Results 191 to 200 of about 6,618 (297)

TiAu Based High Temperature Shape Memory Alloys

TiAu Based High Temperature Shape Memory Alloys
identifier:oai:t2r2.star.titech.ac.jp ...
openaire  

Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities

Advanced Materials, EarlyView.
This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen, Zhanxi Fan, Jingjie Ge, Qiyuan He, Zhuangchai Lai, Jiawei Liu, Chaoliang Tan, Hua Zhang   +7 more
wiley   +1 more source

Giant Orbital Rashba–Edelstein Effect in Crystalline Cu2O/Cu Heterostructures

Advanced Materials, EarlyView.
An enhanced orbital Rashba–Edelstein effect is demonstrated in a crystalline Cu2O/Cu heterostructure, compared to naturally oxidized CuOx structures, highlighting the critical role of crystallinity and interface control in orbital torque generation. The resulting spin torque conductivity exceeds that of Pt, indicating the potential of orbital torque ...
San Ko, Jaimin Kang, Su Jae Kim, Hanhwi Jang, Do‐Kyeong Nam, Minseok Kang, Sunghoon Kim, Yeon Sik Jung, Se‐Young Jeong, Kab‐Jin Kim, Byong‐Guk Park   +10 more
wiley   +1 more source

Oxidation Kinetics of a NiPtTi High Temperature Shape Memory Alloy

, 2007
A high temperature shape memory alloy (HTSMA), Ni30Pt50Ti, with an M(sub s) near 600 C, was isothermally oxidized in air for 100 hr over the temperature range of 500 to 900 C. Parabolic kinetics were confirmed by log-log and parabolic plots and showed no
Noebe, Ronald D., Humphrey, Donald L., Smialek, James L.   +2 more
core  

Phase transformation and creep behavior in Ti 50 Pd 30 Ni 20 high temperature shape memory alloy in compression [PDF]

, 2010
Parikshith K. Kumar, Uri Desai, James A. Monroe, Dimitris C. Lagoudas, İbrahim Karaman, R.D. Noebe, Glenn Bigelow   +6 more
openalex   +1 more source

Low-Temperature Rolling Induces High-Strength Quasi-Linear Superelasticity Over a Wide Temperature Range in Tini Shape Memory Alloys

, 2023
Shuangshuang Zhao, Qianglong Liang, Yunting Su, Tianjiao Dong, Dong Wang   +4 more
openalex   +1 more source

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung, Jiaxiang Yi, Hieu Nguyen‐Duc, Tien Nu Hoang Lo, Weili Zhao, Chaoqun Dong, Fabien Sorin, Baris Caglar, Lei Wei, Tung Nguyen‐Dang   +9 more
wiley   +1 more source

Precipitation-Strengthened, High-Temperature, High-Force Shape Memory Alloys

, 2008
Shape memory alloys (SMAs) are an enabling component in the development of compact, lightweight, durable, high-force actuation systems particularly for use where hydraulics or electrical motors are not practical.
Nathal, Michael V., Crombie, Edwin A., Noebe, Ronald D., Draper, Susan L.   +3 more
core  

Designable van der Waals Crystal for Artificial Neuronal Cell Mimicking

Advanced Materials, EarlyView.
Designable van der Waals crystal has been demonstrated for device‐scale neuronal cell mimicking. The structural similarity between ion‐channel in biological membranes and layered vdW lattices is realized with nano‐crystallization via Ar + H2S plasma sulfurization.
Jinhyoung Lee, Gunhyoung Kim, Dongho Lee, Seowoo Son, Hyunho Seok, Sihoon Son, Hyunbin Choi, Geonwook Kim, Geumji Back, Hyunkyu Kim, Chaerin Park, Junmin Ahn, Seongyun Je, Chaeyoung Im, Junil Cho, Magdalena Grzeszczyk, Seongho Kim, Eunseo Go, Hyunwoo Shim, Donghwan Choi, Muyoung Kim, Hyoeng‐U. Kim, Won‐Jun Jang, Taesung Kim   +23 more
wiley   +1 more source

Ferroelectric Dynamic‐Field‐Driven Nucleation and Growth Model for Predictive Materials‐To‐Circuit Co‐Design

Advanced Materials, EarlyView.
This study presents a compact dynamic‐field‐driven nucleation and growth (DFNG) model that captures ferroelectric switching behavior under arbitrary voltage waveforms. It enables extraction of time‐dependent domain wall velocity and growth dimensionality, which can then be extended to device‐level modeling.
Yi Liang, Soohyeon Kim, Tony Chiang, Megan K. Lenox, Ian Mercer, John J. Plombon, Jon‐Paul Maria, Jon F. Ihlefeld, Wenhao Sun, Wei Lu, John T. Heron   +10 more
wiley   +1 more source