Fiber‐Format Flexible Linear Electrostatic Motors
A flexible coaxial fibre‐format electrostatic motor enables backdrivable and reversible linear actuation with high force density and functionality under bending, offering a scalable actuation platform for soft and wearable robotics. ABSTRACT Linear motion is fundamental to robotics, yet existing solutions are either rigid electromagnetic motors or ...
Sylvain Schaller, Herbert Shea
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Variational phase-field modeling of fracture and fatigue in shape memory alloys: a one-dimensional study. [PDF]
Brambilla A, De Lorenzis L, Petrini L.
europepmc +1 more source
Equivalent Heat Treatments and Mechanical Properties in Cold-Rolled TiNiFe Shape-Memory Alloys. [PDF]
Liu S, Hui S, Li Y, Song X, Yu Y, Ye W.
europepmc +1 more source
Giant Anisotropic Spin Absorption in Chiral Hybrid Semiconductors
Researchers uncover that chiral hybrid organic–inorganic semiconductors absorb spin differently depending on its polarization direction. This anisotropic spin absorption is primarily driven by the local symmetry breaking within the layered structure.
Cong Yang +12 more
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Noise-Aware Machine Learning Accelerates Development of High-Latent-Heat Cu-Al-Ni Shape Memory Alloys for Thermal Management. [PDF]
Zhou D +9 more
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Environment-Induced Degradation of Shape Memory Alloys: Role of Alloying and Nature of Environment. [PDF]
Santosh S, Harris WBJ, Srivatsan TS.
europepmc +1 more source
Spin‐crossover metal‐organic frameworks (SCO‐MOFs) provide a route to control the electronic and magnetic properties of two‐dimensional quantum materials. By integrating a layered SCO‐MOFs with graphene, CrSBr, and NbSe2 nanodevices, thermally and light induced spin transitions induce strain that reversibly modulates charge transport, magnetic memory ...
Carla Boix‐Constant +4 more
wiley +1 more source
Mechanical Response and Functional Performance of Heat-Treated LPBF NiTi Shape Memory Alloys. [PDF]
Ratajski J +6 more
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Influence of Dynamic Strain Sweep on the Degradation Behavior of FeMnSi-Ag Shape Memory Alloys. [PDF]
Roman AM +9 more
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Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng +24 more
wiley +1 more source

