Results 121 to 130 of about 613,752 (314)

Thermoelectric Modules Incorporating MgAgSb and Mg3(Sb,Bi)2 Synthesized Using a Melting Method

Advanced Engineering Materials, EarlyView.
A scalable synthesis method for a thermoelectric material of MgAgSb is established. A thermoelectric power module of MgAgSb/Mg3(Sb,Bi)2 is fabricated, showing the conversion efficiency of 7.4% at ΔT = 315 K. The performance is comparable to conventional Bi2Te3 modules when they are operated with an air‐cooled heat exchanger.
Kazuo Nagase, Hironori Ohshima, Kunihiro Kihou, Haruno Kunioka, Ushin Anazawa, Ryosuke Sakagami, Yosuke Goto, Masayuki Murata, Chul‐Ho Lee   +8 more
wiley   +1 more source

Lower bounds on the mean square error derived from mixture of linear and non-linear transformations of the unbiasness definition

, 2009
Éric Chaumette, Alexandre Renaux, Pascal Larzabal   +2 more
openalex   +2 more sources

Estimating the Mean of a Normal Distribution with Loss Equal to Squared Error Plus Complexity Cost [PDF]

, 1987
Peter J. Kempthorne
openalex   +1 more source

Photoswitchable Conductive Metal–Organic Frameworks

Advanced Functional Materials, EarlyView.
A conductive material where the conductivity can be modulated remotely by irradiation with light is presented. It is based on films of conductive metal–organic framework type Cu3(HHTP)2 with embedded photochromic molecules such as azobenzene, diarylethene, spiropyran, and hexaarylbiimidazole in the pores.
Yidong Liu, Mersad Mostaghimi, Abhinav Chandresh, Saibal Jana, Wolfgang Wenzel, Lars Heinke   +5 more
wiley   +1 more source

Linear Precoding based on Minimum Mean Square Error in MISO Downlink Cognitive Radio Network [PDF]

, 2015
Shunran Wang, Yanhui Lu, Duanyang Li
openalex   +1 more source

Understanding and Optimizing Li Substitution in P2‐Type Sodium Layered Oxides for Sodium‐Ion Batteries

Advanced Functional Materials, EarlyView.
This work explores Li‐substituted P2 layered oxides for Na‐ion batteries by crystallographic and electrochemical studies. The effect of lithium on superstructure orderings, on phase transitions during synthesis and electrochemical cycling and on the interplay of O‐ versus TM‐redox is revealed via various advanced techniques, including semi‐simultaneous 
Mingfeng Xu, Giovanni Gammaitoni, Michael Häfner, Eduardo Villalobos‐Portillo, Carlo Marini, Matteo Bianchini   +5 more
wiley   +1 more source

The mean and standard error of cross-correlation (CC) and root mean square of the difference (RMS. Diff) across the participants and the cycles for shoulder flexion (SF), internal rotation (SI), abduction (SA) angle and angular velocity.

, 2015
Samani Afshin, Pontonnier Charles, Dumont Georges, Madeleine Pascal   +3 more
openalex   +2 more sources

Cu‐Based MOF/TiO2 Composite Nanomaterials for Photocatalytic Hydrogen Generation and the Role of Copper

Advanced Functional Materials, EarlyView.
HKUST‐1/TiO2 composite materials show a very high photocatalytic hydrogen evolution rate which increases as a function of the irradiation time until reaching a plateau and even surpasses the performance of the 1%Pt/TiO2 material after three photocatalytic cycles.
Alisha Khan, Marie Le Pivert, Alireza Ranjbari, Diana Dragoe, Daniel Bahena‐Uribe, Christophe Colbeau‐Justin, Christian Herrero, Dorota Rutkowska‐Zbik, Johnny Deschamps, Hynd Remita   +9 more
wiley   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Flux‐Regulated Crystallization of Perovskites Using Machine Learning‐Predicted Solvent Evaporation Rates for X‐Ray Detectors

Advanced Functional Materials, EarlyView.
By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto, Sergey Dayneko, Antoine Pavesic Junior, Nicholas Sandor, Alexander Hart, Yuki Haruta, Magdalena Bazalova‐Carter, Marcos J. L. Santos, Makhsud I. Saidaminov   +8 more
wiley   +1 more source