High-throughput search for caloric materials: the CaloriCool approach (original) (raw)
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Exploration of selected room temperature magneto caloric materials using COMSOL multiphysics
IOP Conference Series: Materials Science and Engineering, 2019
Estimation of magneto-caloric effect is crucial to determine a material's suitability for the desired operating conditions. The magneto-caloric effect can be measured in two ways-the magnetic entropy change and the adiabatic temperature change. These parameters are the prerequisites in evaluating a magnetic refrigeration system. In this work, an application is developed and tested for 3 materials (one Gadolinium and two Lanthanum alloys) using COMSOL multiphysics to estimate the final temperature of a Magneto-Caloric Material (MCM). The duration of the magneto-caloric effect is compared amongst 4 different cases of magnetic field change. Among the selected materials Gadolinium shows the highest adiabatic temperature difference of 12K at a field change from 0 to 5 tesla.
Material-based figure of merit for caloric materials
Journal of Applied Physics, 2018
The efficient use of reversible thermal effects in magnetocaloric, electrocaloric, and elastocaloric materials is a promising avenue that can lead to a substantially increased efficiency of refrigeration and heat pumping devices, most importantly, those used in household and commercial cooling applications near ambient temperature. A proliferation in caloric material research has resulted in a wide array of materials where only the isothermal change in entropy in response to a handful of different field strengths over a limited range of temperatures has been evaluated and reported. Given the abundance of such data, there is a clear need for a simple and reliable figure of merit enabling fast screening and down-selection to justify further detailed characterization of those material systems that hold the greatest promise. Based on the analysis of several wellknown materials that exhibit vastly different magnetocaloric effects, the Temperature averaged Entropy Change is introduced as a suitable early indicator of the material's utility for magnetocaloric cooling applications, and its adoption by the caloric community is recommended.
Journal of Materials Science, 2012
The development of new technological materials has historically been a difficult and time-consuming task. The traditional role of computation in materials design has been to better understand existing materials. However, an emerging paradigm for accelerated materials discovery is to design new compounds in silico using firstprinciples calculations, and then perform experiments on the computationally designed candidates. In this paper, we provide a review of ab initio computational materials design, focusing on instances in which a computational approach has been successfully applied to propose new materials of technological interest in the laboratory. Our examples include applications in renewable energy, electronic, magnetic and multiferroic materials, and catalysis, demonstrating that computationally guided materials design is a broadly applicable technique. We then discuss some of the common features and limitations of successful theoretical predictions across fields, examining the different ways in which first-principles calculations can guide the final experimental result. Finally, we present a future outlook in which we expect that new models of computational search, such as high-throughput studies, will play a greater role in guiding materials advancements. ! wðr 1 ; . . .; r N Þ ¼ wðr 1 ; . . .; r N Þ
First-principles investigations of caloric effects in ferroic materials
2011
Hysteresis effects in the inverse magnetocaloric effect in martensitic Ni-Mn-In and Ni-Mn-Sn J. Appl. Phys. 112, 073914 (2012) Resolving quandaries surrounding NiTi Appl. Phys. Lett. 101, 081907 Incident flux angle induced crystal texture transformation in nanostructured molybdenum films
Computational Materials Science, 2012
Empirical databases of crystal structures and thermodynamic properties are fundamental tools for materials research. Recent rapid proliferation of computational data on materials properties presents the possibility to complement and extend the databases where the experimental data is lacking or difficult to obtain. Enhanced repositories that integrate both computational and empirical approaches open novel opportunities for structure discovery and optimization, including uncovering of unsuspected compounds, metastable structures and correlations between various characteristics. The practical realization of these opportunities depends on a systematic compilation and classification of the generated data in addition to an accessible interface for the materials science community. In this paper we present an extensive repository, aflowlib.org, comprising phase-diagrams, electronic structure and magnetic properties, generated by the high-throughput framework AFLOW. This continuously updated compilation currently contains over 150,000 thermodynamic entries for alloys, covering the entire composition range of more than 650 binary systems, 13,000 electronic structure analyses of inorganic compounds, and 50,000 entries for novel potential magnetic and spintronics systems. The repository is available for the scientific community on the website of the materials research consortium, aflowlib.org.
The AFLOW Fleet for Materials Discovery
Handbook of Materials Modeling, 2018
The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data driven research. With the intent to accelerate the development and the deployment of new technologies, the AFLOW Fleet for computational materials design automates high-throughput first principles calculations, and provides tools for data verification and dissemination for a broad community of users. AFLOW incorporates different computational modules to robustly determine thermodynamic stability, electronic band structures, vibrational dispersions, thermo-mechanical properties and more. The AFLOW data repository is publicly accessible online at aflow.org, with more than 1.7 million materials entries and a panoply of queryable computed properties. Tools to programmatically search and process the data, as well as to perform online machine learning predictions, are also available.
First principles approach to the magneto caloric effect: Application toNi2MnGa
Journal of Applied Physics, 2011
The magneto-caloric effect (MCE) is a possible route to more efficient heating and cooling of residential and commercial buildings. The search for improved materials is important to the development of a viable MCE based heat pump technology. We have calculated the magnetic structure of a candidate MCE material: Ni 2 MnGa. The density of magnetic states was calculated with the Wang Landau statistical method utilizing energies fit to those of the locally self-consistent multiple scattering method. The relationships between the density of magnetic states and the field induced adiabatic temperature change and the isothermal entropy change are discussed.
High-Throughput Methods for Searching New Permanent Magnet Materials
IEEE Transactions on Magnetics, 2014
Highest performance FeNd -B-based permanent magnets offer only low cost-effectiveness and shortened lifetime, both induced by their rare-earth (RE) content. Thus, the necessity for novel hard magnetic phases with better available RE metals, reduced RE content or fully free of RE is immense. As the number of so far unexplored alloy systems is large, the chances that such magnet materials still exist are good. The successful search for novel hard magnetic phases demands an efficient approach of restricting and prioritizing the search field as well as deployment of efficient synthesis and analysis methods. The high-throughput approaches are based on heterogeneous nonequilibrium states and the estimation of the intrinsic material parameters from the domain structure. The efficiency of the methods is demonstrated for the well-known systems Co-Sm and FeNd -B. The methods are then applied to discover novel hard magnetic compounds with RE elements of better availability (Fe-Nd-(Ce,La,Y)-B) or smaller amount (Fe-Ce-(Ti,Zr)).
Challenges in Materials Discovery – Synthetic Generator and Real Datasets
Proceedings of the AAAI Conference on Artificial Intelligence
Newly-discovered materials have been central to recent technological advances. They have contributed significantly to breakthroughs in electronics, renewable energy and green buildings, and overall, have promoted the advancement of global human welfare. Yet, only a fraction of all possible materials have been explored. Accelerating the pace of discovery of materials would foster technological innovations, and would potentially address pressing issues in sustainability, such as energy production or consumption. The bottleneck of this discovery cycle lies, however, in the analysis of the materials data. As materials scientists have recently devised techniques to efficiently create thousands of materials and experimentalists have developed new methods and tools to characterize these materials, the limiting factor has become the data analysis itself. Hence, the goal of this paper is to stimulate the development of new computational techniques for the analysis of materials data, by bring...
AFLOW: An automatic framework for high-throughput materials discovery
Computational Materials Science, 2012
Recent advances in computational materials science present novel opportunities for structure discovery and optimization, including uncovering of unsuspected compounds and metastable structures, electronic structure, surface and nano-particle properties. The practical realization of these opportunities requires systematic generation and classification of the relevant computational data by high-throughput methods. In this paper we present A (Automatic Flow), a software framework for high-throughput calculation of crystal structure properties of alloys, intermetallics and inorganic compounds. The A software is available for the scientific community on the website of the materials research consortium, aflowlib.org. Its geometric and electronic structure analysis and manipulation tools are additionally available for online operation at the same website. The combination of automatic methods and user online interfaces provide a powerful tool for efficient quantum computational materials discovery and characterization.