Results 221 to 230 of about 378,747 (352)

Cell‐Delivering Injectable Hydrogels with Tunable Microporous Structures Improve Therapeutic Efficacy for Volumetric Muscle Loss

Advanced Functional Materials, EarlyView.
The study presents an injectable hydrogel with tunable microporosity to improve mesenchymal stem cell delivery for volumetric muscle loss treatment. Mesenchymal stem cells encapsulated in porous hydrogels significantly promote the spreading, proliferation, and cytokine secretion of mesenchymal stem cells.
Hana Yasue, Tetsushi Taguchi, Taka‐Aki Asoh, Akihiro Nishiguchi   +3 more
wiley   +1 more source

Characterising Through-Thickness Shear Anisotropy Using the Double-Bridge Shear Test and Finite Element Model Updating. [PDF]

Materials (Basel)
Starman B, Chen B, Maček A, Zhang Y, Halilovič M, Coppieters S.   +5 more
europepmc   +1 more source

Printing Nacre‐Mimetic MXene‐Based E‐Textile Devices for Sensing and Breathing‐Pattern Recognition Using Machine Learning

Advanced Functional Materials, EarlyView.
This study presents a Ti3C2Tx MXene/WPU nacre‐mimetic nanomaterial as a printable ink for direct‐write printing onto textiles‐based sensors. The resulting wearable device demonstrates high sensitivity, biocompatibility, and mechanical strength. Furthermore, NFC‐enabled humidity sensor produces time‐series data, which informs a machine learning ...
Lulu Xu, Wenqing Chen, Qian Li, Rohit Gupta, Biswajoy Bagchi, Laurence B. Lovat, Manish K. Tiwari   +6 more
wiley   +1 more source

Experimental study on rheological properties of serrate discontinuity under stepwise loading. [PDF]

Sci Rep
Tian GH, Mei BQ, Zhang QZ, Hao YX, Zhu YZ, Jiu YZ.   +5 more
europepmc   +1 more source

Engineering Topographical Cues to Enhance Neural Regeneration in Spinal Cord Injury: Overcoming Challenges and Advancing Therapies

Advanced Functional Materials, EarlyView.
Spinal cord injury (SCI) poses significant challenges for regeneration due to a series of secondary injury mechanisms. How to use biomaterial approach to target the failed regeneration after SCI remains a critical challenge. This review systematically evaluates current strategies to optimize biomaterial topographies for neurite outgrowth, axonal ...
Wei Xu, Fenghui Wang, Joshua Stein, Siqiao Wang, Pengfei Jiang, Letao Yang, Liming Cheng, Ki‐Bum Lee   +7 more
wiley   +1 more source

Experimental study of shear strength and CBR improvement of silty clay soil reinforced with waste tires. [PDF]

Sci Rep
Bezih K, Djenane M, Laouche M, Hebbache K.   +3 more
europepmc   +1 more source

Artificial Intelligence‐Driven Development in Rechargeable Battery Materials: Progress, Challenges, and Future Perspectives

Advanced Functional Materials, EarlyView.
AI is transforming the research paradigm of battery materials and reshaping the entire landscape of battery technology. This comprehensive review summarizes the cutting‐edge applications of AI in the advancement of battery materials, underscores the critical challenges faced in harnessing the full potential of AI, and proposes strategic guidance for ...
Qingyun Hu, Junyuan Lu, Jian Hui, Ziyuan Rao, Yang Ren, Hong Wang   +5 more
wiley   +1 more source

The Cementation Mechanisms and Mechanical Properties of Different Soil-Rock Mixtures-Slurry Cements. [PDF]

Materials (Basel)
Li J, Zhong Z, Zou H.
europepmc   +1 more source

Cu2O/Cu Chiral Catalysts for Highly Selective Solar‐Assisted CO2‐to‐CO Electroreduction

Advanced Functional Materials, EarlyView.
To address the poor target‐product selectivity of the eCO2RR, breakthrough approaches based on the chiral‐induced spin selectivity phenomenon enhance the Faradaic efficiency (FE) for target hydrocarbons, such as CO. To induce this spin polarization strategy in Cu2O/Cu catalysts, it is proposed using amine‐based intermediate organic molecules with ...
Hyungsoo Lee, Young Sun Park, Eunji Kwon, Chang‐Seop Jeong, Juwon Yun, Subin Moon, Soobin Lee, Jun Hwan Kim, Donghyun Kim, Wooyong Jeong, Jaehyun Son, Jihwon Park, Seungho Yu, Jooho Moon   +13 more
wiley   +1 more source

Advanced hybrid machine learning models with explainable AI for predicting residual friction angle in clay soils. [PDF]

Sci Rep
Ankah MLY, Adjei-Yeboah S, Ziggah YY, Asare EN.   +3 more
europepmc   +1 more source