Results 121 to 130 of about 5,915,931 (293)

Spontaneous Cyclic Levitation of Glycerol‐Water Droplets at Low Pressures

Advanced Science, EarlyView.
Under low pressure, a minute glycerol addition transforms the chaotic dynamics of freezing water droplets into cyclic levitation. Freeze‐concentration preserves liquid pathways that relax expansion‐induced stress, while freezing point depression weakens asymmetric vaporization recoil.
Chen Xu, Renjie Hua, Wei Ma, Fuqiang Chu, Dong Liang, Xueshi Li, Qirui Zhang, Yuan Dong, Xuehu Ma, Xiao Yan, Shuhuai Yao   +10 more
wiley   +1 more source

Smart Bioinks for 4D Bioprinting: Requirements, Design, and Applications

Advanced Science, EarlyView.
Smart bioinks empower 4D‐bioprinted constructs to dynamically adapt and remodel in response to stimuli, effectively biomimicking native tissues. Artificial Intelligence (AI) and Machine Learning (ML) play a guiding role in their rational design by optimizing relevant properties.
Shangsi Chen, Jiahui Lai, Qiongjiao Zeng, Liangbin Zhou, Boguang Yang, Bin Zhang, Min Wang, Jiajing Zhou, Kieran Lau, Khoon S. Lim, Zhong Alan Li, Rocky S. Tuan   +11 more
wiley   +1 more source

On the polynomial degeneracy of Ricci invariants and spacetime singularity

Physics Letters B
We explore the connection of a general relativistic matter-energy momentum tensor with the polynomial degeneracies of curvature invariants defined in Riemannian geometry.
Soumya Chakrabarti
doaj   +1 more source

Q‐LEAP: Millisecond Hyperdimensional Optimization for Full‐Spectrum Optical Metamaterials

Advanced Science, EarlyView.
Q‐LEAP integrates physics‐informed residual machine learning with factorization‐machine‐encoded quantum annealing to design full‐spectrum optical metamaterials. It explores a 2108 design space and, in a single 2.56 ms annealing step, reaches 85.83% of the theoretical FoM limit, enabling selective 5‐8 µm emission with 3–5 and 8–14 µm suppression and ∼40×
Zikang Guo, Yunwen Wu, Yuhui Guo, Shenghong Ju   +3 more
wiley   +1 more source

Evolution of Physical Intelligence Across Scales

Advanced Intelligent Discovery, EarlyView.
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu, Tianyun Huang, Aming Li, Pengyu Lv, Tingting Qin, Wenhui Chen, Hui Wei, Huiling Duan   +7 more
wiley   +1 more source

Orchestrating Anion–π+ Interactions to Accelerate Metal‐Free Room‐Temperature Phosphorescence

Angewandte Chemie, EarlyView.
Tuning anion–π+ interactions in pyridinium iodide contact ion pairs enables ultrafast metal‐free room‐temperature phosphorescence (540–605 nm) with radiative rates up to 5.2×105 s−1. Strong iodide→π+ charge‐transfer coupling, enhanced spin–orbit interactions, and dynamic ion‐pair organization accelerate intersystem crossing and emission, establishing ...
Eetu Hakkarainen, Corentin Montagne, Hao‐Cheng Lin, Chen‐Yu Lin, Khai‐Nghi Truong, Po‐Yu Chen, Anton Nechaev, Fabien B. L. Cougnon, Igor O. Koshevoy, Toni Eskelinen, Hao‐Wu Lin, Pi‐Tai Chou, Andrey Belyaev   +12 more
wiley   +2 more sources

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Novel features of the energy momentum tensor of a Casimir apparatus in a weak gravitational field.

, 2008
The influence of the gravity acceleration on the regularized energy–momentum tensor of the quantized electromagnetic field between two plane parallel conducting plates is derived.
Luigi Rosa, Giuseppe Bimonte, Giampiero Esposito, Calloni, Enrico, Enrico Calloni, Bimonte, Giuseppe Roberto, G. Esposito, Rosa, Luigi   +7 more
core   +1 more source