Results 121 to 130 of about 174,416 (267)

Region‐to‐Region Unidirectional Connection In Vitro Brain Model for Studying Directional Propagation of Neuropathologies

Advanced Functional Materials, EarlyView.
A unidirectional cerebral organoid–organoid neural circuit is established using a microfluidic platform, enabling controlled directional propagation of electrical signals, neuroinflammatory cues, and neurodegenerative disease–related proteins between spatially separated organoids.
Kyeong Seob Hwang, Hui‐Wen Liu, Hyogeun Shin, Hyun Wook Kang, Minjin Kang, Jongbaeg Kim, Il‐Joo Cho, Nakwon Choi, Seok Chung, Hong Nam Kim   +9 more
wiley   +1 more source

Exploiting Two‐Photon Lithography, Deposition, and Processing to Realize Complex 3D Magnetic Nanostructures

Advanced Functional Materials, EarlyView.
Two‐photon lithography (TPL) enables 3D magnetic nanostructures with unmatched freedom in geometry and material choice. Advances in voxel control, deposition, and functionalization open pathways to artificial spin ices, racetracks, microrobots, and a number of additional technological applications.
Joseph Askey, Arjen van den Berg, Sandra Ruiz Gomez, Claire Donnelly, Dirk Grundler, Sam Ladak   +5 more
wiley   +1 more source

Nanomaterial‐Integrated Fiber Neural Probes for Deep Brain Monitoring and Modulation: Challenges and Opportunities

Advanced Functional Materials, EarlyView.
The article presents nanomaterial‐integrated fiber neural probes as innovative tools for deep brain molecular sensing, neural stimulation, and temperature monitoring. It examines breakthroughs in SERS‐based biomolecule detection, thermoplasmonic activation, and luminescent thermometry, alongside strategies to overcome stability, specificity, and ...
Di Zheng, Yang Li, Muhammad Fayyaz Kashif, Linda Piscopo, Massimo De Vittorio, Ferruccio Pisanello   +5 more
wiley   +1 more source

Blueprint2Code: a multi-agent pipeline for reliable code generation via blueprint planning and repair. [PDF]

Front Artif Intell
Mao K, Hu B, Lin R, Li Z, Lu G, Zhang Z.
europepmc   +1 more source

In Situ Study of Resistive Switching in a Nitride‐Based Memristive Device

Advanced Functional Materials, EarlyView.
In situ TEM biasing experiment demonstrates the volatile I‐V characteristic of MIM lamella device. In situ STEM‐EELS Ti L2/L3 ratio maps provide direct evidence of the oxygen vacancies migrations under positive/negative electrical bias, which is critical for revealing the RS mechanism for the MIM lamella device.
Di Zhang, Rohan Dhall, Matthew M. Schneider, Cun Li, Chengyu Song, Sundar Kunwar, Hongyi Dou, Natanii R. Yazzie, Henry Tran, Daniel Appuing, Jim Ciston, Nicholas G. Cucciniello, Pinku Roy, Michael T. Pettes, John Watt, Winson Kuo, Haiyan Wang, Ye Cao, Rodney J. McCabe, Aiping Chen   +19 more
wiley   +1 more source

Feedback-integrated prompt optimiser for problem formulation. [PDF]

Sci Rep
Amarasinghe PT, Nguyen S, Sun Y, Alahakoon D.   +3 more
europepmc   +1 more source

Perceived impacts of the Use of E-learning in Teaching and Learning English Language at Postgraduate Program Level: First Generation Ethiopian Public Universities in Focus

Temesgen Mereba, Tewodros Zeleke, Endalfer Melese   +2 more
openalex   +1 more source

Integrative Approaches for DNA Sequence‐Controlled Functional Materials

Advanced Functional Materials, EarlyView.
DNA is emerging as a programmable building block for functional materials with applications in biomimicry, biochemical, and mechanical information processing. The integration of simulations, experiments, and machine learning is explored as a means to bridge DNA sequences with macroscopic material properties, highlighting current advances and providing ...
Aaron Gadzekpo, Ewa Anna Oprzeska‐Zingrebe, Mariana Kozlowska, Lennart Hilbert, Iliya D. Stoev   +4 more
wiley   +1 more source

How Can Clinicians Leverage Vibe Coding for Machine Learning and Deep Learning Research? [PDF]

Endocrinol Metab (Seoul)
Lee Y, Huh S.
europepmc   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source