Results 191 to 200 of about 3,388 (272)

Topological Materials and Related Applications

Advanced Electronic Materials, EarlyView.
This review covers topological materials—including topological insulators, quantum valley Hall and quantum spin Hall insulators, and topological Weyl and Dirac semimetals—as well as their most recent advancements in fields such as spintronics, electronics, photonics, thermoelectrics, and catalysis.
Carlo Grazianetti, Roberto Mantovan, Emanuele Longo, Harold J. W. Zandvliet, Pantelis Bampoulis, Yu Pan, Fan Li, Xia Wang, Payton Downey, Alessandro Molle   +9 more
wiley   +1 more source

Wilson Loop as a Tool to Investigate Chirality-Induced Spin Selectivity: Role of Vibrations and Multiple Channels. [PDF]

J Phys Chem Lett
Celada L, Huu DKAP, Chiesa A, Santini P, Griguolo L, Carretta S.   +5 more
europepmc   +1 more source

Towards Real‐Time Monitoring of Soft Robotic Systems in Endoscopic Application With Ultra‐Flexible Organic Transistor‐Based Strain Sensors

Advanced Electronic Materials, EarlyView.
The integration of ultra‐flexible, all‐organic, field‐effect transistor‐based strain sensors to soft structures is reported for the development of sensorized soft robots. The envisaged application is the development of next‐generation, controllable, and observable soft robotic catheters for endoscopic applications, such as drug delivery. Mechanical and
Usama Mahmood, Andrea Bartolucci, Giulia Casula, Antonello Mascia, Lorenzo Vannozzi, Stefano Lai   +5 more
wiley   +1 more source

Scalable Implementation of Mean-Field and Correlation Methods Based on Lie-Algebraic Similarity Transformation of Spin Hamiltonians in the Jordan-Wigner Representation. [PDF]

J Chem Theory Comput
Ghassemi Tabrizi S, Henderson TM, Kühne TD, Scuseria GE.   +3 more
europepmc   +1 more source

Printed Flexible WO3‐Based Supercapacitors for Powering Low‐Powered Electronics in Wearable Devices and Energy Autonomous Temperature Monitoring

Advanced Electronic Materials, EarlyView.
This study represents one of the systematic demonstrations of a screen‐printed, flexible WO3‐based supercapacitor, exhibiting excellent charge‐storage performance for powering wearable electronics. The device shows a specific capacitance of 3.44 F g−1 and an energy density of 0.302 Wh kg−1 at 0.05 mA, which enable to operate multiple wearable ...
Jithin Kanathedath, Adarsh Sivan Pillai, Febin Paul, Prasutha Rani Markapudi, Nazmi Sellami, Firdaus Muhammad‐Sukki, Libu Manjakkal   +6 more
wiley   +1 more source

Cyclo-Graphyne: A Highly Porous and Semimetallic 2D Carbon Allotrope with Dirac Cones. [PDF]

ACS Omega
de Lima J, Woellner CF.
europepmc   +1 more source

Machine Learning‐Assisted Design and Performance Prediction of a Compact Dual‐Band Polarization‐Insensitive THz Metamaterial Absorber for Skin‐Cancer‐Related Refractive‐Index Sensing

Advanced Electronic Materials, EarlyView.
A compact QASRR‐based THz metamaterial absorber enables polarization‐insensitive dual‐band absorption and skin‐cancer‐related refractive‐index sensing through measurable resonance shifts. Field, surface‐current, and circuit analyses clarify the dual‐resonance mechanism, while StackNet‐assisted prediction accurately estimates the simulated absorption ...
Md. Murad Kabir Nipun, S. M. Rifatur Rana, Md. Golam Morshed, Imrose Jahan, F. A. Sabbir Ahamed, Md. Jahedul Islam   +5 more
wiley   +1 more source

Proton-driven many-body interactions and structural organization in He _<i>n</i> H⁺ clusters. [PDF]

RSC Adv
Montes de Oca-Estévez MJ, Hernández-Rojas J, Prosmiti R.   +2 more
europepmc   +1 more source

Sulfide‐Based Electrolytes for All‐Solid‐State Sodium Batteries

Advanced Energy Materials, EarlyView.
This review covers the structural features and synthesis strategies of sulfide‐based solid electrolytes, as well as critical challenges related to conductivity, interfacial and moisture stability, and scaling‐up for practical application in Sodium‐based All Solid‐State Batteries.
Han Yang, Luca Weckelmann, Baolin Wu, Chih‐Long Tsai, Luc Raijmakers, Rüdiger‐A. Eichel, Anna Windmüller   +6 more
wiley   +1 more source

Machine learning approach for prediction of TBM performance and risk of jamming in Himalayan geology using a cross-project tunnelling database. [PDF]

Sci Rep
Katuwal TB, Panthi KK, Basnet CB.
europepmc   +1 more source