Results 181 to 190 of about 58,975 (287)

Step towards High Power Factor in Acidic-Doped Poly(3-hexylthiophene) Systems. [PDF]

open access: yesACS Omega
Gogoc S   +5 more
europepmc   +1 more source

Advancing Energy Materials by In Situ Atomic Scale Methods

open access: yesAdvanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
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]

open access: yesAdv Mater
Dörling B   +14 more
europepmc   +1 more source

Toward a Rational Design of Conjugated Copolymers with Oxygenated Side Chains for Boosting Thermoelectric Properties

open access: yesAdvanced Energy Materials, EarlyView.
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

Dual Band Optimization and Defect Engineering Enable Ultrahigh Thermoelectric Performance in Filled Skutterudites

open access: yesAdvanced Energy Materials, EarlyView.
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

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
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]

open access: yesACS Appl Mater Interfaces
García Santamaría I   +9 more
europepmc   +1 more source

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