Integrated computational materials engineering for advanced materials: A brief review
TL;DR: It is believed that the combinations of high-throughput multi-scale computations and fast experiments/manufacturing will build the advanced algorithms in the development of a promising digital fabricating approach to overcome the present and future challenges, illuminating the way toward the digital-twin intelligent manufacturing era.
About: This article is published in Computational Materials Science.The article was published on 2019-02-15. It has received 59 citations till now. The article focuses on the topics: Integrated computational materials engineering.
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TL;DR: In this paper, the authors proposed the strategy of tailoring strain delocalization to evade long-standing strength-ductility trade-off dilemma, where the achieving of strengthductility synergy depends on the delocalizing of localized strains.
197 citations
TL;DR: The extent of digital twin adoption in agriculture is examined, light is shed on the concept and the benefits it brings, and an application-based roadmap for a more extended adoption is proposed.
153 citations
Cites background from "Integrated computational materials ..."
...…engineering x x x Raman and Hassanaly (2019) 2019 2019 82 for material fabrication growth of material knowledge concept material science x Yi Wang et al. (2019) 2019 2019 83 to monitor pig health and prevent diseases reduced animal disease costs concept agriculture x x Paraforos et al.…...
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...…2018; Dong et al., 2019; Cohen et al., 2019; Tomiyama et al., 2019; Qi and Tao, 2018; Tao et al., 2019; Lu et al., 2020; Raman and Hassanaly, 2019; Yi Wang et al., 2019; Paraforos et al., 2019; Pizzolato et al., 2019; Mabkhot et al., 2018; Cimino et al., 2019; Gupta and Basu, 2019; Ghobakhloo,…...
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TL;DR: The adoption of laser powder bed fusion (L-PBF) for metals by the industry has been limited despite the significant progress made in the development of the process chain this paper.
Abstract: The adoption of laser powder bed fusion (L-PBF) for metals by the industry has been limited despite the significant progress made in the development of the process chain. One of the key obstacles i...
87 citations
01 Oct 2017
TL;DR: Cubuk et al. as mentioned in this paper link structure to plasticity in disordered solids via a microscopic structural quantity, "softness," designed by machine learning to be maximally predictive of rearrangements.
Abstract: Behavioral universality across size scales Glassy materials are characterized by a lack of long-range order, whether at the atomic level or at much larger length scales. But to what extent is their commonality in the behavior retained at these different scales? Cubuk et al. used experiments and simulations to show universality across seven orders of magnitude in length. Particle rearrangements in such systems are mediated by defects that are on the order of a few particle diameters. These rearrangements correlate with the material's softness and yielding behavior. Science, this issue p. 1033 A range of particle-based and glassy systems show universal features of the onset of plasticity and a universal yield strain. When deformed beyond their elastic limits, crystalline solids flow plastically via particle rearrangements localized around structural defects. Disordered solids also flow, but without obvious structural defects. We link structure to plasticity in disordered solids via a microscopic structural quantity, “softness,” designed by machine learning to be maximally predictive of rearrangements. Experimental results and computations enabled us to measure the spatial correlations and strain response of softness, as well as two measures of plasticity: the size of rearrangements and the yield strain. All four quantities maintained remarkable commonality in their values for disordered packings of objects ranging from atoms to grains, spanning seven orders of magnitude in diameter and 13 orders of magnitude in elastic modulus. These commonalities link the spatial correlations and strain response of softness to rearrangement size and yield strain, respectively.
69 citations
TL;DR: In this paper, an integrated computational materials engineering case study with the aim of improving the strength and ductility of Titanium (Ti) alloys is presented, where the electronic properties of elemental building blocks were derived from high-throughput first-principles calculations and presented in the form of the Mendeleev periodic table, including their electron work function, Fermi energy, bonding charge density, and lattice distortion energy.
66 citations
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TL;DR: A unified theoretical framework highlights the need for catalyst design strategies that selectively stabilize distinct reaction intermediates relative to each other, and opens up opportunities and approaches to develop higher-performance electrocatalysts for a wide range of reactions.
Abstract: BACKGROUND With a rising global population, increasing energy demands, and impending climate change, major concerns have been raised over the security of our energy future. Developing sustainable, fossil-free pathways to produce fuels and chemicals of global importance could play a major role in reducing carbon dioxide emissions while providing the feedstocks needed to make the products we use on a daily basis. One prospective goal is to develop electrochemical conversion processes that can convert molecules in the atmosphere (e.g., water, carbon dioxide, and nitrogen) into higher-value products (e.g., hydrogen, hydrocarbons, oxygenates, and ammonia) by coupling to renewable energy. Electrocatalysts play a key role in these energy conversion technologies because they increase the rate, efficiency, and selectivity of the chemical transformations involved. Today’s electrocatalysts, however, are inadequate. The grand challenge is to develop advanced electrocatalysts with the enhanced performance needed to enable widespread penetration of clean energy technologies. ADVANCES Over the past decade, substantial progress has been made in understanding several key electrochemical transformations, particularly those that involve water, hydrogen, and oxygen. The combination of theoretical and experimental studies working in concert has proven to be a successful strategy in this respect, yielding a framework to understand catalytic trends that can ultimately provide rational guidance toward the development of improved catalysts. Catalyst design strategies that aim to increase the number of active sites and/or increase the intrinsic activity of each active site have been successfully developed. The field of hydrogen evolution, for example, has seen important breakthroughs over the years in the development of highly active non–precious metal catalysts in acid. Notable advancements have also been made in the design of oxygen reduction and evolution catalysts, although there remains substantial room for improvement. The combination of theory and experiment elucidates the remaining challenges in developing further improved catalysts, often involving scaling relations among reactive intermediates. This understanding serves as an initial platform to design strategies to circumvent technical obstacles, opening up opportunities and approaches to develop higher-performance electrocatalysts for a wide range of reactions. OUTLOOK A systematic framework of combining theory and experiment in electrocatalysis helps to uncover broader governing principles that can be used to understand a wide variety of electrochemical transformations. These principles can be applied to other emerging and promising clean energy reactions, including hydrogen peroxide production, carbon dioxide reduction, and nitrogen reduction, among others. Although current paradigms for catalyst development have been helpful to date, a number of challenges need to be successfully addressed in order to achieve major breakthroughs. One important frontier, for example, is the development of both experimental and computational methods that can rapidly elucidate reaction mechanisms on broad classes of materials and in a wide range of operating conditions (e.g., pH, solvent, electrolyte). Such efforts would build on current frameworks for understanding catalysis to provide the deeper insights needed to fine-tune catalyst properties in an optimal manner. The long-term goal is to continue improving the activity and selectivity of these catalysts in order to realize the prospects of using renewable energy to provide the fuels and chemicals that we need for a sustainable energy future.
7,062 citations
TL;DR: On the bicentenary of the publication of Poisson's Traité de Mécanique, the continuing relevance of Poissons's ratio in the understanding of the mechanical characteristics of modern materials is reviewed.
Abstract: In comparing a material's resistance to distort under mechanical load rather than to alter in volume, Poisson's ratio offers the fundamental metric by which to compare the performance of any material when strained elastically. The numerical limits are set by ½ and -1, between which all stable isotropic materials are found. With new experiments, computational methods and routes to materials synthesis, we assess what Poisson's ratio means in the contemporary understanding of the mechanical characteristics of modern materials. Central to these recent advances, we emphasize the significance of relationships outside the elastic limit between Poisson's ratio and densification, connectivity, ductility and the toughness of solids; and their association with the dynamic properties of the liquids from which they were condensed and into which they melt.
1,625 citations
TL;DR: This paper provides a comprehensive review of associated topics such as intelligent manufacturing, Internet of Things (IoT)-enabled manufacturing, and cloud manufacturing and describes worldwide movements in intelligent manufacturing.
1,602 citations
TL;DR: The Open Quantum Materials Database (OQMD) as mentioned in this paper contains over 200,000 DFT calculated crystal structures and will be freely available for public use at http://oqmd.org.
Abstract: High-throughput density functional theory (HT DFT) is fast becoming a powerful tool for accelerating materials design and discovery by the amassing tens and even hundreds of thousands of DFT calculations in large databases. Complex materials problems can be approached much more efficiently and broadly through the sheer quantity of structures and chemistries available in such databases. Our HT DFT database, the Open Quantum Materials Database (OQMD), contains over 200,000 DFT calculated crystal structures and will be freely available for public use at http://oqmd.org
. In this review, we describe the OQMD and its use in five materials problems, spanning a wide range of applications and materials types: (I) Li-air battery combination catalyst/electrodes, (II) Li-ion battery anodes, (III) Li-ion battery cathode coatings reactive with HF, (IV) Mg-alloy long-period stacking ordered (LPSO) strengthening precipitates, and (V) training a machine learning model to predict new stable ternary compounds.
1,475 citations
TL;DR: The largest available database of potentially exfoliable 2D materials has been obtained via high-throughput calculations using van der Waals density functional theory.
Abstract: Two-dimensional (2D) materials have emerged as promising candidates for next-generation electronic and optoelectronic applications. Yet, only a few dozen 2D materials have been successfully synthesized or exfoliated. Here, we search for 2D materials that can be easily exfoliated from their parent compounds. Starting from 108,423 unique, experimentally known 3D compounds, we identify a subset of 5,619 compounds that appear layered according to robust geometric and bonding criteria. High-throughput calculations using van der Waals density functional theory, validated against experimental structural data and calculated random phase approximation binding energies, further allowed the identification of 1,825 compounds that are either easily or potentially exfoliable. In particular, the subset of 1,036 easily exfoliable cases provides novel structural prototypes and simple ternary compounds as well as a large portfolio of materials to search from for optimal properties. For a subset of 258 compounds, we explore vibrational, electronic, magnetic and topological properties, identifying 56 ferromagnetic and antiferromagnetic systems, including half-metals and half-semiconductors.
1,336 citations