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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Image-Based Failure Assessment of Li-Ion Batteries

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. In this work, a digital twin is created to investigate the performance of a heterogeneous Li-ion battery cathode and simulate degradation accumulation. Pixel-based model construction is used to represent the complex material geometries from microstructural images supplied by the National Renewable Energy Laboratory (NREL). Because of the expected large deformation and crack opening, the reproducing kernel particle method (RKPM), a meshfree method with discretization at the image pixels, is used to approximate the field variables: electrostatic potential, concentration, and displacement. An interface modified reproducing kernel (IM-RK) is constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. IM-RK is additionally used to inform how crack evolution in turn affects the coupled electro-chemo-mechanical behavior of the Li-ion battery cathode.

image-based modeling↗
DOE OSTI2026

Structural Heterogeneity in Medium-Entropy AgMnSbPbTe 4 for Glassy Thermal Transport and High Thermoelectric Performance

Medium-entropy semiconductors represent a unique category of entropy-engineered materials. They possess a considerable level of randomness in atomic mixing, although this is not sufficient to conclusively achieve single-phase structure stabilization, in contrast to high-entropy materials. This introduces strong competition between the formation of different phases, which can potentially lead to structural heterogeneity. Here, in this work, we uncover endotaxial nanoprecipitates in the microscopically identified homogeneous medium-entropy semiconductor AgMnSbPbTe 4 . These nanoprecipitates initially crystallize in a cubic phase $(Fm\bar{3}m)$ within kinetically stabilized AgMnSbPbTe 4 , subsequently evolving into a thermodynamically stable monoclinic phase $(P2_1/c)$ during thermal annealing while maintaining an endotaxial relationship with the matrix lattice. This nanophase segregation and the resultant lattice mismatch at interfaces introduce strain fluctuations up to 5% at intervals of 20 nm across the entire microstructure. Within the matrix phase, atomic displacement of up to 23 pm was observed. This structural heterogeneity results in glass-like thermal transport behavior, achieving an ultralow lattice thermal conductivity κ L = 0.312 Wm –1 K –1 at 800 K, which is in accordance with the amorphous limit predicted by the Cahill model. The synergy of band convergence effect and well-maintained carrier mobility leads to a maximum ZT of 1.72 at 800 K and an average ZT avg of 1.02 over the temperature range of 300–825 K. This study highlights that the underexplored structural heterogeneity in medium-entropy semiconductors can potentially yield beneficial phenomena, such as the phonon-glass electron-crystal transport behavior in this case, which holds promise for advancing thermoelectric applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Progress towards a phenomenological picture and theoretical understanding of glassy dynamics and vitrification near interfaces and under nanoconfinement

The nature of alterations to dynamics and vitrification in the nanoscale vicinity of interfaces-commonly referred to as "nanoconfinement" effects on the glass transition-has been an open question for a quarter century. We first analyze experimental and simulation results over the last decade to construct an overall phenomenological picture. Key features include the following: after a metrology- and chemistry-dependent onset, near-interface relaxation times obey a fractional power law decoupling relation with bulk relaxation; relaxation times vary in a double-exponential manner with distance from the interface, with an intrinsic dynamical length scale appearing to saturate at low temperatures; the activation barrier and vitrification temperature T-g approach bulk behavior in a spatially exponential manner; and all these behaviors depend quantitatively on the nature of the interface. We demonstrate that the thickness dependence of film-averaged T-g for individual systems provides a poor basis for discrimination between different theories, and thus we assess their merits based on the above dynamical gradient properties. Entropy-based theories appear to exhibit significant inconsistencies with the phenomenology. Diverse free-volume-motivated theories vary in their agreement with observations, with approaches invoking cooperative motion exhibiting the most promise. The elastically cooperative nonlinear Langevin equation theory appears to capture the largest portion of the phenomenology, although important aspects remain to be addressed. A full theoretical understanding requires improved confrontation with simulations and experiments that probe spatially heterogeneous dynamics within the accessible 1-ps to 1-year time window, minimal use of adjustable parameters, and recognition of the rich quantitative dependence on chemistry and interface. Published under license by AIP Publishing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Adrastea: An Efficient FPGA Design Environment for Heterogeneous Scientific Computing and Machine Learning

We present Adrastea, an efficient FPGA design environment for developing scientific machine learning applications. FPGA development is challenging, from deployment, proper toolchain setup, programming methods, interfacing FPGA kernels, and more importantly, the need to explore design space choices to get the best performance and area usage from the FPGA kernel design. Adrastea provides an automated and scalable design flow to parameterize, implement, and optimize complex FPGA kernels and associated interfaces. We show how virtualization of the development environment via virtual machines is leveraged to simplify the setup of the FPGA toolchain while deploying the FPGA boards and while scaling up the automated design space exploration to leverage multiple machines concurrently. Adrastea provides an automated build and test environment of FPGA kernels. By exposing design space hyper-parameters, Adrastea can automatically search the design space in parallel to optimize the FPGA design for a given metric, usually performance or area. Adrastea simplifies the task of interfacing with the FPGA kernels with a simplified interface API. To demonstrate the capabilities of Adrastea, we implement a complex random forest machine learning kernel with 10,000 input features while achieving extremely low computing latency without loss of prediction accuracy, which is required by a scientific edge application at SNS. We also demonstrate Adrastea using an FFT kernel and show that for both applications Adrastea is able to systematically and efficiently evaluate different design options, which reduced the time and effort required to develop the kernel from months of manual work to days of automatic builds.

Young, Aaron↗
DOE OSTI2025

Nickel hydroxide–nickel carbonate competitive growth on carbonate surfaces

The thermodynamic and kinetic factors controlling the competitive heterogeneous nucleation and growth of ubiquitous metal carbonate and hydroxide phases are poorly understood. In this work, calcite (CaCO 3 ) and magnesite (MgCO 3 ) powders were reacted with NiCl 2 (0–600 μM) for 7 days at 22 °C and 5 °C. The reacted powders were analyzed with X-ray photoelectron spectroscopy (XPS), scanning electron microscopy, and energy-dispersive X-ray spectroscopy to characterize the Ni surface precipitates formed. Evidence from these techniques pointed to the formation of mixed Ni carbonate-Ni hydroxide amorphous surface precipitates. On calcite, XPS detected primarily Ni(OH) 2 despite the initial solutions being more supersaturated with respect to gaspéite (NiCO 3 ) than to theophrastite (Ni(OH) 2 ) by a factor of 17–18. In contrast, NiCO 3 was the dominant component detected by XPS on magnesite in the same conditions. Decreasing the temperature had the effect of increasing the proportion of NiCO 3 to the detriment of Ni(OH) 2 . The experimental observations were consistent with low lattice/cation size mismatch favoring NiCO 3 nucleation and temperature most influencing Ni(OH) 2 nucleation. Comparison to previous work on Co-reacted powders indicated the differences in lattice/cation size mismatch and/or water exchange rate impacted the composition of the surface precipitates more than the relative thermodynamic stabilities of the competing minerals. This work explored the heterogeneous growth regime of Ni carbonate and hydroxide phases on carbonate surfaces and shed light on the factors that control the competition between surface precipitates when mineral surfaces are in contact with aqueous solutions supersaturated with respect to multiple mineral phases. In conclusion, these results contribute to geochemists’ efforts toward interpreting data from geochemical systems with elevated Ni concentrations, improving Ni environmental remediation and recovery strategies, and predicting the fate and transport of Ni in geochemical systems.

Heterogeneous nucleation↗
DOE OSTI2026

Melatonin-Induced Modulation of Cholesterol-Enriched Model Neuronal Membranes

Melatonin, a hormone primarily produced by the brain’s pineal gland, not only regulates circadian rhythms, but also influences the structural and biophysical properties of neuronal membranes. Its amphiphilic nature enables direct incorporation into lipid bilayers and preferential interactions with cholesterol-rich lipid rafts, critical hubs for cellular signaling and membrane organization. Despite increasing recognition of its membrane activity, the molecular basis of melatonin’s interactions with coexisting liquid-ordered (L o ) and liquid-disordered (L d ) phases remains unclear. Here, in this study, we combine small-angle neutron scattering (SANS) and all-atom molecular dynamics simulations to examine model neuronal membranes composed of DSPC, DOPC, POPC, and cholesterol. Our results show that melatonin preserves domain morphology while adopting distinct orientations within the bilayer and at the membrane interface, allowing both lateral and transmembrane bridging across lipid phases. These findings establish the molecular underpinnings of melatonin’s modulation of membrane heterogeneity and provide strong support for its receptor-independent actions.

atomistic simulations↗
DOE OSTI2026

Fidelity Comparison of Time-Bin and Fock State Encoding in Hybrid Quantum Systems Under Channel and Transduction Effects

Future quantum networks are expected to integrate a heterogeneous combination of quantum systems, owing to the diverse advantages offered by different physical platforms in terms of scalability, coherence times, and interfacing capabilities. Within the context of this emerging quantum communication paradigm, this paper presents an analytical comparison of two photonic encoding schemes—time-bin and Fock state (single rail)—in hybrid quantum systems where flying qubits are entangled with stationary matter qubits. We evaluate their resilience against fiber channel and quantum transduction effects by calculating the fidelity of the final states relative to their ideal forms. Employing the characteristic function approach, we derive analytical fidelity expressions and investigate their dependence on parameters such as transmissivity, noise levels, fiber length, and source generation success probability. Additionally, we simulate the scenario with a dedicated QuTiP software implementation to verify the validity of the theoretical models. Our findings reveal that due to its inherent single-mode structure, the Fock state encoding consistently outperforms time-bin encoding in fidelity, as this structure significantly minimizes susceptibility to losses compared to the two-mode nature of the time-bin scheme. This analysis offers valuable insights for future hybrid quantum communication and information processing applications.

Fiorini, Francesco [Pisa U.]↗
DOE OSTI2021

SV-Sim: Scalable PGAS-based State Vector Simulation of Quantum Circuits

High-performance quantum circuit simulation in a classic HPC is still imperative in the NISQ era. Observing that the major obstacle of scalable state-vector quantum simulation arises from the massively fine-grained irregular data-exchange with remote nodes, in this paper we present SV-Sim to apply the emerging PGAS-based communication models (i.e., direct peer access for intra-node CPUs/GPUs and SHMEM for inter-node CPU/GPU clusters) for efficient scalable quantum circuit simulation. Through an orchestrated device functional pointer design, SV-Sim is able to abstract the quantum gate sets across various heterogeneous backends, including IBM/Intel/AMD CPUs, NVIDIA /AMD GPUs, and Intel MIC, in a unified framework, but still asserting outstanding performance and tractable interface to higher-level quantum programming environments, such as IBM Qiskit, Microsoft Q\# and Google Cirq. Circumventing the disability of polymorphism in GPUs and leveraging the device-initiated one-sided communication, SV-Sim can process dynamically synthesized quantum circuit in a single GPU/CPU kernel without the need of expensive JIT or runtime branching, significantly improving the performance and simplifying the programming complexity for the emerging variational quantum algorithms. Evaluations on NVIDIA A100-DGX-1, V100-DGX-2, AMD MI100, ALCF Theta, and OLCF Summit HPCs show that SV-Sim can delivery scalable performance on various state-of-the-art HPC platforms, offering a useful tool for quantum algorithm validation and verification.

Li, Ang↗
DOE OSTI2022

Improved Cross Section Generation Capability of Griffin in FY22

The Griffin code is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor multiphysics analysis application jointly developed by Idaho National Laboratory and Argonne National Laboratory. The code includes a variety of deterministic steady-state transport solvers for fixed source, k-eigenvalue, adjoint, and subcritical multiplication as well as transient solvers for spatial dynamics with the improved quasi-static method. Griffin uses cross section data in the ISOXML format generated from external deterministic or Monte Carlo cross section generation codes. In recent years, the MC 2 -3 modules have been added to Griffin for fast reactor cross section generation, and the self-shielding application programming interface (SSAPI) was implemented in the ISOXML module for thermal reactor cross section generation. The on-the-fly slowing down method and double-heterogeneity treatment have been implemented to SSAPI and verified against particulate fuel-bearing graphite-moderated thermal reactor problems with high accuracy. This year, work has been focused on improving the cross section generation capability of ISOXML and streamlining the cross section generation procedures. In addition, the form function data were added to ISOXML in order to support the pin power reconstruction capability that was newly implemented in Griffin in this fiscal year. To facilitate the cross section generation using MC 2 -3 and SSAPI in Griffin, the cross section generation workflows have been set up for both fast and thermal spectrum reactors. The MOOSE action system tool was devised for fast spectrum problems, and the MOOSE stochastic tool was adopted to the branch calculation procedure for thermal spectrum problems. Meanwhile, to ensure the accuracy of group-constants, the thermal up-scattering kernel calculator accounting for resonance scattering was implemented in ISOXML, demonstrating the accurate computation of a Doppler-broadened scattering kernel of any Legendre order within a reasonable timescale. Other aspects of ISOXML, such as deletion solver and data, documentation, ISOXML file management, and the interface for Mixture, were improved as well.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Bespoke Liquid/Liquid Interfaces (Final Technical Report)

The goal of DE-SC0001815 was to advance the basic science of liquid:liquid interface formation, to develop a deeper understanding of the mechanisms of phase separation and the essential relationships between solution composition, organization and dynamics that underlie the kinetic regime of solvent extraction. This included learning how interfacial organization and dynamics alters the properties of the primary coordination sphere of ions and the free energy of transport of ions complexes across a phase boundary. We relied primarily upon classical molecular dynamics studies to determine the equilibrium ensembles of these complex systems, but also utilized ab-initio MD and cluster-based density functional theory (DFT) calculations when more detailed investigation of the electronic structure was needed. We continued development of graph-theory based analyses to elucidate hierarchical correlations and expanded into geometric topology methods to quantify the collectively organized structures that can organize at a liquid/liquid interface during solute transport. One of the main conclusions was from the observation of two distinct mechanisms for solute transport - those that derive from amplifications of interfacial heterogeneity and surface roughness, and those wherein surface roughness has been dampened and instead collectively organized macrostructures work to bring solutes into the organic phase. It was our aim to create a concrete chemical model of the underlying driving forces behind interfacial primary and secondary structure formation and to map out the energetic features of solute transport so that tailored liquid/liquid can be developed that have characteristic kinetic features associated with mass transport.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Machine learning dielectric screening for the simulation of excited state properties of molecules and materials

Accurate and efficient calculations of absorption spectra of molecules and materials are essential for the understanding and rational design of broad classes of systems. Solving the Bethe–Salpeter equation (BSE) for electron–hole pairs usually yields accurate predictions of absorption spectra, but it is computationally expensive, especially if thermal averages of spectra computed for multiple configurations are required. We present a method based on machine learning to evaluate a key quantity entering the definition of absorption spectra: the dielectric screening. We show that our approach yields a model for the screening that is transferable between multiple configurations sampled during first principles molecular dynamics simulations; hence it leads to a substantial improvement in the efficiency of calculations of finite temperature spectra. We obtained computational gains of one to two orders of magnitude for systems with 50 to 500 atoms, including liquids, solids, nanostructures, and solid/liquid interfaces. Importantly, the models of dielectric screening derived here may be used not only in the solution of the BSE but also in developing functionals for time-dependent density functional theory (TDDFT) calculations of homogeneous and heterogeneous systems. Overall, our work provides a strategy to combine machine learning with electronic structure calculations to accelerate first principles simulations of excited-state properties.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Gas-Phase Temperature Mapping of Evaporating Microdroplets

Evaporation is a ubiquitous and complex phenomenon of importance to many natural and industrial systems. Evaporation occurs when molecules near the free interface overcome intermolecular attractions with the bulk liquid. As molecules escape the liquid phase, heat is removed, causing evaporative cooling. The influence of evaporative cooling on inducing a temperature difference with the surrounding atmosphere as well as within the liquid is poorly understood. Here, we develop a technique to overcome past difficulties encountered during the study of heterogeneous droplet evaporation by coupling a piezo-driven droplet generation mechanism to a controlled micro-thermocouple to probe microdroplet evaporation. The technique allowed us to probe the gas-phase temperature distribution using a micro-thermocouple (50 μm) in the vicinity of the liquid–vapor interface with high spatial (±10 μm) and temporal (±100 ms) resolution. We experimentally map the temperature gradient formed surrounding sessile water droplets having varying curvature dictated by the apparent advancing contact angle (100° ≲ θ ≲ 165°). The experiments were carried out at temperatures below and above ambient for a range of fixed droplet radii (130 μm ≲ R ≲ 330 μm). Our results provide a primary validation of the centuries-old theoretical framework underpinning heterogeneous droplet evaporation mediated by the working fluid, substrate, and gas thermophysical properties, droplet apparent contact angle, and droplet size. We show that microscale droplets residing on low-thermal-conductivity substrates such as glass absorb up to 8× more heat from the surrounding gas compared to droplets residing on high-thermal-conductivity substrates such as copper. Finally, our work not only develops an experimental understanding of the heat transfer mechanisms governing droplet evaporation but also presents a powerful platform for the study and characterization of liquid–vapor transport at curved interfaces wetting and nonwetting advanced functional surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Modeling Microstructural Effects on Heterogeneous Temperature Fields within Polycrystalline Explosives

The paper addresses the role of crystal anisotropy on the evolution of heterogeneous temperature fields in plastic-bonded explosives (PBXs) under conditions of weak shock. The modeling approach is based on simplified idealizations of PBX microstructure including RDX grains and estane binder regions subjected to velocity boundary conditions representative of impact conditions in situ. The constitutive description of the microstructure constituents includes a dislocation-based, anisotropic, single crystal plasticity model for the explosive grains and a linear viscoelastic model to represent the estane binder. Large suites of simulations were used to systematically study the correlation in heating of the grains with local wave dynamics, crystal orientation, and the microstructural neighborhood. These correlations were identified through the selection of characteristics of crystal anisotropy including oriented wave speeds and Taylor factor. A key observation is that the wave dispersion within a certain distance from the impact interface plays a dominant role in the temperature field. Beyond this distance, individual crystal orientations play a more dominant role, but cannot entirely account for the observed heterogeneity without consideration of the local microstructure neighborhood.

42 ENGINEERING↗
DOE OSTI2022

Metal–Metal Oxide Catalytic Interface Formation and Structural Evolution: A Discovery of Strong Metal–Support Bonding, Ordered Intermetallics, and Single Atoms

In-depth investigation of metal–metal oxide interactions and their corresponding evolution is of paramount importance to heterogeneous catalysis as it allows the understanding and maneuvering of the structure of catalytic motifs. Herein, using a series of core/shell metal/iron oxide (M/FeO x , M = Pd, Pt, Au) nanoparticles and through a combination of in situ and ex situ electron and X-ray investigations, we revealed anomalous and dissimilar M–FeO x interactions among different systems under reducing conditions. Further, Pd interacts strongly with FeO x after high-temperature reductive treatment, featured by the formation of Pd single atoms in the FeO x matrix and increased Pd–Fe bonding, while Pt transforms into ordered PtFe intermetallics and Pt single atoms immediately upon the coating of FeO x . In contrast, Au does not manifest strong bonding with FeO x . As a proof of concept of tailoring metal–metal oxide interactions for catalysis, optimized Pd/FeO x demonstrates 100% conversion and 86.5% selectivity at 60 °C for acetylene semihydrogenation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Exceptional fracture toughness of CrCoNi-based medium- and high-entropy alloys at 20 kelvin

Medium- and high-entropy alloys based on the CrCoNi-system have been shown to display outstanding strength, tensile ductility and fracture toughness (damage-tolerance properties), especially at cryogenic temperatures. Here we examine the J Ic and (back-calculated) K JIc fracture toughness values of the face-centered cubic, equiatomic CrCoNi and CrMnFeCoNi alloys at 20 K. At flow stress values of ~1.5 GPa, crack-initiation K JIc toughnesses were found to be exceptionally high, respectively 235 and 415 MPa√m for CrMnFeCoNi and CrCoNi, with the latter displaying a crack-growth toughness K ss exceeding 540 MPa√m after 2.25 mm of stable cracking, which to our knowledge is the highest such value ever reported. Characterization of the crack-tip regions in CrCoNi by scanning electron and transmission electron microscopy reveal deformation structures at 20 K that are quite distinct from those at higher temperatures and involve heterogeneous nucleation, but restricted growth, of stacking faults and fine nanotwins, together with transformation to the hexagonal closed-packed phase. The coherent interfaces of these features can promote both the arrest and transmission of dislocations to generate respectively strength and ductility which strongly contributes to sustained strain hardening. Indeed, we believe that these nominally single-phase, concentrated solid-solution alloys develop their fracture resistance through a progressive synergy of deformation mechanisms, including dislocation glide, stacking-fault formation, nano-twinning and eventually in situ phase transformation, all of which serve to extend continuous strain hardening which simultaneously elevates strength and ductility (by delaying plastic instability), leading to truly exceptional resistance to fracture.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Interactions between Surface Chemistry and Gas-Phase Combustion: New Optical Tools for Probing Flame-Wall Interactions and the Heterogeneous Chemistry of Soot Growth and Oxidation in Flame. Final report

Some of the most stubborn and technologically critical problems in combustion are dominated by heterogeneous processes. While purely gas-phase combustion systems have been the subject of intense theoretical and experimental study, combustion phenomena occurring at interfaces are far less understood. This is partly caused by the lack of experimental approaches capable of probing locations very close to an interface, especially in the hostile environment of combustion. For laser-based optical techniques, measurements taken near interfaces are often complicated by laser scattering from the surface interfering with relatively weak signals. Further, for measurements intended to probe molecular species adsorbed at the interface between a gas-phase combustion reaction and a condensed phase material, signals are generally overwhelmed by contributions from the bulk phases, causing the small contribution from the interfacial molecular species to be undetectable. Our goal in this project has been to develop new optical tools for imaging chemical species, temperature, and surface species at and near surfaces or interfaces of relevance to combustion. We have placed focus on the development and refinement of ultrafast techniques such as femtosecond coherent Raman imaging and femtosecond/picosecond sum-frequency generation (SFG) scattering, as well as the models used to simulate such spectra under differing conditions of pressure and chemical speciation. The two physical phenomena initially targeted for study in this project were flamewall interactions, and the growth of particulates in flames.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Shaping the Future of Self-Driving Autonomous Laboratories Workshop

The "Shaping the Future of Self-Driving Autonomous Laboratories" workshop, held in Denver on November 7-8, 2024, brought together leading experts from materials science and computing to address the growing need to revolutionize scientific research through AI-driven autonomous laboratories. The workshop identified critical challenges, including the integration of heterogeneous data, development of AI systems that understand fundamental physical principles, and comprehensive safety protocols. Key recommendations emerged around developing universal laboratory equipment interfaces, implementing automated metadata collection systems, and creating hybrid AI approaches that combine data-driven learning with scientific principles. The workshop emphasized maintaining human oversight while leveraging automation, transforming scientific education to prepare the next generation of researchers, and establishing a national consortium leveraging DOE facilities as anchors for broader collaboration with academia and industry. Participants stressed the urgency of addressing the growing disconnect between human decision-making timescales and modern instrumentation capabilities, highlighting the need for strategic automation while preserving essential human insight and oversight in the research process.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Orchestration of materials science workflows for heterogeneous resources at large scale

In the era of big data, materials science workflows need to handle large-scale data distribution, storage, and computation. Any of these areas can become a performance bottleneck. We present a framework for analyzing internal material structures (e.g., cracks) to mitigate these bottlenecks. We demonstrate the effectiveness of our framework for a workflow performing synchrotron X-ray computed tomography reconstruction and segmentation of a silica-based structure. Our framework provides a cloud-based, cutting-edge solution to challenges such as growing intermediate and output data and heavy resource demands during image reconstruction and segmentation. Specifically, our framework efficiently manages data storage, scaling up compute resources on the cloud. The multi-layer software structure of our framework includes three layers. A top layer uses Jupyter notebooks and serves as the user interface. A middle layer uses Ansible for resource deployment and managing the execution environment. A low layer is dedicated to resource management and provides resource management and job scheduling on heterogeneous nodes (i.e., GPU and CPU). At the core of this layer, Kubernetes supports resource management, and Dask enables large-scale job scheduling for heterogeneous resources. The broader impact of our work is four-fold: through our framework, we hide the complexity of the cloud’s software stack to the user who otherwise is required to have expertise in cloud technologies; we manage job scheduling efficiently and in a scalable manner; we enable resource elasticity and workflow orchestration at a large scale; and we facilitate moving the study of nonporous structures, which has wide applications in engineering and scientific fields, to the cloud. While we demonstrate the capability of our framework for a specific materials science application, it can be adapted for other applications and domains because of its modular, multi-layer architecture.

97 MATHEMATICS AND COMPUTING↗