Zi-Kui Liu - US grants

0073836
Liu

The Department of Materials Science and Engineering at Penn State University develops an integrated computational approach in core subjects of the graduate and upper-undergraduate curricula. The approach is based on new courses on computational thermodynamics, computational kinetics and integrated systems materials design, that integrate fundamental principles and advanced computational tools.

Computer-based educational tools will help students connect abstract thermodynamic concepts with the properties of real world materials and mathematical kinetics with practical materials processing procedures, and thus remove the common perception among students that thermodynamics and kinetics are problematical to learn and difficult to apply in practice.

9983532
Liu

The objective of this CAREER grant is to create a completely new methodology for magnesium alloy design through a fundamental understanding of process/structure/property relationships in metal alloys. This work develops (a) a novel system materials design approach based on a combination of computational thermodynamics calculation, phase transformation simulation, and experimental prototype evaluation, (b) an efficient methodology of multi-component thermodynamic modeling by integrating thermodynamic predictions and critically designed experiments, and (c) thermodynamic models of phase interfaces. Computational thermodynamics is the important part of the program and is essential for understanding the fundamental mechanisms, morphology, and kinetics of microstructure development. The CAREER teaching program focuses on computational thermodynamics and system materials design, involving both undergraduate and graduate students. The planned effort will improve the core curriculum in materials science and engineering by applying fundamental principles in conjunction with state-of-the-art computer software to efficiently develop solutions to technological problems. It will enable students to visualize the abstract concepts in thermodynamics through phase diagram calculations and phase transformation simulations, strengthen their computational skills through computer experiments, and improve their communication skills through team projects and presentations.
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The proposed program will aid the development of magnesium alloys for automotive and aerospace applications and for hydrogen storage. The program is timely due to increasing industrial interest in magnesium alloys, and it is especially desirable in the U.S. as research activities on magnesium alloys are limited in comparison with Europe. New structural materials technologies are a determining factor in the global competitiveness of U.S. manufacturing industries. As one of the lightest structural materials, magnesium alloys have high potential for considerably reducing the weight of transportation vehicles and improving fuel efficiency.
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This award is made under the Information Technology Research initiative and is funded jointly by the Division of Materials Research and the Advanced Computational Infrastructure Research Division.

This collaborative research project involves two materials scientists, a computer
scientist, a mathematician, and two physicists from academia, industry and a national laboratory. The project is a synergistic effort that leverages the overlapping and complimentary expertise of the researchers in the areas of scalable parallel scientific computing, first-principles and atomistic calculations, computational thermodynamics, mesoscale microstructure evolution, and macroscopic mechanical property modeling. The main objective of the proposal is to develop a set of integrated computational tools to predict the relationships among the chemical, microstructural, and mechanical properties of multicomponent materials using technologically important aluminum-based alloys as model materials. A prototype GRID-enabled software will be developed for multicomponent materials design with efficient information exchange between design stages. Each design stage will incorporate effective algorithms and parallel computing schemes. Four computational components will be integrated, these are: (1) first-principles calculations to determine thermodynamic properties, lattice parameters, and kinetic data of unary, binary and ternary compounds; (2) CALPHAD data optimization computation to extract thermodynamic properties, lattice parameters, and kinetic data of multicomponent systems combining results from first-principles calculations and experimental data; (3) multicomponent phase-field modeling to produce microstructure; and (4) finite element analysis to obtain the mechanical response from the simulated microstructure. The research involves a parallel effort in information technology with two main components: (1) advanced discretization and parallel algorithms, and (2) a software architecture for distributed computing system. The first component includes: (a) a coupling of spectral and finite element approximations, (b) local adaptivity and multi-scale resolution, (c) high order stable semi-implicit in time schemes, (d) parallelization through domain decomposition, and (e) scalable sparse system solvers. The second component involves computational GRID-enabled software for the overall design process; this software architecture enables the use of geographically distributed high performance parallel computing resources to reduce application turnaround time while providing a flexible client-server interface that allows multiple design cycles to proceed.

The research project will be integrated with education and training of graduate students in the broad area of computational science and engineering through the participation of students and the PIs in the "High Performance Computing Graduate Minor" offered through the Institute of High Performance Computing at The Pennsylvania State University. Existing programs at Penn State will be used to integrate undergraduates into the project.
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This award is made under the Information Technology Research initiative and is funded jointly by the Division of Materials Research and the Advanced Computational Infrastructure Research Division.

This collaborative research project involves two materials scientists, a computer
scientist, a mathematician, and two physicists from academia, industry and a national laboratory. The project is a synergistic effort that leverages the overlapping and complimentary expertise of the researchers in the areas of scalable parallel scientific computing, first-principles and atomistic calculations, computational thermodynamics, mesoscale microstructure evolution, and macroscopic mechanical property modeling. The main objective of the proposal is to develop a set of integrated computational tools to predict the relationships among the chemical, microstructural and mechanical properties of multicomponent materials using technologically important aluminum-based alloys as model materials. Prototype GRID-enabled software will be developed for multicomponent materials design. Effective algorithms and parallel computing schemes will be incorporated into the design. The GRID-enabled software allows geographically distributed high performance parallel computing resources to be harnessed bringing greater computational power to bear on a given problem and enabling practical application of these computational tools. The prototype software, with improved predictive power in multicomponent materials design, may enable scientists to develop new materials with unique properties and to tailor existing materials for better performance.

The research project will be integrated with education and training of graduate students in the broad area of computational science and engineering through the participation of students and the PIs in the "High Performance Computing Graduate Minor" offered through the Institute of High Performance Computing at The Pennsylvania State University. Existing programs at Penn State will be used to integrate undergraduates into the project.
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The objective of this research is to develop a thermodynamic description for the free energy of each phase as a function of composition and temperature in ternary aluminum and nickel base alloys. The heats of formation are determined using a custom built high temperature reaction calorimeter with a typical accuracy of +/- 1kJ/mole. In addition, differential thermal analysis will be used to determine melting points and other phase transitions and differential scanning calorimetry will be used to determine heat capacity of selected alloys as a function of temperature. The DTA and DSC experiments will be performed in a new SETARAM 1750 C calorimeter. The data determined from the experiments will be used to develop an improved, self-consistent thermodynamic database for Aluminum-Nickel-base alloys that find application in technologies requiring high temperature structural alloys. Such data on Al and Ni-base alloy systems are scarce or non-existent. The experimental results will be used to compute the minimum in free energy for a particular composition at a given temperature. Such thermodynamic modeling of phase diagrams provides an opportunity to approach the phase equilibria aspects of alloy development in a more efficient manner. The improved database will be used to compute several isothermal sections in each of the ternary alloy systems using THERMOCALC. The data will also be used to validate various extrapolation models from the literature for the prediction of heats of formation of ternary compounds from binary data.

The work finds application in the design of multi-component nickel and aluminum based alloys that are used in many technologies as structural materials. The experimental results of the study will provide the needed data for phase diagram calculations using CALPHAD methodology that is far more efficient than the currently available techniques. These experimental data are not available and this will be the only facility in USA that has the expertise to fill the need. From a fundamental viewpoint, the project will advance a largely uncharted area of research that is concerned with multi-component, multi-phase systems with varied phases. These systems find application in many technologies that require high temperature structural materials.

The Industry/University Cooperative Research Center for Computational Materials Design jointly proposed by Penn State and Georgia Tech, aims to substantially impact progress towards systems-based materials design by promoting research programs of interest to both industry and universities, to enhance the infrastructure of computational materials research in the nation, to explore and extend the interface between engineering systems design, information technology and physics-based simulation of process-structure and structure-property relations of materials, to improve the intellectual capacity of the workforce through industrial participation and conduct of high quality research projects, and to develop curriculum in computational and systems design aspects of materials. This will be achieved by developing long-term partnerships among industry, university and other organizations.

The Industry/University Cooperative Research Center for Computational Materials Design joins Penn State and Georgia Tech to substantially impact progress towards systems-based materials design by promoting research programs of interest to both industry and universities, to enhance the infrastructure of computational materials research in the nation, to explore and extend the interface between engineering systems design, information technology and physics-based simulation of process-structure and structure-property relations of materials, to improve the intellectual capacity of the workforce through industrial participation and conduct of high quality research projects, and to develop curriculum in computational and systems design aspects of materials.

TECHNICAL SUMMARY: This project aims to develop a comprehensive understanding of the effects of alloying elements on the properties of magnesium alloys by integrating first-principles calculations, computational modeling and experimental investigations for the purpose of providing quantitative guidance for designing high performance magnesium alloys. The objectives of the proposed research are severalfold: (a) to predict elastic properties and diffusion behavior of binary and ternary compounds and solution phases through first-principles calculations; (b) to create libraries of diffusion data and elastic properties of important ternary systems through the use of diffusion couples and experiments on individual alloys using advanced analytical tools; (c) to develop models for the properties of magnesium alloys through innovative modeling approaches; (d) to establish mechanistic models that relate elastic properties and diffusivities to the performance of these materials by collaborating with research organizations and companies.

NON-TECHNICAL SUMMARY: Magnesium is the lightest structural metallic material. This makes magnesium alloys particularly attractive for transportation applications such as automobiles and helicopters for weight reduction and higher fuel efficiency. It is anticipated that the proposed research will contribute to shortening the time to develop new materials and improve existing materials. The participation of underrepresented groups will be encouraged through the SEEMS program (Summer Experience in Earth and Mineral Science) at Penn State for high school students and the recruitment of female students from the Penn State WISER program (Women in Science and Engineering Research). The proposed activity will also educate graduate and undergraduate students in computational and experimental work, encourage students to participate and present their work at meetings of professional societies and foster their writing skills through the preparation of publications for peer-reviewed journals.

***NON-TECHNICAL ABSTRACT***
Superconductors are essentially frictionless conductors of electricity. Thus, they avoid the heating effects that occur even in very high-conductivity copper wires. High magnetic field devices, impossible to make with copper, therefore become a possibility. Unfortunately superconductivity occurs only at rather low temperatures. There was great excitement when MgB2, an apparently simple superconductor made from inexpensive raw materials, was recently discovered to be superconducting at twice the temperature of any other simple superconductor. The electronic characteristics of MgB2 provide unique opportunities to explore the possibility of improving the material's properties to make them superior to those of any present superconductor. This Focused Research Group (FRG) award provides support for an inter-institutional collaboration between groups at the U. of Wisconsin-Madison (UW), Arizona State U. (ASU), Pennsylvania State U. (PSU), and the U. of Puerto Rico-Mayaguez (UPRM). The project seeks to understand how to make MgB2 attractive for applications. The team has already demonstrated that MgB2 remains superconducting in higher magnetic fields than materials based on Nb. More than 99% of all current superconducting magnets are made from Nb based materials. Superconductivity is vital to many aspects of technology, especially to Magnetic Resonance Imaging (MRI). General Electric, one of the world's largest manufacturers of MRI machines will collaborate on this study. This effort will be implemented by research carried out by graduate research students and amplified by collaboration with the developing materials science program at UPRM and by outreach at the K-12 level to Native American and Hispanic communities in Arizona. The project is supported by the Condensed Matter Physics, Ceramics, and MRSEC programs in the Division of Materials Research, as well as by the Office of Multidisciplinary Activities.


***TECHNICAL ABSTRACT***
Magnesium diboride is a hexagonal layered compound recently found to have a 40K superconducting transition temperature, almost twice as high as any other electron-phonon superconductor. Even more interesting is that MgB2 contains two distinct superconducting gaps that are only weakly coupled to each other. The larger sigma gap is formed by in-plane sigma boron bonds, whereas the smaller pi gap results from pi boron bonds between the Mg and B planes. This inter-institutional Focused Research Group (FRG), consisting of groups at the U. of Wisconsin-Madison (UW), Arizona State U. (ASU), Pennsylvania State U. (PSU), and the U. of Puerto Rico-Mayaguez (UPRM), will address fundamental physics and materials science issues of MgB2 alloys, concentrating on bulk-form samples and damage studies that have great potential for MgB2 technology. The project seeks to understand how the upper critical field is affected by scattering in and perhaps between the sigma and pi bands of MgB2 and how the scattering changes as MgB2 is alloyed or ion irradiated. Bulk form samples will be the primary thrust of the studies at UW and UPRM; transmission electron microscopy will be performed at UW. Researchers at PSU will concentrate on modeling of the alloying process. Ion irradiation and connectivity effects will be the focus of research at ASU. The broader impacts are both technological and educational. The superconducting magnet user community is excited by recent demonstrations that Hc2 of alloyed MgB2 can exceed Hc2 of the Nb-based superconductors, from which virtually all superconducting magnets are presently made. US industry and national laboratories, as well as international academic collaborators, will work with the FRG to explore the full potential of MgB2 for cryocooled magnets in the 10-30K range, as well as ultra high-field magnets beyond the reach of any Nb-based material. Outreach collaborations in research through a recently started UW-UPRM NSF-PREM at UPRM will be further developed and K-12 outreach will start at ASU to Hispanic and Native American communities in Arizona. The project is supported by several programs in the Division of Materials Research, as well as by the Office of Multidisciplinary Activities.

Center for Computational Materials Design (CCMD)

IIP-1034965 Pennsylvania State University (PSU)
IIP-1034968 Georgia Tech (GT)

This is a proposal to renew the Center for Computational Materials Design (CCMD), an I/UCRC center that was created in 2005. The lead institution is Pennsylvania State University, and the research partner is Georgia Tech. The main research mission of the CCMD is to develop simulation tools and methods to support materials design decisions and novel methods for collaborative, decision-based systems robust design of materials.

The intellectual merit of CCMD is based on the integration of multiscale, interdisciplinary computational expertise at PSU and GT. CCMD provides leadership in articulating the importance of integrated design of materials and products to industry and the broad profession of materials engineering; and is developing new methods and algorithms for concurrent design of components and materials.

CCMD has operated successfully in Phase I, and has helped develop a partnership amongst academe, industry and national laboratories. Based on feedback received from the various members, CCMD has outlined in the renewal proposal research thrusts and initiatives for Phase II; and has also identified gaps that will be addressed as research opportunities in Phase II.

CCMD will have a large impact on how industry addresses material selection and development. The expanded university/industry interaction of this multi-university center offers all participants a broader view of material design activities in all sectors. CCMD contributes to US competitiveness in computational materials design by educating new generations of students who have valuable perspectives on fundamental modeling and simulation methods, as well as industry-relevant design integration and materials development. CCMD participates in programs at PSU and GT that support K-12 STEM issues, women and underrepresented groups, undergraduate students, and high school teachers. CCMD plans to disseminate research results via papers, conferences and the CCMD website.

The NSF Sustainable Energy pathways (SEP) Program, under the umbrella of the NSF Science, Engineering and Education for Sustainability (SEES) initiative, will support the research program of Prof. Timothy Anderson and co-workers at the University of Florida, Prof. Zi-Kui Liu and co-workers at Pennsylvania State University, and Prof. Angus Rockett and co-workers at the University of Illinois at Urbana-Champaign to develop new Earth abundent-based thin film photovoltaic materials. The use of Earth abundent materials is required for a sustainable energy pathway that includes significant photovoltaic (PV) electricity generation capacity. The recent demonstration of a 10.1% efficient cell using earth abundant Cu2ZnSn(SxSe1-x)4 (CZTSe) has elevated this absorber to one of the most promising sustainable material for high penetration PV. Developing a fundamental knowledge of the material properties of CZTS is needed to underpin its rapid development. The aim of this program is to define a self-consistent framework that describes the thermochemistry and reaction kinetics for the CZTSSe system. This framework can then inspire intelligent process innovation, for example, rapid CZTSSe synthesis pathways, precursor structures defining optimal Se distribution, or processing conditions minimizing bulk recombination centers. The CALculation of PHAse Diagram (CALPHAD) approach will be used to assess experimental data in the literature, supplemented by first-principles calculations of unknown thermochemical properties, to produce a full description of the thermodynamic properties of this 5-component system. The assessment will also provide insight into the point defect chemistry necessary to link processing conditions to device performance. Reaction pathways will be investigated using high temperature X-ray diffraction (HTXRD) experiments coupled with materials characterization and first-principles calculations to assist in creating a species mobility database for this earth abundant system.

Significant adoption of sustainable PV would clearly have a tremendous global impact. The greatest benefits accrue to the >1 billion people without reliable or any access to electricity. Two programs are proposed to facilitate bringing PV to those areas. An economist with considerable expertise in electricity generation in developing countries will conduct economic and behavioral studies to better understand the barriers to PV deployment in the developing world. This activity will be complemented by engaging undergraduate multidisciplinary capstone design teams to define affordable and reliable individual PV systems, while collaborating with PV manufacturers. Each PhD student will participate in an internship at one of our collaborating national labs as well as engage an undergraduate student in their research. The team also has an interest in new faculty development. A workshop designed to help new faculty start quickly, now being taught to new and prospective chemical engineer faculty, will be adapted for the chemistry and materials science communities.

Ultimately, solar energy is the principal source of our energy, producing our fossil fuels, biomass, wind, and solar thermal resources, and of course, electricity by direct conversion using a solar cell. The cost of solar panels is decreasing rapidly as we learn how to manufacture more efficient panels at large scale. Indeed the historical price has decreased 22% every time the installed world capacity doubles, and they are now providing electricity that is less than the retail cost of electricity in many parts of the world. The installed capacity of solar panels world-wide, however, is very small percentage of the total production (<1%). The panel manufacturing cost is mainly in the cost of the materials and building the manufacturing plant. At high deployment of solar panels, the limited supply/high cost of some elements will prohibit their use. This research will focus on solar cells using the earth abundant elements copper, zinc, tin, sulfur and a possibly selenium to ensure cheap materials cost. The rate of manufacturing thin film solar cells is normally limited by the rate to form the compound that absorbs the light. This program aims to understand how to make these materials at very high rates. Higher rates translate into higher throughput of cells, and thus more output for a manufacturing plant.

Technical Abstract

Recently, a new class of high-energy-density, Li- and Mn-rich layered cathode materials has been discovered. The project aims to build the fundamental knowledge base needed to progress towards design and processing of the materials with desired properties through integrated first-principles calculations, CALPHAD modeling, materials processing, and battery assembling and testing. This fundamental knowledge base also builds the genome foundation to discover new cathode materials. The new cathode material resides in a multi-component space of xLi2MnO3ª(1-x)LiMO2 with M being alloying elements including Mn, Co, and Ni. In the project, first-principles calculations will be used to systematically investigate the effects of these common alloying elements and potential outliers on electronic structures and charge transfers and predict thermodynamic properties of individual phases as a function of temperature and compositions. CALPHAD modeling will be utilized to establish phase relations and optimize the composition space (x and M) for superior charging-discharging performance. To validate the predictions from first-principles calculations and CALPHAD modeling, cathode materials will be synthesized with tailored composition and assemble coin cells to test battery performance. The project objectives are:

1.Establish fundamental understanding of effects of alloying elements and search for potential outliers;
2.Develop a thermodynamic description of the Li-Mn-Co-Ni-O system plus potential outliers;
3.Synthesize and characterize cathode materials and test battery performance based on computational modeling and feedback to improve databases.


Nontechnical Summary

The development of new materials and the capability of tailoring existing materials to meet new and demanding applications are critical for continued improvements in the quality of human life. Materials are a determining factor in the global competitiveness of the U.S. manufacturing industry as materials account for up to half of the costs of most manufactured products. Li-ion rechargeable batteries are the key constituent for low cost and high-energy-density storages needed for numerous applications such as electronic devices and electric vehicles. The development of novel cathodes is critical because of the limitations of cost and energy density for cathodes used in current rechargeable Li-ion batteries. Recently, a new class of high-energy-density, Li- and Mn-rich layered cathode materials has been discovered. The project aims to build the fundamental knowledge base needed to progress towards design and processing of the materials with desired properties through integrated first-principles calculations, thermodynamic modeling, materials processing, and battery assembling and testing. This fundamental knowledge base also builds the genome foundation to discover new cathode materials.
The proposal's intellectual merit lies on its collaborative, synergistic approaches between theory, computation, and experiments to rapidly build a chemistry-processing-structure-property-performance knowledge base for the Li- and Mn-rich layered cathode materials. This integrated approach will be based on the combined expertise in simulations, syntheses, and evaluation of battery materials. The research project aims to move the low cost and high-energy-density cathode materials research in the US to a new level by further building the foundation to answer fundamental questions that can only be addressed efficiently via combined computational and experimental methodology. These include: what is the best combination of Li/Mn/M layers in terms of cost and performance? what are the composition/temperature variations for their robust processing? and what are the potential outliers of alloying elements for superior performances?
Broader impacts include following aspects, in addition to economic impact of low-cost and high-energy-density cathode materials on battery manufacturing, a) educate students to be professionals mastering both innovative computational and experimental approaches with cross-disciplinary knowledge of materials and batteries; b) encourage students to make presentations at professional meetings to improve communication skills; c) foster students' writing skills through peer reviewed journal publications; d) participate in activities to broaden the participation of underrepresented groups through the SEEMS (Summer Experience in Earth and Mineral Science) programs for high school students and WISER (Women in Science and Engineering Research) program for first year students, e) contribute to new materials research paradigm in shortening the time for developing new materials and improving existing materials to minimize the cost to the society and the negative impact to the environment, and increasing the competitiveness of US manufacturing.

The research objective of this Designing Materials to Revolutionize and Engineer our Future (DMREF) project is to establish a fundamental knowledge base to enable accelerated design of advanced low-modulus (20-30 GPa to match that of bone) Ti alloys for biomedical prosthetic devices. The team will: 1) employ first-principles calculations to predict elastic modulus and thermodynamic phase stability of the Ti-Mo-Nb-Ta-Zr system; 2) use high-throughput diffusion multiples and micron resolution materials property measurement tools to obtain large amount of materials property data; 3) establish CALPHAD-type databases of thermodynamics and elastic modulus for the 5-component system; and 4) employ direct laser deposition to validate model predictions. Integration of these computational and experimental tools will achieve a multifold increase in the efficiency of establishing composition-structure-property relationships in comparison with traditional methods based on individual alloys, and thus will fundamentally change the way future materials databases are established.

An aging population with an extended lifespan is demanding more and more biomedical prosthetic devices, such as knee and hip replacements, to sustain an active lifestyle. Biocompatible Ti alloys are considered to be one of the best options for such implants. The ability to tailor the composition and microstructure to design alloys to meet specific property requirements is the goal of the Materials Genome Initiative (MGI) in general and the purpose of this study in particular. The approach developed here will significantly speed up data generation for rapid establishment of digital materials property databases for accelerated design of new materials. The timely design of high-performance materials is critical to the global competitiveness of US manufacturing. All digital data generated from this study will be published and archived in the MGI informatics infrastructure. This project will educate next-generation materials engineers who will master both advanced computational and experimental approaches to better serve the society. The research and education of this study will also help usher in a new paradigm of materials innovation where materials design is conducted by up-front simulations followed by key validation experiments in contrast to the current approach that is based on experimental iterations followed by mechanistic characterization.

Nickel-based superalloys have a number of critical applications relevant to the US economy and national defense, including commercial and military jet engines, gas turbines, and power generators. These materials can operate at relatively high temperatures, but often are limited in their application by their poor performance at the highest operating temperatures. In order to design superalloys that can withstand ever increasing temperatures, it is necessary first to understand what happens at the microscopic level in these alloys. This award supports fundamental research to understand the microscopic processes that control superalloy behavior at high temperatures, and the development of robust computational tools to predict this behavior and design high-performance materials. The approach takes advantage of a unique high-throughput approach to experimental characterization, coupled with a data-driven computational approach to enable the calculation of phase stability in these superalloys. This project will educate next-generation materials scientists and engineers with strong materials processing expertise and both computational and experimental skills to better serve the U.S. manufacturing industry.

The overall objective of this research is to establish a new paradigm for reliable and effective assessments of the thermodynamic stability of intermetallic phases during process. This objective will be achieved by: 1) performing high-throughput first-principles calculations of sublattice stabilities and atomic interaction energetics in individual sublattices of the complex topological close-packed (TCP) phases with multiple sublattices (Wyckoff sites) that cannot be directly measured experimentally; 2) exploring innovative and systematic strategies to enable facile incorporation of first-principles results into calculation of phase diagrams ; 3) making high-throughput diffusion multiples to obtain reliable phase diagrams of ternary systems critical to TCP phase stability evaluation, and employing the data to optimize the Gibbs energy parameters of the phases; and 4) expanding the infrastructure capabilities to seamlessly use both first-principles calculation results and experimental data to perform high-throughput phase diagram calculations, including uncertainty quantifications. In addition to establishing a new paradigm in phase diagram modeling, the outcomes of this study include valuable phase diagrams of important ternary systems obtained from diffusion multiples, and a set of reliable Gibbs energy functions for the TCP phases modeled from both experimental phase diagrams and density functional theory (DFT) predictions that can be incorporated into thermodynamic databases for Ni-based superalloys.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

This grant will support fundamental research on controlling phases generated at the welded interface between dissimilar metals. Joining dissimilar metals has become increasingly important for creating lightweight, high-performance, and economic structures in various industries. However, the chemical reactions between two dissimilar metals during welding can generate harmful phases like brittle intermetallic compounds. This award aims to address scientific and technical challenges in controlling the metallurgical phase formation in the weld by introducing a suitable interposing metal to create a nonlinear alloy composition pathway through the joint thickness. The situation is illustrated by the laser welding (LW) of aluminum and copper. These two metals are major materials in the assembly of battery cells, which are in high demand for electric vehicles. This research will enable engineers to design and transform the metallic phases in the weld in a controllable fashion with more freedom than when limited to the two base metals. In turn, this award can broaden the adoption of dissimilar metal joints in industries such as automotive, aerospace, power generation, marine application, medical devices, and information technology. This research involves several disciplines, including manufacturing, materials science, multiscale simulations, and machine learning. The multi-disciplinary approach will broaden the participation of underrepresented groups in research and positively impact both undergraduate and graduate education. <br/><br/>The investigators will design and realize optimal bonding phases with a data-driven paradigm to learn and control metallurgic phases in dissimilar metal joints. The research team will conduct multiscale simulations for data generation to establish data-driven models which provide high-fidelity welding predictions. Metallurgical reactions at the bonding interface will be explained using calculation of phase diagrams (CALPHAD)-based analysis, correlation analysis and molecular dynamics simulations. Machine learning will be used to provide inverse design of the nonlinear modification and laser welding processes, and simulation and designs will be validated experimentally. This research will fill the knowledge gap in understanding the interactions between LW energy inputs, keyhole dynamics, phase formation, and transition from liquids to solids under different LW conditions. It will build an efficient methodology, via thermodynamics and kinetics, to predict preferred phases and properties to meet a joint’s requirements.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

This project is funded by Pathways to Enable Open-Source Ecosystems (POSE) which seeks to harness the power of open-source development for the creation of new technology solutions to problems of national and societal importance. OSEMatS aims to scope preparatory activities to enable the growth of existing open-source materials research tools into a sustainable and robust Open-Source Ecosystem (OSE) that will have broad and lasting scientific and societal impacts. OSEMatS stems from the team’s nonprofit Materials Genome Foundation (MGF) incorporated in 2018 for “promoting computational approaches in science and engineering through organizing workshops and supporting the development of computational tools and databases”. The existing open-source tools on GitHub developed by the team are PyCalphad and ESPEI (Extensible Self-optimizing Phase Equilibria Infrastructure) for the modeling and applications of thermodynamics, which is the most fundamental component of materials science and engineering, through the calculation of phase diagram (CALPHAD) method which is the backbone of the Integrated Computational Materials Engineering (ICME) and Materials Genome Initiative (MGI). An advisory council will be established within the MGF and will include key contributors and stakeholders associated with PyCalphad and related projects, as well as external subject matter experts in open-source governance. The near-term goal of OSEMatS is to develop and execute a strategic plan for a sustainable PyCalphad and ESPEI OSE using an organized and intentional approach through joint efforts between MGF and The Pennsylvania State University (PSU). The long-term vision of OSEMatS seeks to promote the computational thermodynamics library PyCalphad as a foundational component of scientific computing within materials science, supporting a robust portfolio of associated software projects and user cases to enable the integrated computational-experimental fundamental research and data-driven discovery and inverse-design of materials with emergent functionalities.<br/><br/>OSEMatS will engage in several planning and outreach activities with the goal of devising a path to sustainability. OSEMatS will (i) empower its user community to become contributors, mentors, and technical leaders through interactive workshops; (ii) ensure a low barrier for onboarding of new projects by providing access to MGF organizational resources commensurate with transparent success criteria and periodic evaluation processes; and (iii) organize outreach activities and events within OSEMatS in a manner consistent with a commitment to inclusion, diversity, equity, and accessibility (IDEA). To organize outreach activities coherently, the team incorporated the nonprofit MGF in 2018, aiming to search for a sustainability model to continue the development of OSE in alignment with the POSE program for the creation and maintenance of infrastructure needed for efficient and secure operation of the OSEMatS. PyCalphad and ESPEI have demonstrated their global impacts on computational materials science for universities, national laboratories, and commercial companies. The POSE program will provide necessary support to kickstart a path to sustainability for OSEMatS, based on the open-source PyCalphad and ESPEI, along with many new ones on the way from the PI’s group and in the community through increased coordination of developer contributions and a more focused route to impactful technologies. OSEMatS will enable better fundamental understanding of materials and efficient discovery and design of advanced materials to benefit our society. The team will actively engage students in these activities via various educational and outreach programs at PSU as done in the past such as the Summer Research Opportunity Program for high school students, the Women in Science and Engineering Research program, and student chapters of various professional societies.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.