scholarly journals Integrating lattice materials science into the traditional processing–structure–properties paradigm

2019 ◽  
Vol 9 (4) ◽  
pp. 1284-1291 ◽  
Author(s):  
Frank W. Zok
Keyword(s):  
Materials Science ◽  
Lattice Materials ◽  
Image Position ◽  
Traditional Processing ◽  
Structure Properties

Abstract

Targeted Alternation in Properties of Solid Amorphous-Nanocrystalline Material in Exposing to Nanosecond Laser Radiation

2021 ◽  
Vol 410 ◽  
pp. 469-474
Author(s):  
Ivan S. Safronov ◽  
Alexander I. Ushakov
Keyword(s):  
Laser Radiation ◽  
Physical Properties ◽  
Materials Science ◽  
Chemical Properties ◽  
High Energy ◽  
Strength Properties ◽  
Nanosecond Laser ◽  
Processing Modes ◽  
Traditional Processing ◽  
Physical And Chemical

One of the most important purposes of materials science is the ability to govern the physical properties of materials characterized by different structures. The strength properties of nanostructured metal alloys do not always meet the exploitation requirements. The set of properties of such materials is stable within narrow limits: temperature, mechanical, and corrosion conditions. Traditional processing modes are ineffective for such materials. Attempts to use them often lead to the loss of unique physical and chemical properties. The most effective methods of processing such materials are associated with the use of laser radiation. The laser pulse has a number of features, including a complex effect on the surface layers of the material. Spot and short irradiation with high-energy rays can preserve the unique physical properties of samples as a whole and improve strength indicators without destroying the structure of the material as a whole.

scholarly journals NOMAD: The FAIR concept for big data-driven materials science

MRS Bulletin ◽  
2018 ◽  
Vol 43 (9) ◽  
pp. 676-682 ◽  
Author(s):  
Claudia Draxl ◽  
Matthias Scheffler
Keyword(s):  
Big Data ◽  
Materials Science ◽  
Data Driven ◽  
Image Position

Abstract

scholarly journals A data ecosystem to support machine learning in materials science

2019 ◽  
Vol 9 (4) ◽  
pp. 1125-1133 ◽  
Author(s):  
Ben Blaiszik ◽  
Logan Ward ◽  
Marcus Schwarting ◽  
Jonathon Gaff ◽  
Ryan Chard ◽  
...  
Keyword(s):  
Machine Learning ◽  
Materials Science ◽  
Data Ecosystem ◽  
Image Position

Abstract

scholarly journals Symbolic regression in materials science

2019 ◽  
Vol 9 (3) ◽  
pp. 793-805 ◽  
Author(s):  
Yiqun Wang ◽  
Nicholas Wagner ◽  
James M. Rondinelli
Keyword(s):  
Materials Science ◽  
Symbolic Regression ◽  
Image Position

Abstract

scholarly journals The lateral completion of an arbitrary lattice group

1975 ◽  
Vol 19 (3) ◽  
pp. 263-289 ◽  
Author(s):  
S. J. Bernau
Keyword(s):  
Complete Lattice ◽  
Lattice Group ◽  
Arbitrary Lattice ◽  
Image Position ◽  
Structure Properties ◽  
The Ideal

SummaryThis paper shows that every lattice group G can be densely embedded in a unique laterally complete lattice group H (the lateral completion of G). All reasonable structure properties of G are inherited by H and we have the following relationships between the ideal radical L(G), the distributive radical D(G) and the radical R(G) of G and the corresponding radicals of H. .

scholarly journals Materials science with large-scale data and informatics: Unlocking new opportunities

MRS Bulletin ◽  
2016 ◽  
Vol 41 (5) ◽  
pp. 399-409 ◽  
Author(s):  
Joanne Hill ◽  
Gregory Mulholland ◽  
Kristin Persson ◽  
Ram Seshadri ◽  
Chris Wolverton ◽  
...  
Keyword(s):  
Large Scale ◽  
Materials Science ◽  
Large Scale Data ◽  
Image Position ◽  
Scale Data

Abstract

Facile Preparation of a Binderless Hierarchical Beta Zeolite in Shaped Form and with Improved Acidity for Catalysis

2020 ◽  
Author(s):  
Jiaxu Liu ◽  
Zhenmei Zhang ◽  
Chunyan Liu ◽  
Gianvito Vilé ◽  
Guang Xiong ◽  
...  
Keyword(s):  
Materials Science ◽  
Zeolite Catalysts ◽  
Beta Zeolite ◽  
Synthetic Approach ◽  
Advanced Manufacturing ◽  
Hierarchical Zeolite ◽  
Characterization Methods ◽  
Tetraethylammonium Hydroxide ◽  
Beta Zeolites ◽  
Structure Properties

<div> <div> <div> <div> <p>The synthesis of a technical hierarchical nanosized zeolite catalysts without growth modifiers and binders remains a major challenge in catalysis. Herein, we report a new synthetic approach to directly produce hierarchical nanosized Beta zeolites in technical form, without any binders in the final material. The synthesis consists of two steps, where a Beta zeolite powder is first shaped using tetraethyl orthosilicate; the extrude is then recrystallized at high temperature in the presence of tetraethylammonium hydroxide solution. This transforms the SiO2 binders into zeolite framework. A variety of characterization methods were applied to unlock structure-properties relationships of the materials and demostrate their catalytic functionality. We believe that this work opens avenues for the advanced manufacturing of hierarchical zeolite materials in shaped form, and will find useful applications in catalysis and materials science. </p> </div> </div> </div> </div>

Sign in / Sign up

Export Citation Format

Share Document