Results 191 to 200 of about 3,904,649 (388)

Chronic Disease Monitoring Using Advanced Compliant Materials for Bioelectronics

open access: yesAdvanced Electronic Materials, EarlyView.
Compliant bioelectronic systems enable continuous monitoring of chronic disease through soft, stretchable materials and tissue‐conformal designs that support stable electrophysiological, mechanical, and biochemical sensing. Integration of diverse sensing modalities with thoughtful material selection, device architectures, and advanced fabrication ...
Han Kim   +7 more
wiley   +1 more source

Pilot-scale testing of natural gas pipeline monitoring based on phase-OTDR and enhanced scatter optical fiber cable. [PDF]

open access: yesSci Rep, 2023
Lalam N   +7 more
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

open access: yesAdvanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen   +4 more
wiley   +1 more source

Peculiarities of Fatigue Crack Growth in Steel 17H1S after Long-Term Operations on a Gas Pipeline. [PDF]

open access: yesMaterials (Basel), 2023
Vira V   +7 more
europepmc   +1 more source

Strategic Investment in International Gas-Transport Systems: A Dynamic Analysis of the Hold-up Problem [PDF]

open access: yes
We develop a dynamic model of strategic investment in a transnational pipeline system. In the absence of international contract enforcement, countries may distort investment in order to increase their bargaining power, resulting in overinvestment in ...
Franz Hubert, Irina Suleymanova
core  

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

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