Results 91 to 100 of about 5,812 (219)
ABSTRACT Real‐time insight into local chemistry is critical for reliable part quality in additive manufacturing, especially laser powder bed fusion (PBF‑LB/M), where rapid thermal cycles and localized evaporation can undermine part performance. Optical emission spectroscopy (OES) offers non‑intrusive, in situ plume monitoring, but detection geometry ...
Philipp Gabriel +4 more
wiley +1 more source
Zinc Exposure Causes Disulfidptosis to Induce Miscarriage by Up‐Regulating GATA1/METTL1/SLC7A11 Axis
Zn exposure up‐regulates GATA1, promoting GATA1‐mediated METTL1 and SLC7A11 transcription. It also enhances METTL1‐mediated m7G modification on SLC7A11 mRNA, increasing SLC7A11 mRNA stability. Ultimately, Zn exposure up‐regulates SLC7A11 at both transcriptional and post‐transcriptional levels, causing disulfidptosis. Knockdown of murine Slc7a11, Gata1,
Wenxin Huang +16 more
wiley +1 more source
Schematic showing a stretchable triboelectric nanogenerator based on interlocked wavy architectures that uses EGaIn microflower‐embedded PVDF‐TrFE and Nylon‐6 nanofiber membranes. The multi‐petaled, electron‐rich EGaIn microflowers enhance interfacial polarization and capacitance, while the interlocked wavy architecture enlarges the effective contact ...
Qianqian Xu +12 more
wiley +1 more source
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Here, we demonstrate and investigate polarization‐enabled electromechanical responses in cryogenic physical vapor deposition (cryogenic PVD)‐deposited TexSe1‐x thin films, a tellurium‐based compound with a tunable bandgap and enhanced non‐centrosymmetry.
Chia‐Chen Chung +16 more
wiley +1 more source
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin +12 more
wiley +1 more source
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li +8 more
wiley +1 more source
ABSTRACT Large‐ion (K, Na) battery systems mitigate uneven global lithium distribution, while their ability to attain recharge time shorter than refueling would remove the final barrier for secondary batteries to replace petroleum vehicles. However, their large‐ion chemistry makes ultra‐fast charging an even significant challenge.
Shukai Ding +12 more
wiley +1 more source
A direct cascaded utilization strategy for spent LiFePO4 batteries efficiently extracts lithium from brine, embodying the “urban mining” concept. Phase fraction modulation revealed its significant impact on local bond lengths of crystal structure and the Li/Na diffusion energy barrier, identifying the best material (Li0.19FePO4) for lithium extraction.
Ruiqi Yin +7 more
wiley +1 more source

