nobuhiro Tsuji, Kuniaki Murase, Kazuhiro Fukami   +7 more
wiley   +1 more source