Results 211 to 220 of about 26,220 (311)

Controls on hydrocarbon accumulation in ultra-deep carbonate reservoirs of the Ordovician Yingshan Formation, Catake Uplift, Tarim Basin. [PDF]

Sci Rep
Wang L, Yang R, Geng F, Jiang Z, Zhang H, Zhang Q.   +5 more
europepmc   +1 more source

Methanol‐Ethanol Discrimination and Selective Sensing Enabled by Molecular Sieving in Conductive MOFs

Advanced Materials, EarlyView.
Selective methanol sensors are achieved by coating carbon nanotube chemiresistors with two dimensional conductive metal–organic frameworks that incorporate intra‐pore clusters. These confined clusters increase the density of adsorption sites while restricting the transport of larger interfering molecules, particularly ethanol. This sensing architecture
Young‐Moo Jo, Mingyu Jeon, Dong‐Ha Kim, Jihan Kim, Mircea Dincă   +4 more
wiley   +1 more source

Simulation of water-mud-inrush in fault fracture zone of deep and long railway tunnel in mountain area. [PDF]

Sci Rep
Yang S, Han H, Chen G, Guo M, Fan C, Zhao B, Yang B.   +6 more
europepmc   +1 more source

Advances in Magnesium‐Based Thermoelectrics: A Critical Review

Advanced Materials, EarlyView.
Magnesium‐based thermoelectric materials have emerged as promising candidates for low‐to‐mid‐temperature energy conversion due to their abundance, low cost, and competitive performance. This review summarizes recent advances in Mg3X2, MgAgSb, and Mg2X systems, covering transport mechanisms, fabrication strategies, stability challenges, and device ...
Li‐Min Zhang, Li Zhang, Nan‐Hai Li, Yan‐Ling Yang, Xiao‐Lei Shi, Zhi‐Gang Chen   +5 more
wiley   +1 more source

Mechanical response analysis of tunnels crossing reverse faults under non-uniform seismic inputs. [PDF]

Sci Rep
Yang Y, Li X, Liu J, Chen S.
europepmc   +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

Integrated 3D static modelling to assess hydrocarbon potential of the fluvial-alluvial sandstones of Nukhul Formation, October oil field, Gulf of Suez, Egypt. [PDF]

Sci Rep
Khattab MA, Radwan AE, El-Anbaawy MI, El-Tehiwy AA.   +3 more
europepmc   +1 more source

Tailoring Phonon‐Driven Responses in α‐MoO3 through Isotopic Enrichment

Advanced Materials, EarlyView.
ABSTRACT The implementation of polaritonic materials into nanoscale devices requires selective tuning of parameters to realize desired spectral or thermal responses. One robust material, α‐MoO3, an orthorhombic crystal boasting three distinct phonon dispersions, provides three polaritonic dispersions of hyperbolic phonon polaritons (HPhPs) across the ...
Thiago S. Arnaud, Ryan W. Spangler, Johnathan D. Georgaras, Jonah B. Haber, Daniel Hirt, Maximilian Obst, Gonzalo Álvarez‐Pérez, Mackey Long III, Felix G. Kaps, Jakob Wetzel, Courtney Ragle, John E. Buchner, Youngji Kim, Aditha S. Senarath, Richarda Niemann, Mingze He, Giulia Carini, Unai Arregui‐Leon, Akash C. Behera, Ramachandra Bangari, Nihar Sahoo, Niels C. Brumby, J. Michael Klopf, Martin Wolf, Lukas M. Eng, Susanne C. Kehr, Thomas G. Folland, Alexander Paarmann, Patrick E. Hopkins, Felipe Jornada, Jon‐Paul Maria, Joshua D. Caldwell   +31 more
wiley   +1 more source

Insights into Sudbury's deep architecture: a revised geodynamic model for Earth's largest ore-bearing impact structure. [PDF]

Sci Rep
Haugaard R, Spray JG, Adetunji AQ, Vayavur R, Hamilton MA, Snyder D, Cheraghi S, Ayer J, Henry K, Jørgensen TRC, Serafini G, Smith R, Gibson L.   +12 more
europepmc   +1 more source

Deep Learning Inverse Design of Phase‐Change Reconfigurable Terahertz Metadevices for Multidimensional Secure Communication

Advanced Materials, EarlyView.
A deep learning inverse‐design framework is established to create versatile reconfigurable terahertz metadevices. By synergizing deep learning with phase‐change materials, this approach enables on‐demand customization of multidimensional electromagnetic responses.
Yisheng Dong, Xieyu Chen, Aarthy Nagarajan, Yi Yang, Zhihao Wang, Rui Yu, Chuang Zheng, Chunmei Ouyang, Xueqian Zhang, Tun Cao, Ranjan Singh, Zhen Tian   +11 more
wiley   +1 more source