Results 121 to 130 of about 43,872 (219)

Identifying key influencing factors and their hierarchical structure for green supply chain management in China's aerospace manufacturing using DEMATEL-ISM. [PDF]

Sci Rep
Zheng J, Li X, Wang F, Wang C, Chen Y.
europepmc   +1 more source

Disorder‐Induced Extremely Low Thermal Conductivity of Graphite Fluoride

Advanced Science, EarlyView.
This article investigates the effect of fluorination on the thermal conductivity of graphite fluoride, demonstrating the relationship between structural modification and thermal conductivity in an extreme case. The record‐low through‐plane thermal conductivity measured in exfoliated graphite fluoride flakes was found to correlate with the wide ...
Wonsik Lee, Donghoon Moon, Ziyan Qian, Jinwoo Kim, Changheon Kim, Yeojin Lee, Hyobin Yoo, Richard B. Wilson, Qiye Zheng, Gwan‐Hyoung Lee, Hyejin Jang   +10 more
wiley   +1 more source

Lightweight Structural Design of UAM Fuselage Using AI Predictive Modeling and Composite Big Data from Automated Manufacturing. [PDF]

Materials (Basel)
Son WH, Kim JH, Bae SY.
europepmc   +1 more source

Microscale Mapping of Fiber Strain and Damage in Composite Wrinkled Laminates Using Computed Tomography Assisted Wide‐Angle X‐Ray Scattering

Advanced Science, EarlyView.
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong, James Trevarthen, Igor Dolbnya, Wadwan Singhapong, Nicholas Pilato, Richard Butler, Jiraphant Srisuriyachot, Alexander J. G. Lunt   +7 more
wiley   +1 more source

Interfaces and Transport Phenomena in Materials Under Extreme Conditions. [PDF]

Materials (Basel)
Chen Y, Hu R, Wang H.
europepmc   +1 more source

Wavy‐Interlocked Stretchable Triboelectric Nanogenerators Enhanced by Liquid Metal Microflowers for Self‐Powered Wearable Motion Monitoring

Advanced Science, EarlyView.
Schematic showing a stretchable triboelectric nanogenerator based on interlocked wavy architectures that uses EGaIn microflower‐embedded PVDF‐TrFE and Nylon‐6 nanofiber membranes. The multi‐petaled, electron‐rich EGaIn microflowers enhance interfacial polarization and capacitance, while the interlocked wavy architecture enlarges the effective contact ...
Qianqian Xu, Huimin Li, Hanmin Zeng, Yahui Meng, Yimeng He, Xinke Hu, Senfeng Zhao, Jianxun Zhang, Peiqiong Zhou, Kechao Zhou, Dou Zhang, Chris Bowen, Yan Zhang   +12 more
wiley   +1 more source

Boosting capacitive energy storage in relaxor ferroelectrics through polymorphic phase engineering. [PDF]

Sci Adv
Zhang Y, Liang H, Liu Y, Li D, Dong S, Wang J, Li W, Nan CW.   +7 more
europepmc   +1 more source

Atomic Defects in Layered Transition Metal Dichalcogenides for Sustainable Energy Storage and the Intelligent Trends in Data Analytics

Advanced Science, EarlyView.
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo, Ying Yang, Zizhen Fu, Fengqi Liu, Susu Fang, Kele Xu, Shanshan Wang   +6 more
wiley   +1 more source

Preliminary Assessment of Thermal and Mechanical Properties of a Graphene-Rich Carbon Coating on 3003-H14 Aluminum Alloy for Potential Anti-Icing Applications. [PDF]

Materials (Basel)
Almomani A, Alkhasawneh M, Almomani MA, Bani-Hani MA.   +3 more
europepmc   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source