Results 221 to 230 of about 3,606,574 (279)

Unique Performance Considerations for Printable Organic Semiconductor and Perovskite Radiation Detectors: Toward Consensus on Best Practice Evaluation

Advanced Functional Materials, EarlyView.
A lack of standard approaches for testing and reporting the performance of metal halide perovskites and organic semiconductor radiation detectors has resulted in inconsistent interpretation of performance parameters, impeding progress in the field. This Perspective recommends key metrics and experimental details, which are suggested for reporting in ...
Jessie A. Posar, Matthew Large, Andrea Ciavatti, Laura Basiricò, Beatrice Fraboni, Paul J. Sellin, Attila J. Mozer, Marco Petasecca, Matthew J. Griffith   +8 more
wiley   +1 more source

Organic Electrochemical Transistor Channel Materials: Copolymerization Versus Physical Mixing of Glycolated and Alkoxylated Polymers

Advanced Functional Materials, EarlyView.
This work discusses the use of blended channel materials in OECTs. It explores how mixing glycolated and alkoxylated polymers in various ratios offers a simpler and more efficient route to tuning OECT properties. The performance of the polymer blends is compared to the corresponding copolymers, demonstrating similar OECT characteristics, swelling ...
Lize Bynens, Kaishuai Zhang, Priscila Cavassin, Arwin Goossens, Jochen Vanderspikken, Tania C. H. Castillo, Demetra Tsokkou, Adam Marks, Arianna Magni, Karrie Weaver, Laurence Lutsen, Sahika Inal, Koen Vandewal, Natalie Banerji, Wouter Maes   +14 more
wiley   +1 more source

Ideal Molecular Sieving with a Dense MOF for Helium Upgrading with Highly Diffusion Selective Mixed Matrix Membranes

Advanced Functional Materials, EarlyView.
The separation of Helium gas from natural gas is challenging but highly important. MIL‐116(Ga), a “non‐porous” metal–organic framework is used as a molecular sieve to separate He from CH4. Druse‐like MIL‐116(Ga) particles are integrated into polysulfone mixed matrix membranes.
Ayisha Komal, Laura Calderón‐Rodríguez, Oksana Smirnova, Eren Grossmann, Aparna Binu Varghese, Karen Marlenne Garcia Alvarez, Andreas Schneemann, Thomas Hoyer, Ralf Wyrwa, Felix Helmut Schacher, Alexander Knebel   +10 more
wiley   +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

Model averaging in calibration of near-infrared instruments with correlated high-dimensional data. [PDF]

J Appl Stat
Salaki DT, Kurnia A, Sartono B, Mangku IW, Gusnanto A.   +4 more
europepmc   +1 more source

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Dimensionality reduction for visualizing high-dimensional biological data

Biosystems, 2022
High throughput technologies used in experimental biological sciences produce data with a vast number of variables at a rapid pace, making large volumes of high-dimensional data available. The exploratory analysis of such high-dimensional data can be aided by human interpretable low-dimensional visualizations.
Tamasha Malepathirana, Damith Senanayake, Rajith Vidanaarachchi, Vini Gautam, Saman Halgamuge   +4 more
openaire   +3 more sources

High-Dimensional Data Cubes

Proceedings of the VLDB Endowment, 2022
This paper introduces an approach to supporting high-dimensional data cubes at interactive query speeds and moderate storage cost. The approach is based on binary(-domain) data cubes that are judiciously partially materialized; the missing information can be quickly reconstructed using statistical or linear programming techniques.
Sachin Basil John, Christoph Koch
openaire   +1 more source

Dimensionality reduction for high dimensional data

Proceedings of the 2014 International Conference on Information and Communication Technology for Competitive Strategies, 2014
Information Technology has produced huge amounts of data and these data need to be processed to extract information hidden in it. Feature selection techniques often come handy to process these data efficiently. In this paper, a novel approach for feature selection GA-CFS is proposed.
Aditya Kumar, Smita Roy, Prabhat Ranjan
openaire   +1 more source

Cross-Dimensional Inference of Dependent High-Dimensional Data

Journal of the American Statistical Association, 2012
A growing number of modern scientific problems in areas such as genomics, neurobiology, and spatial epidemiology involve the measurement and analysis of thousands of related features that may be stochastically dependent at arbitrarily strong levels. In this work, we consider the scenario where the features follow a multivariate Normal distribution.
Keyur H, Desai, John D, Storey
openaire   +2 more sources