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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

TRIDENT Drill Validation at Mars and Lunar Analog Field Sites

Drilling on Earth is typically a human-intensive activity. Drilling on other planets is further complicated by the lack of prior local field surveys of their target area, hence blindly drilling into uncertain target rocks. Field conditions on the Moon or Mars are also different than for shallow drilling on Earth: lower temperatures and pressures, less power available, low masses (hence less weight-on-bit). Given the cost of transport from Earth, no drilling muds or working fluids are likely to be available to carry away cuttings. And impact-gardened regolith and dust vary mechanically and texturally from most terrestrial soils. The Regolith and Ice Drill for Exploration of New Terrains (TRIDENT) is a rotary-percussive 1m-class drill from Honeybee Robotics. It is low-power (rotary and percussive actuators are 200 W each) and lightweight (<20 kg) with the maximum weight on bit limited to 200 N. TRIDENT has been manifested for the Volatiles Investigating Polar Exploration Rover (VIPER) and PRIME-1 lunar south pole missions in 2024, has previously been field tested at a hot, dry analog site in the Atacama Desert, and in lunar conditions in thermal vacuum chamber tests. TRIDENT was also part of the 2019 Icebreaker Mars Discovery proposal, as well as in the Mars Life Explorer concept. During ARADS tests, drill control and fault recovery automation software enabled hands-off operations of a rover-mounted TRIDENT drill. TRIDENT Drill Analog Site Validation: Past TRIDENT tests in thermal vacuum (TVAC) chambers targeted containers of manufactured lunar simulants with added volatiles. 2022 TRIDENT ambient testing at NASA Ames drilled into cemented lunar simulant materials. Low cuttings-permeability led to cuttings buildup, and drill choking and binding was observed. The Atacama analog site in ARADS had desiccated unconsolidated sediments that did not challenge the TRIDENT design. However, lunar polar regolith is expected to be diverse and heterogeneous with varying clast sizes, with abundant impactites and perhaps subsurface ice deposits. Neither the simulants nor Atacama testing had completely covered the TRIDENT-targeted field characteristics, motivating further analog tests prior to the planned lunar missions. To gain more insight into the behavior of the TRIDENT hardware in diverse impactites and subsurface ice, and to verify the software automation in that environment, in August 2023 TRIDENT was brought to Haughton Crater, a field analog site in the Canadian Arctic. In September 2023 the same drill was brought to the Bishop Tuff in southern California to verify whether drilling binding behaviors previously seen in lunar simulant testing would be observed in naturally occurring fine-grained massive layers. The ~22 Ma Haughton Crater impact structure is located at 75 ̊22’ N, 89 ̊41’ W, on northwestern Devon Island, Nunavut, Canada. Numerous deposits of pale-grey crater-fill polymictic impact-melt breccia are found within the crater with a typical thickness reaching ~125 m or greater and covering ~60 km -2 . An approximately 600m-thick permafrost layer is also present with ice typically found within 0.5-0.6m of the surface. The volcanic tableland north of Bishop, CA exposes densely welded tuff laid down during the eruption that created the Long Valley Caldera at approximately 0.76 Ma. Extensional faults and the Owens River gorge expose cross-sections across the plateau. The area is viewed as an analog site for Mars features believed to be of pyroclastic origin. Results: Haughton Crater.Drilling tests were conducted 8-13 August 2023 at a previously undisturbed area separated 5-10 m from past years’ Drill Hill test sites (75.4208, -089.7613). In six days, TRIDENT drilled 8 holes to nearly 1 m depth each, totaling 7.80 m. The active layer/ice boundary was at ~67 cm depth, with a total of approximately 2.4 m drilled into ice or ice-cemented impact breccia. During drilling, five drill fault states were observed and successfully recovered. Holes 23-1, 4 and 7 were drilled under manual control, using Honeybee’s Thorax user interface. Holes 23-5, 6, and 8 were drilled with the Ames IBexec automated drilling control software. TRIDENT was observed to have little difficulty in the thawed uncemented impact breccia above the active layer boundary, but required percussion to make slower headway in the ice-cemented breccia. In Hole 23-7 (Fig.1), drilling slowed down in a massive unit just above the active-layer boundary (perhaps a large rock extending into the ice-cementation?), with only 7cm progress made in 27 minutes of high auger torque and constant percussion, leading to a choking fault and then a binding fault. A similar pattern had been observed in TRIDENT Rio Tinto test data from 2017 [6] as well as in the 2022laboratory tests.Bishop Tuff.A team from NASA Ames and the US Geological Survey deployed the same TRIDENT drill to Bishop Sites 1B and 1C (37.4203, -118.4289; 37.4265, -118.4215) on 13-16 September 2023, on the Bishop Tuff plateau. A third drill site was used 17-18 September 2023(37.4598, -118.3667) in an abandoned pumice mine. Four holes (totaling 2.5m depth) were drilled into the fine-grained, meters-thick tuff units at Sites 1B and 1C, and a further two boreholes (totaling 1.98m depth) were made at the pumice site. Drill behavior in the tuff below 10 cm depth was similar to that seen at 65-74 cm depth in Haughton Hole 23-7 (Fig. 1) and that seen in the 2022 lab simulant drilling. Drill safety torque limits were exceeded multiple times resulting in drill stops downhole. These freezes then required external added torques (with a pipe wrench) to resume rotation, to unstick the drill for withdrawal. To prevent this choking and binding behavior we found that more-frequent cuttings removal was necessary, e.g., reducing the “drill bite” size from the nominal 10 cm to 2 cm per bite --bringing the auger up to the surface more frequently, as seen in Bishop Site 1C Hole 2 (Fig.2). This permitted slow progress without drill binding and without external interventions. Conversely, TRIDENT drilling in the more porous pumice target material showed no cuttings buildup issue, and single bites as large as 40 cm were demonstrated. Discussion: We observed that TRIDENT easily penetrated unconsolidated heterogeneous soils (both above the active layer boundary at Haughton and previously in the Atacama). Cemented or consolidated targets that were cuttings-permeable (icy impact breccia, pumice) required more energy applied and percussion. However, in non-cuttings-permeable targets (welded microporous tuff, cemented simulants, boulder) TRIDENT was observed to be prone to excessive cuttings accumulation leading to choking/binding faults and stalling. The wedge cutting bit, used by TRIDENT in field tests and in its flight versions, pulverizes the target rock and creates fine cuttings that ideally are transported up the auger spirals for removal. In porous, fractured or vesicular target materials (such as at the Bishop pumice site) a significant portion of the cuttings are pushed aside, but for non-fractured, microporous targets the cuttings remain in the borehole and accumulate. Rock powder is relatively incompressible as a working fluid at only 100-200N downward force (TRIDENT limits) and hence eventual drilling progress slows or stops. Our recommended strategy for improving TRIDENT cuttings removal in massive target units with low cuttings-permeability is to reduce TRIDENT bite sizes when encountering these units, from 10cm to as little as 1-2cm, to effectively bail the accumulating cuttings. This approach was demonstrated to reduce choking and allowed slow progress to continue in cuttings-impermeable microporous target units (viz. the Bishop tuff in our September 2023 tests or cemented simulants in 2022 ambient tests).

robotic drilling↗
NASA NTRS2011

Radiation Shielding of Lunar Regolith/Polyethylene Composites and Lunar Regolith/Water Mixtures

Space radiation is a complex mixed field of ionizing radiation that can pose hazardous risks to sophisticated electronics and humans. Mission planning for lunar exploration and long duration habitat construction will face tremendous challenges of shielding against various types of space radiation in an attempt to minimize the detrimental effects it may have on materials, electronics, and humans. In late 2009, the Lunar Crater Observation and Sensing Satellite (LCROSS) discovered that water content in lunar regolith found in certain areas on the moon can be up to 5.6 +/-2.8 weight percent (wt%) [A. Colaprete, et. al., Science, Vol. 330, 463 (2010). ]. In this work, shielding studies were performed utilizing ultra high molecular weight polyethylene (UHMWPE) and aluminum, both being standard space shielding materials, simulated lunar regolith/ polyethylene composites, and simulated lunar regolith mixed with UHMWPE particles and water. Based on the LCROSS findings, radiation shielding experiments were conducted to test for shielding efficiency of regolith/UHMWPE/water mixtures with various percentages of water to compare relative shielding characteristics of these materials. One set of radiation studies were performed using the proton synchrotron at the Loma Linda Medical University where high energy protons similar to those found on the surface of the moon can be generated. A similar experimental protocol was also used at a high energy spalation neutron source at Los Alamos Neutron Science Center (LANSCE). These experiments studied the shielding efficiency against secondary neutrons, another major component of space radiation field. In both the proton and neutron studies, shielding efficiency was determined by utilizing a tissue equivalent proportional counter (TEPC) behind various thicknesses of shielding composite panels or mixture materials. Preliminary results from these studies indicated that adding 2 wt% water to regolith particles could increase shielding of the regolith materials by about 6%. The findings may be utilized to extend the possibilities of potential candidate materials for lunar habitat structures, will potentially impact the design criteria of future human bases on the moon, and provide some guidelines for future space mission planning with respect to radiation exposure and risks posed on astronauts.

Johnson, Quincy F.↗
NASA NTRS1991

An investigation of the thermal shock resistance of lunar regolith and the recovery of hydrogen from lunar soil heated using microwave radiation

The objective is to develop a better understanding of the thermal shock properties of lunar regolith sintered using 2.45 GHz electromagnetic radiation and to do a preliminary study into the recovery of bound hydrogen in lunar soil heated using 2.45 GHz radiation. During the first phase of this work, lunar simulant material was used to test whether or not microhardness data could be used to infer thermal shock resistance and later actual lunar regolith was used. Results are included on the lunar regolith since this is of primary concern and not the simulant results. They were similar, however. The second phase investigated the recovery of hydrogen from lunar regolith and results indicate that microwave heating of lunar regolith may be a good method for recovery of bound gases in the regolith.

Meek, T. T.↗
DOE OSTI2022

Simulation of anoxic lenses as exporters of reactivity in alluvial aquifer sediments

Sedimentary interfaces between contrasting hydrogeological facies in alluvial aquifers drive the development of biogeochemical interfaces that influence subsurface and surface water quality. Here, we calibrate a reactive transport model on a series of dual-domain column experiments, where centimeter-scale, low-permeability, organic-rich anoxic lenses are embedded in coarser-grained aquifer material. Simulations explicitly account for C, Fe, and S cycling at the interface between the lenses and the aquifer in water-saturated conditions. Our results highlight the role of fine-grained, organic-rich inclusions not only as sources or sinks for redox-sensitive species, but also as exporters of nutrients that stimulate downgradient biogeochemical cycling. By releasing large amounts of organic carbon into the surrounding aquifer, such lenses drive the development of proximal secondary reduction zones ("halos"), characterized by high microbial activity (e.g., sulfate reduction) and accumulation of reduced reaction products (e.g., iron sulfide). If similar secondary reduction zones develop within the hydraulically conductive domain of an aquifer, they would be highly susceptible to changes in hydrologic conditions, for instance oxygen pulses associated with seasonal snowmelt. Furthermore, our results also emphasize the limitations of relying solely on aqueous species measurements to inform reactivity in systems where fast redox cycling and/or sizeable particulate transport may limit the signature of reactivity in the dissolved phase.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Mesoscale simulation of granular materials under weak shock compaction–pore size distribution effects

This research established a systematic method to generate various pore-size distributions (PSDs) and studied the effect of PSDs on the shock compaction response of granular materials using two-dimensional mesoscale simulations under identical porosity. Simulations utilized various PSDs for three particle shapes (circle, ellipse, and square). Contacting particle configurations using three PSDs, characterized by spatially uniform distributed pores to heterogeneous distributed pores, and non-contacting particle configurations under a single case of PSD were tested. The PSD of generated particle sets was characterized using coordination number, mean diameter, and bimodality coefficient as statistical metrics. Mesoscale simulations showed that regardless of the conditions of pore distributions, shock compaction of granular materials consistently demonstrates a precursor, shock compaction front, and end. However, the shock compaction velocity of contacting particles was dependent on the PSDs despite the constant initial porosity. The compaction velocity was faster in particle configurations with relatively uniform pore distributions than in heterogeneous pore distributions, which our study demonstrated can be attributed to particle rearrangement during compaction. Circular-shaped particles had high sensitivity in shock compaction response to the various PSDs. Furthermore, a contacting particle configuration tended to propagate the shock compaction wave relatively faster than particles that were in a non-contact configuration. This study established the relative importance of considering PSD as a metric over the coordination number in studies of the shock compaction response of granular materials. Further, insights are provided on the evolving shock substructure to characterize the shock compaction response of granular materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Numerical Diffusion (Mixing) of Material in Numerical Simulations of Hydrodynamics [Slides]

It is often assumed that a material interface between two materials is spread over a few numerical cells in numerical simulations for hydrodynamics. Also, we have the impression that higher order methods introduce less numerical diffusion (mixing) of material. As we know one of the purposes of adaptive mesh refinement (AMR) is to resolve interfaces between materials, but we would like to know how effective AMR is to reduce numerical diffusion of material. We will present our investigation about numerical diffusion (mixing) of material in xRage. The result of the investigation indicates that the assumptions mentioned above are not always valid. In this talk, we will also demonstrate the effectiveness of numerical techniques to reduce numerical diffusion of material, including contact discontinuity steepening, isotropic interface steepening, max interface steepening, material interface reconstruct.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Recent advances and applications of deep learning methods in materials science

Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data modalities. DL allows analysis of unstructured data and automated identification of features. The recent development of large materials databases has fueled the application of DL methods in atomistic prediction in particular. In contrast, advances in image and spectral data have largely leveraged synthetic data enabled by high-quality forward models as well as by generative unsupervised DL methods. In this article, we present a high-level overview of deep learning methods followed by a detailed discussion of recent developments of deep learning in atomistic simulation, materials imaging, spectral analysis, and natural language processing. For each modality we discuss applications involving both theoretical and experimental data, typical modeling approaches with their strengths and limitations, and relevant publicly available software and datasets. We conclude the review with a discussion of recent cross-cutting work related to uncertainty quantification in this field and a brief perspective on limitations, challenges, and potential growth areas for DL methods in materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Fully self-consistent finite-temperature $GW$ in Gaussian Bloch orbitals for solids

In this work, we present algorithmic and implementation details for the fully self-consistent finite-temperature $GW$ method in Gaussian Bloch orbitals for solids. Our implementation is based on the finite-temperature Green's function formalism in which all equations are solved on the imaginary axis, without resorting to analytical continuation during the self-consistency. No quasiparticle approximation is employed and all matrix elements of the self-energy are explicitly evaluated. The method is tested by evaluating the band gaps of selected semiconductors and insulators. We show agreement with other, differently formulated, finite-temperature sc ⁢$GW$ implementations when finite-size corrections and basis-set errors are taken into account. By migrating computationally intensive calculations to graphics processing units, we obtain scalable results on large supercomputers with nearly optimal performance. Our work demonstrates the applicability of Gaussian orbital based sc⁢ $GW$ for ab initio correlated material simulations and provides a sound starting point for embedding methods built on top of $GW$.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRSDate not supplied

Extending ISS Life Beyond 2030

This paper presents an overview of the International Space Station life extension project, focusing on the analytical approach used to assess its primary structure. Also addressed are life extension approaches for other affected sub-systems, including secondary structure, materials, Environmental Control and Life Support Systems (ECLSS), Electrical Power Systems (EPS), and Logistics and Maintenance (L&M). The United States On-orbit Segment (USOS) of the International Space Station (ISS) was initially designed for a 15-year on-orbit life, but with the realization of its continued importance, efforts were made to extend its operations through 2030. The paper discusses the various analyses conducted, including future operations planning, load simulation, material degradation studies, thermal analyses, and fracture analyses. The results demonstrate the feasibility and achievability of extending the ISS's life, ensuring its on-going role as a hub for scientific research, international cooperation, and educational endeavors. With the life extension process in place, continuous operations beyond 2030 are possible to maintain an uninterrupted human presence in Low Earth Orbit, facilitating the testing of new technologies, and allow for a seamless transition to new commercially owned and operated destinations.

design life↗
DOE OSTI2024

Development of a Model for Irradiation-Induced Grain Growth in UO2 thin films

In this work, we develop a model of irradiation-induced grain growth in UO2 using the MARMOT mesoscale nuclear materials simulation tool. We couple the existing thermally activated grain growth model with a heat conduction model that includes random heat sources representing thermal spikes. We compare the results with the irradiation data on UO2 thin films.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

AtomSets as a hierarchical transfer learning framework for small and large materials datasets

Abstract Predicting properties from a material’s composition or structure is of great interest for materials design. Deep learning has recently garnered considerable interest in materials predictive tasks with low model errors when dealing with large materials data. However, deep learning models suffer in the small data regime that is common in materials science. Here we develop the AtomSets framework, which utilizes universal compositional and structural descriptors extracted from pre-trained graph network deep learning models with standard multi-layer perceptrons to achieve consistently high model accuracy for both small compositional data (<400) and large structural data (>130,000). The AtomSets models show lower errors than the graph network models at small data limits and other non-deep-learning models at large data limits. They also transfer better in a simulated materials discovery process where the targeted materials have property values out of the training data limits. The models require minimal domain knowledge inputs and are free from feature engineering. The presented AtomSets model framework can potentially accelerate machine learning-assisted materials design and discovery with less data restriction.

Chen, Chi (ORCID:0000000180087043)↗
DOE OSTI2026

Development of local hybrid density functionals to treat self-interaction error and many-electron effects

The goal of this project was to improve density functional theory (DFT) for systems where conventional semilocal approximations are limited by self-interaction error (SIE) and by near-degeneracy or strong many-electron effects. While DFT remains the only broadly practical first-principles framework for large-scale materials simulations, its predictive accuracy is often challenged in situations involving stretched bonds, charge transfer, transition-metal chemistry, magnetic couplings, band gaps, and correlated electronic states. This project addressed these limitations by developing physically grounded and numerically robust exchange–correlation functionals that retain the efficiency of modern DFT while extending its predictive scope.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Actinide Science for Post Detonation Nuclear Forensic Analyses

Actinide and fission product separations, analyses, and solid material syntheses are key to supporting the development and testing of new nuclear forensic science technologies and for training nuclear emergency responders to effectively respond to nuclear emergency events. In this presentation, nuclear forensic scientist Dr. Mathew Snow will discuss a variety of technologies developed at Idaho National Laboratory (INL) and around the world for these applications. The presentation will include discussions of new approaches to rapid, high-efficiency chemical separations, sample preparation and analysis techniques for field-deployable actinide analyses, and techniques recently developed at INL for producing solid nuclear fallout simulant materials. An overview of the challenges confronting researchers in these area, along with possible opportunities, will also be provided.

Nuclear Forensics↗
DOE OSTI2024

Enhancing the Quality and Reliability of Machine Learning Interatomic Potentials through Better Reporting Practices

Recent developments in machine learning interatomic potentials (MLIPs) have empowered even nonexperts in machine learning to train MLIPs for accelerating materials simulations. However, reproducibility and independent evaluation of presented MLIP results is hindered by a lack of clear standards in current literature. In this Perspective, we aim to provide guidance on best practices for documenting MLIP use while walking the reader through the development and deployment of MLIPs including hardware and software requirements, generating training data, training models, validating predictions, and MLIP inference. We also suggest useful plotting practices and analyses to validate and boost confidence in the deployed models. Finally, we provide a step-by-step checklist for practitioners to use directly before publication to standardize the information to be reported. Altogether, we hope that our work will encourage the reliable and reproducible use of these MLIPs, which will accelerate their ability to make a positive impact in various disciplines including materials science, chemistry, and biology, among others.

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

TDEP: Temperature Dependent Effective Potentials

The Temperature Dependent Effective Potential (TDEP) method is a versatile and efficient approach to include temperature in ab initio materials simulations based on phonon theory. TDEP can be used to describe thermodynamic properties in classical and quantum ensembles, and several response properties ranging from thermal transport to Neutron and Raman spectroscopy. A stable and fast reference implementation is given in the software package of the same name described here. The underlying theoretical framework and foundation is briefly sketched with an emphasis on discerning the conceptual difference between bare and effective phonon theory, in both self-consistent and non-self-consistent formulations. References to numerous applications and more in-depth discussions of the theory are given.

36 MATERIALS SCIENCE↗
NASA NTRS2005

Formation of Nanophase Iron in Lunar Soil Simulant for Use in ISRU Studies

For the prospective return of humans to the Moon and the extensive amount of premonitory studies necessary, large quantities of lunar soil simulants are required, for a myriad of purposes from construction/engineering purposes all the way to medical testing of its effects from ingestion by humans. And there is only a limited and precious quantity of lunar soil available on Earth (i.e., Apollo soils) - therefore, the immediate need for lunar soil simulants. Since the Apollo era, there have been several simulants; of these JSC-1 (Johnson Space Center) and MLS-1 (Minnesota Lunar Simulant) have been the most widely used. JSC-1 was produced from glassy volcanic tuff in order to approximate lunar soil geotechnical properties; whereas, MLS-1 approximates the chemistry of Apollo 11 high-Ti soil, 10084. Stocks of both simulants are depleted, but JSC-1 has recently gone back into production. The lunar soil simulant workshop, held at Marshall Space Flight Center in January 2005, identified the need to make new simulants for the special properties of lunar soil, such as nanophase iron (np-Fe(sup 0). Hill et al. (2005, this volume) showed the important role of microscale Fe(sup 0) in microwave processing of the lunar soil simulants JSC-1 and MLS-1. Lunar soil is formed by space weathering of lunar rocks (e.g., micrometeorite impact, cosmic particle bombardment). Glass generated during micrometeorite impact cements rock and mineral fragments together to form aggregates called agglutinates, and also produces vapor that is deposited and coats soil grains. Taylor et al. (2001) showed that the relative amount of impact glass in lunar soil increases with decreasing grain size and is the most abundant component in lunar dust (less than 20 micrometer fraction). Notably, the magnetic susceptibility of lunar soil also increases with the decreasing grain size, as a function of the amount of nanophase-sized Fe(sup 0) in impact-melt generated glass. Keller et al. (1997, 1999) also discovered the presence of abundant np-Fe(sup 0) particles in the glass patinas coating most soil particles. Therefore, the correlation of glass content and magnetic susceptibility can be explained by the presence of the np-Feo particles in glass: small particles contain relatively more np-Fe(sup 0) as glass coatings because the surface area versus mass ratio of the grain size is so increased. The magnetic properties of lunar soil are important in dust mitigation on the Moon (Taylor et al. 2005). Thus material simulating this property is important for testing mitigation methods using electromagnetic field. This np- Fe(sup 0) also produces a unique energy coupling to normal microwaves, such as present in kitchen microwave ovens. Effectively, a portion of lunar soil placed in a normal 2.45 GHz oven will melt at greater than 1200 C before your tea will boil at 100 C, a startling and new discovery reported by Taylor and Meek (2004, 2005). Several methods have been investigated in attempts to make nanophase-sized Feo dispersed within silicate glass; like in the lunar glass. We have been successful in synthesizing such a product and continue to improve on our recipe. We have performed extensive experimentation on this subject to date. Ultimately it will probably be necessary to add this np-Fe(sup 0) bearing silicate glass to lunar soil stimulant, like JSC-1, to actually produce the desired magnetic and microwave coupling properties for use in appropriate ISRU experimentation.

Liu, Yang↗
DOE OSTI2026

matsim-agents v1.0

matsim-agents is a multi-agent AI framework for atomistic materials simulation and discovery. It orchestrates large language models (LLMs), machine-learned interatomic potentials (MLIPs), and DFT codes into a single agentic loop running on laptops and DOE leadership-class supercomputers. MULTI-AGENT ORCHESTRATION A LangGraph state machine with three nodes: a Planner that converts a natural-language research objective into structured tasks; an Executor that dispatches atomistic tools and loops until the queue is empty; and an Analyst that summarizes results into a human-readable report. State is checkpointed after every step and human-in-the-loop gates can be inserted at any edge. HYPOTHESIS-DRIVEN DISCOVERY CHAT An interactive REPL (matsim-agents chat) that couples LLM dialogue with atomistic simulation. Chemical formulas are automatically detected in conversation turns and trigger a full crystal-phase exploration: structure generation → relaxation → stability scoring → result injection back into the conversation, creating a closed hypothesis-refinement loop. CRYSTAL PHASE ENUMERATION Given a composition, the phase explorer enumerates prototypes by stoichiometry: elemental (fcc/bcc/hcp/sc/diamond), binary 1:1 (rocksalt/CsCl/zincblende/ wurtzite/fluorite/rutile), ternary 1:1:3 (cubic perovskite), ternary 1:2:4 (perovskite + spinel), quaternary 1:1:2:6 (Fm-3m double perovskite). 2-D prototypes (graphene, h-BN, MoS2 2H/1T) and multilayer stacking are also supported via --include-2d and --num-layers. SUPERCELL GENERATION AND SITE DECORATION Auto-tiling to a minimum atom count (--min-atoms), explicit NxNxN tiling (--supercell), symmetry-distinct site decorations (--n-orderings), and isotropic lattice-scale sweeps (--lattice-scales) for volume bracketing. MLFF RELAXATION AND STABILITY SCORING HydraGNN (multi-headed GNN) drives structure relaxation via ASE with FIRE, BFGS, or BFGSLineSearch. Stability output: delta-E/atom ranking across phases and a max-residual-force dynamical-stability proxy. Other MLIPs (MACE, NequIP, Orb) can be plugged in through the same interface. DFT BACKENDS Quantum ESPRESSO pw.x and VASP 6.6 are first-class labellers. Both have validated GPU builds and SLURM/PBS launchers for three DOE platforms: Frontier (AMD MI250X, ROCm), Aurora (Intel PVC, oneAPI), Perlmutter (NVIDIA A100, CUDA). QE produces ~100 binaries (pw.x, ph.x, epw.x, ...). VASP supports scf, relax, vc-relax, and vc-relax-shape run types. ACTIVE-LEARNING LOOP matsim-agents al run CONFIG.yaml drives an iterative HydraGNN-DFT loop: MD generates candidates → ensemble/MC-dropout uncertainty selects the most informative → DFT labels them in parallel inside one allocation → dataset grows → HydraGNN retrains → repeat. DFT backend is a single YAML toggle (dft.backend: vasp | qe). LLM-generated seed structures are supported (no curated POSCAR library needed). Config uses ${VAR}, ${VAR:-default}, ${VAR:?msg} shell-style substitution for cross-user/cross-site portability. LLM BACKENDS Ollama (local, default), vLLM (HPC multi-GPU serving), OpenAI, Anthropic, HuggingFace Transformers+Accelerate. Selected at runtime via flag or env var with no code changes. HPC PORTABILITY Same Python entry points run on Frontier (ROCm 7.2), Aurora (oneAPI), and Perlmutter (CUDA 12). DFT and ML stacks are never co-loaded in the same shell; they couple through the scheduler and filesystem. Advanced multi-node launchers (serve, discovery-chat, single-relaxation, active-learning, QE warm-start) are provided for all three platforms. CODABENCH COMPETITION BUNDLE A self-contained benchmark: 159 atomistic test structures across 11 material classes, 5 tasks (formation energy, forces, ML relaxation, AI-DFT relaxation, phase stability ranking), public/private leaderboard split (30/70), and four ready-to-run baselines: MACE-MP-0, HydraGNN, UMA, AllScAIP.

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗
DOE OSTI2023

Exploring the scaling limitations of the variational quantum eigensolver with the bond dissociation of hydride diatomic molecules

Abstract Materials simulations involving strongly correlated electrons pose fundamental challenges to state‐of‐the‐art electronic structure methods but are hypothesized to be the ideal use case for quantum computing algorithms. To date, no quantum computer has simulated a molecule of a size and complexity relevant to real‐world applications, despite the fact that the variational quantum eigensolver (VQE) algorithm can predict chemically accurate total energies. Nevertheless, because of the many applications of moderately sized, strongly correlated systems, such as molecular catalysts, the successful use of the VQE stands as an important waypoint in the advancement toward useful chemical modeling on near‐term quantum processors. In this paper, we take a significant step in this direction. We lay out the steps, write, and run parallel code for an (emulated) quantum computer to compute the bond dissociation curves of the TiH, LiH, NaH, and KH diatomic hydride molecules using the VQE. TiH was chosen as a relatively simple chemical system that incorporates d orbitals and strong electron correlation. Because current VQE implementations on existing quantum hardware are limited by qubit error rates, the number of qubits available, and the allowable gate depth, recent studies using it have focused on chemical systems involving s and p block elements. Through VQE + UCCSD calculations of TiH, we evaluate the near‐term feasibility of modeling a molecule with d‐orbitals on real quantum hardware. We demonstrate that the inclusion of d‐orbitals and the use of the UCCSD ansatz, which are both necessary to capture the correct TiH physics, dramatically increase the cost of this problem. We estimate the approximate error rates necessary to model TiH on current quantum computing hardware using VQE + UCCSD and show them to likely be prohibitive until significant improvements in hardware and error correction algorithms are available.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗