Interface-Engineered Bi<sub>0.5</sub>Sb<sub>1.5</sub>Te<sub>3</sub>/WSe<sub>2</sub> Heterostructures for Enhanced Thermoelectric Performance. [PDF]
Giri K, Wang YL, Wu YT, Chen CH.
europepmc +1 more source
Step towards High Power Factor in Acidic-Doped Poly(3-hexylthiophene) Systems. [PDF]
Gogoc S +5 more
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Advancing Energy Materials by In Situ Atomic Scale Methods
Progress in in situ atomic scale methods leads to an improved understanding of new and advanced energy materials, where a local understanding of complex, inhomogeneous systems or interfaces down to the atomic scale and quantum level is required. Topics from photovoltaics, dissipation losses, phase transitions, and chemical energy conversion are ...
Christian Jooss +21 more
wiley +1 more source
Toward a Consensus Characterization Protocol for Organic Thermoelectrics. [PDF]
Dörling B +14 more
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The molecular design strategy that integrates both side chain and backbone engineering in diketopyrrolopyrrole‐based conjugated polymers to identify the optimal balance between doping efficiency and microstructural order is demonstrated. Comprehensive spectroscopic, electrochemical, morphological, and structural characterizations reveal that the ...
Taewoong Han +13 more
wiley +1 more source
Effects of Cryotherapy and Thermotherapy Using an E-TEET on Pain, Stress, and Satisfaction Among Patients and Healthcare Providers During Intravenous Catheterization: A Randomized Controlled Trial. [PDF]
Kim B, Kim S, Her J, Lee YJ, Hur MH.
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A synergistic dual‐modulation strategy is employed in Yb‐filled skutterudites through concurrent indium filling and tellurium doping to optimize electronic band structure and phonon scattering. Cooperative band convergence and nanoprecipitate‐induced lattice distortions yield a high zT of 1.72 and enable an ultra‐efficient thermoelectric device with 8 ...
Xuri Rao +10 more
wiley +1 more source
Investigation of thermoelectric properties of flexible Ti<sub>3</sub>C<sub>2</sub>T <sub><i>x</i></sub> MXene membranes. [PDF]
Irfan A +5 more
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Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Reduced Lattice Thermal Conductivity in Thermoelectric α-MgAgSb via Sb<sub>2</sub>Te<sub>3</sub> Powder Atomic Layer Deposition. [PDF]
García Santamaría I +9 more
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