Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
96,653
result(s) for
"Entropy."
Sort by:
(Multiscale) Cross-Entropy Methods: A Review
Cross-entropy was introduced in 1996 to quantify the degree of asynchronism between two time series. In 2009, a multiscale cross-entropy measure was proposed to analyze the dynamical characteristics of the coupling behavior between two sequences on multiple scales. Since their introductions, many improvements and other methods have been developed. In this review we offer a state-of-the-art on cross-entropy measures and their multiscale approaches.
Journal Article
Tunable stacking fault energies by tailoring local chemical order in CrCoNi medium-entropy alloys
High-entropy alloys (HEAs) are an intriguing new class of metallic materials due to their unique mechanical behavior. Achieving a detailed understanding of structure–property relationships in these materials has been challenged by the compositional disorder that underlies their unique mechanical behavior. Accordingly, in this work, we employ first-principles calculations to investigate the nature of local chemical order and establish its relationship to the intrinsic and extrinsic stacking fault energy (SFE) in CrCoNi medium-entropy solid-solution alloys, whose combination of strength, ductility, and toughness properties approaches the best on record. We find that the average intrinsic and extrinsic SFE are both highly tunable, with values ranging from −43 to 30 mJ·m−2 and from −28 to 66 mJ·m−2, respectively, as the degree of local chemical order increases. The state of local ordering also strongly correlates with the energy difference between the face-centered cubic (fcc) and hexagonal close-packed (hcp) phases, which affects the occurrence of transformation-induced plasticity. This theoretical study demonstrates that chemical short-range order is thermodynamically favored in HEAs and can be tuned to affect the mechanical behavior of these alloys. It thus addresses the pressing need to establish robust processing–structure–property relationships to guide the science-based design of new HEAs with targeted mechanical behavior.
Journal Article
Breakthrough applications of high-entropy materials
The concept of high-entropy alloys has been extended to ceramics, polymers, and composites. “High-entropy materials (HEMs)” are named to cover all these materials. Recently, HEMs has become a new emerging field through the collective efforts of many researchers. Basically, high mixing entropy can enhance the formation of solution-type phases for alloys, ceramics, and composites at high temperatures, and in general leads to simpler microstructure. Large degrees of freedom in composition design as well as process design have been found to provide a wide range of microstructure and properties for applications. There are many opportunities for HEMs to overcome the bottlenecks of conventional materials. In this article, several possible breakthrough applications are pointed out and emphasized for turbine blades, thermal spray bond coatings, high-temperature molds and dies, sintered carbides for cutting tools, hard coatings for cutting tools, hardfacings, and radiation-damage resistant materials. In addition, more possible breakthrough examples are briefly described.
Journal Article
Now : the physics of time
\"'Now' is a simple concept--you're reading this sentence now. Yet a real definition of 'now' has eluded even the great Einstein. We know that time stretches and is affected by gravity and velocity. Yet, as ... physicist Richard A. Muller points out, it is only today that we have all the physics at hand--relativity, entropy, entanglement, antimatter, and the Big Bang--to explain the flow of time. With these building blocks in place, Muller [posits that] our expanding universe is continuously creating not only new space but also new time\"-- Provided by publisher.
BOOK
Permutation Entropy: New Ideas and Challenges
Over recent years, some new variants of Permutation entropy have been introduced and applied to EEG analysis, including a conditional variant and variants using some additional metric information or being based on entropies that are different from the Shannon entropy. In some situations, it is not completely clear what kind of information the new measures and their algorithmic implementations provide. We discuss the new developments and illustrate them for EEG data.
Journal Article