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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Can we detect the stellar differential rotation of WASP-7 through the Rossiter–McLaughlin observations?

ABSTRACT The Rossiter–McLaughlin (RM) effect is the radial velocity signal generated when an object transits a rotating star. Stars rotate differentially and this affects the shape and amplitude of this signal, on a level that can no longer be ignored with precise spectrographs. Highly misaligned planets provide a unique opportunity to probe stellar differential rotation via the RM effect, as they cross several stellar latitudes. In this sense, WASP-7, and its hot Jupiter with a projected misalignment of ∼90°, is one of the most promising targets. The aim of this work is to understand if the stellar differential rotation is measurable through the RM signal for systems with a geometry similar to WASP-7. In this sense, we use a modified version of soap3.0 to explore the main hurdles that prevented the precise determination of the differential rotation of WASP-7. We also investigate whether the adoption of the next generation spectrographs, like ESPRESSO, would solve these issues. Additionally, we assess how instrumental and stellar noise influence this effect and the derived geometry of the system. We found that, for WASP-7, the white noise represents an important hurdle in the detection of the stellar differential rotation, and that a precision of at least 2 m s−1 or better is essential.

Serrano, L. M.↗
DOE OSTI2024

TOI–757 b: an eccentric transiting mini–Neptune on a 17.5–d orbit

ABSTRACT We report the spectroscopic confirmation and fundamental properties of TOI$-$757 b, a mini$-$Neptune on a 17.5$-$d orbit transiting a bright star ($V\, =\, 9.7$ mag) discovered by the TESS mission. We acquired high$-$precision radial velocity measurements with the HARPS, ESPRESSO, and PFS spectrographs to confirm the planet detection and determine its mass. We also acquired space$-$borne transit photometry with the CHEOPS space telescope to place stronger constraints on the planet radius, supported with ground$-$based LCOGT photometry. WASP and KELT photometry were used to help constrain the stellar rotation period. We also determined the fundamental parameters of the host star. We find that TOI$-$757 b has a radius of $R_{\mathrm{p}} = 2.5 \pm 0.1 R_{\oplus }$ and a mass of $M_{\mathrm{p}} = 10.5^{+2.2}_{-2.1} M_{\oplus }$, implying a bulk density of $\rho _{\text{p}} = 3.6 \pm 0.8$ g cm$^{-3}$. Our internal composition modelling was unable to constrain the composition of TOI$-$757 b, highlighting the importance of atmospheric observations for the system. We also find the planet to be highly eccentric with e = 0.39$^{+0.08}_{-0.07}$, making it one of the very few highly eccentric planets among precisely characterized mini$-$Neptunes. Based on comparisons to other similar eccentric systems, we find a likely scenario for TOI$-$757 b’s formation to be high eccentricity migration due to a distant outer companion. We additionally propose the possibility of a more intrinsic explanation for the high eccentricity due to star$-$star interactions during the earlier epoch of the Galactic disc formation, given the low metallicity and older age of TOI$-$757.

Alqasim, A. (ORCID:0000000151025505)↗
DOE OSTI2024

A possible misaligned orbit for the young planet AU Mic c

ABSTRACT The AU Microscopii planetary system is only 24 Myr old, and its geometry may provide clues about the early dynamical history of planetary systems. Here, we present the first measurement of the Rossiter–McLaughlin effect for the warm sub-Neptune AU Mic c, using two transits observed simultaneously with the European Southern Observatory's (ESO's) Very Large Telescope (VLT)/Echelle SPectrograph for Rocky Exoplanets and Stable Spectroscopic Observations (ESPRESSO), CHaracterising ExOPlanet Satellite (CHEOPS), and Next-Generation Transit Survey (NGTS). After correcting for flares and for the magnetic activity of the host star, and accounting for transit-timing variations, we find the sky-projected spin–orbit angle of planet c to be in the range $\lambda _{\mathrm{c}}=67.8_{-49.0}^{+31.7}$ degrees (1$\sigma$). We examine the possibility that planet c is misaligned with respect to the orbit of the inner planet b ($\lambda _{\mathrm{b}}=-2.96_{-10.30}^{+10.44}$), and the equatorial plane of the host star, and discuss scenarios that could explain both this and the planet’s high density, including secular interactions with other bodies in the system or a giant impact. We note that a significantly misaligned orbit for planet c is in some degree of tension with the dynamical stability of the system, and with the fact that we see both planets in transit, though these arguments alone do not preclude such an orbit. Further observations would be highly desirable to constrain the spin–orbit angle of planet c more precisely.

Yu, H. (ORCID:0000000209716078)↗
DOE OSTI2020

Many-body electronic structure of LaScO 3 by real-space quantum Monte Carlo

We present real space quantum Monte Carlo (QMC) calculations of the scandate LaSc0 3 that proved to be challenging for traditional electronic structure approaches due to strong correlation effects resulting in inaccurate band gaps from DFT and GW methods when compared with existing experimental data. Besides calculating an accurate QMC band gap corrected for supercell size biases and in agreement with numerous experiments, we also predict the cohesive energy of the crystal using the standard fixed-node QMC without any empirical or non-variational parameters. We show that promotion (optical) gap and fundamental gap agree with each other illustrating a clear absence of significant excitonic effects in the ideal crystal. We obtained these results in perfect consistency in two independent tracks that employ different basis sets (plane wave vs. localized gaussians), different codes for generating orbitals (QUANTUM ESPRESSO vs. CRYSTAL), different QMC codes (QMCPACK vs. QWALK) and different high-accuracy pseudopotentials (ccECPs vs. Troullier-Martins) presenting the maturity and consistency of QMC methodology and tools for studies of strongly correlated problems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
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 OSTI2021

Photoelectrochemically Self Improving Si/GaN Photocathode: Figure 4a Raw Data

Calculated formation energy of (0001 ̅) c-plane GaN surfaces. The density-functional theory (DFT) calculations were performed with the generalized gradient approximation, using the plane-wave pseudopotential quantum-ESPRESSO package. Ultrasoft pseudopotentials were used to describe the interaction between valence electrons and ionic cores, where Ga 3d electrons were explicitly treated as valence electrons. The wave functions and electronic density were expanded in a plane-wave basis set truncated at a cutoff energy of 30 Ry and 240 Ry, respectively. The surface was modeled using a repeated slab geometry using a (2×2) unit cell with a thickness of seven GaN bilayers, where the Ga-terminated bottom side was passivated by pseudo-hydrogen with charge of 1.25e. In addition, the (1010) surface was modeled using 8 GaN atomic layers with a lateral dimension of 9.57 Å x 10.38 Å. A vacuum width of at least 15.0 Å was introduced between consecutive slabs, and a k-point mesh of 5x5x1 and 2x2x1 was used to sample the surface Brillouin zone for the polar and non-polar surfaces, respectively. Calculated formation energy of (0001 ̅) c-plane GaN surfaces with different oxygen configuration within the anion and cation-rich limits: ideal GaN surfaces of c-plane and m-plane; configurations with 100% replacement of nitrogen by oxygen on the surface c-plane and m-plane; 100% replacement of nitrogen by oxygen in the subsurface bilayer c-plane and m-plane; and configurations with 50% replacement of nitrogen of the surface and subsurface bilayers by oxygens c-plane and m-plane. In both cases, the ideal surface is chosen as the reference.

photocathode↗
DOE OSTI2021

Photoelectrochemically Self Improving Si/GaN Photocathode: Figure 4b Raw Data

Calculated formation energy of (1010 ̅) m-plane GaN surfaces. The density-functional theory (DFT) calculations were performed with the generalized gradient approximation, using the plane-wave pseudopotential quantum-ESPRESSO package. Ultrasoft pseudopotentials were used to describe the interaction between valence electrons and ionic cores, where Ga 3d electrons were explicitly treated as valence electrons. The wave functions and electronic density were expanded in a plane-wave basis set truncated at a cutoff energy of 30 Ry and 240 Ry, respectively. The surface was modeled using a repeated slab geometry using a (2×2) unit cell with a thickness of seven GaN bilayers, where the Ga-terminated bottom side was passivated by pseudo-hydrogen with charge of 1.25e. In addition, the (1010) surface was modeled using 8 GaN atomic layers with a lateral dimension of 9.57 Å x 10.38 Å. A vacuum width of at least 15.0 Å was introduced between consecutive slabs, and a k-point mesh of 5x5x1 and 2x2x1 was used to sample the surface Brillouin zone for the polar and non-polar surfaces, respectively. Calculated formation energy of (1010 ̅) m-plane GaN surfaces with different oxygen configuration within the anion and cation-rich limits: ideal GaN surfaces of c-plane and m-plane; configurations with 100% replacement of nitrogen by oxygen on the surface c-plane and m-plane; 100% replacement of nitrogen by oxygen in the subsurface bilayer c-plane and m-plane; and configurations with 50% replacement of nitrogen of the surface and subsurface bilayers by oxygens c-plane and m-plane. In both cases, the ideal surface is chosen as the reference.

photocathode↗
DOE OSTI2022

Machine-Learning for Excited-State Dynamics

The primary objective of this computational chemistry sciences team is to design a machine learning NAMD environment that will utilize current petascale and future exascale computational capabilities to advance understanding of charge and energy flow in materials. Our machine-learning NAMD environment will 1) integrate advanced NAMD capabilities directly into electronic structure software (e.g., ABINIT, Quantum Espresso, VASP, etc.); 2) merge the preparatory tools of Pychemia into PYXAID and Avogadro environments so that massive data collection from NAMD simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

First-Principles Calculations of Thermoelectric Transport Properties of Quaternary and Ternary Bulk Chalcogenide Crystals

Chalcogenide crystals have a wide range of applications, especially as thermoelectric materials for energy conversion. Thermoelectric materials can be used to generate an electric current from a temperature gradient based on the Seebeck effect and based on the Peltier effect, and they can be used in cooling applications. Using first-principles calculations and semiclassical Boltzmann theory, we have computed the Seebeck coefficient, electrical conductivity, electronic thermal conductivity, power factor, and figure of merit of 30 chalcogenide crystals. A Quantum Espresso package is used to calculate the electronic properties and locate the Fermi level. The transport properties are then calculated using the BoltzTraP code. The 30 crystals are divided into two groups. The first group has four crystals with quaternary composition (A 2 BCQ 4 ) (A = Tl; B = Cd, Hg; C = Si, Ge, Sn; Q = S, Se, Te). The second group contains 26 crystals with the ternary composition (A’B’Q 2 ) (A’ = Ag, Cu, Au, Na; B’ = B, Al, Ga, In; Q = S, Se, Te). Among these 30 chalcogenide crystals, the results for 11 crystals: Tl 2 CdGeSe 4 , Tl 2 CdSnSe 4 , Tl 2 HgSiSe 4 , Tl 2 HgSnS 4 , AuBSe 2 , AuBTe 2 , AuAlTe 2 , AuGaTe 2 , AuInTe 2 , AgAlSe 2 , and AgAlTe 2 are revealed for the first time. In addition, temperature-dependent transport properties of pure and doped AgSbSe 2 and AgSbTe 2 crystals with dopant compositions of AgSb 0.94 Cd 0.06 Te 2 and AgSbTe 1.85 Se 0.15 were explored. These results provide an excellent database for bulk chalcogenides crucial for a wide range of potential applications in renewable energy fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2004

UIVerify: A Web-Based Tool for Verification and Automatic Generation of User Interfaces

In this poster, we describe a web-based tool for verification and automatic generation of user interfaces. The verification component of the tool accepts as input a model of a machine and a model of its interface, and checks that the interface is adequate (correct). The generation component of the tool accepts a model of a given machine and the user's task, and then generates a correct and succinct interface. This write-up will demonstrate the usefulness of the tool by verifying the correctness of a user interface to a flight-control system. The poster will include two more examples of using the tool: verification of the interface to an espresso machine, and automatic generation of a succinct interface to a large hypothetical machine.

Shiffman, Smadar↗
NASA NTRS2016

Solar System Exploration Research Virtual Institute: Year Three Annual Report 2016

NASA's Solar System Exploration Research Virtual Institute (SSERVI) is pleased to present the 2016 Annual Report. Each year brings new scientific discoveries, technological breakthroughs, and collaborations. The integration of basic research and development, industry and academic partnerships, plus the leveraging of existing technologies, has further opened a scientific window into human exploration. SSERVI sponsorship by the NASA Science Mission Directorate (SMD) and Human Exploration and Operations Mission Directorate (HEOMD) continues to enable the exchange of insights between the human exploration and space science communities, paving a clearer path for future space exploration. SSERVI provides a unique environment for scientists and engineers to interact within multidisciplinary research teams. As a virtual institute, the best teaming arrangements can be made irrespective of the geographical location of individuals or laboratory facilities. The interdisciplinary science that ensues from virtual and in-person interactions, both within the teams and across team lines, provides answers to questions that many times cannot be foreseen. Much of this research would not be accomplished except for the catalyzing, collaborative environment enabled by SSERVI. The SSERVI Central Office, located at NASA Ames Research Center in Silicon Valley, California, provides the leadership, guidance and technical support that steers the virtual institute. At the start of 2016, our institute had nine U.S. teams, each mid-way through their five-year funding cycle, plus nine international partnerships. However, by the end of the year we were well into the selection of four new domestic teams, selected through NASA's Cooperative Agreement Notice (CAN) process, and a new international partnership. Understanding that human and robotic exploration is most successful as an international endeavor, international partnerships collaborate with SSERVI domestic teams on a no-exchange of funds basis, but they bring a richness to the institute that is priceless. The international partner teams interact with the domestic teams in a number of ways, including sharing students, scientific insights, and access to facilities. We are proud to introduce our newest partnership with the Astrophysics and Planetology Research Institute (IRAP) in Toulouse, France. In 2016, Principal Investigator Dr. Patrick Pinet assembled a group of French researchers who will contribute scientific and technological expertise related to SSERVI research. SSERVI's domestic teams compete for five-year funding opportunities through proposals to a NASA CAN every few years. Having overlapping proposal selection cycles allows SSERVI to be more responsive to any change in direction NASA might experience, while providing operational continuity for the institute. Allowing new teams to blend with the more seasoned teams preserves corporate memory and expands the realm of collaborative possibilities. A key component of SSERVI's mission is to grow and maintain an integrated research community focused on questions related to the Moon, Near-Earth asteroids, and the moons of Mars. The strong community response to CAN-2 demonstrated the health of that effort. NASA Headquarters conducted the peer-review of 22 proposals early in 2017 and, based on recommendations from the SSERVI Central Office and NASA SSERVI program officers, the NASA selecting officials determined the new teams in the spring of 2017. We are pleased to welcome the CAN-2 teams into the institute, and look forward to the collaborations that will develop with the current teams. The new teams are: The Network for Exploration and Space Science (NESS) team (Principal Investigator (PI) Prof. Jack Burns/U. Colorado); the Exploration Science Pathfinder Research for Enhancing Solar System Observations (ESPRESSO) team (PI Dr. Alex Parker/Southwest Research Institute); the Toolbox for Research and Exploration (TREX) team (PI Dr. Amanda Hendrix/ Planetary Science Institute); and the Radiation Effects on Volatiles and Exploration of Asteroids & Lunar Surfaces (REVEALS) team (PI Prof. Thomas Orlando/ Georgia Institute of Technology). In this report, you will find an overview of the 2016 leadership activities of the SSERVI Central Office, reports prepared by the U.S. teams from CAN-1, and achievements from several of the SSERVI international partners. Reflecting on the past year's discoveries and advancements serves as a potent reminder that there is still a great deal to learn about NASA's target destinations. Innovation in the way we access, sample, measure, visualize, and assess our target destinations is needed for further discovery. At the same time, let us celebrate how far we have come, and strongly encourage a new generation that will make the most of future opportunities.

Pendleton, Yvonne↗
NASA NTRS2022

HD 28109 Hosts A Trio of Transiting Neptunian Planets Including A Near-Resonant Pair, Confirmed By ASTEP From Antarctica

We report on the discovery and characterization of three planets orbiting the F8 star HD 28109, which sits comfortably in TESS ’s continuous viewing zone. The two outer planets have periods of 56 . 0067 ±0 . 0003 d and 84 . 2597 + 0 . 0010 −0 . 0008 d, which implies a period ratio very close to that of the first-order 3:2 mean motion resonance, exciting transit timing variations (TTVs) of up to 60 min. These two planets were first identified by TESS , and we identified a third planet in the TESS photometry with a period of 22 . 8911 ±0 . 0004 d. We confirm the planetary nature of all three planetary candidates using ground-based photometry from Hazelwood , ASTEP , and LCO , including a full detection of the ∼9 h transit of HD 28109 c from Antarctica. The radii of the three planets are R b = 2 . 199 + 0 . 098 −0 . 10 R ⊕, R c = 4 . 23 ±0 . 11 R ⊕, and R d = 3 . 25 ±0 . 11 R ⊕; we characterize their masses using TTVs and precise radial velocities from ESPRESSO and HARPS, and find them to be M b = 18 . 5 + 9 . 1 −7 . 6 M ⊕, M c = 7 . 9 + 4 . 2 −3 . 0 M ⊕, and M d = 5 . 7 + 2 . 7 −2 . 1 M ⊕, making planet b a dense, massive planet while c and d are both underdense. We also demonstrate that the two outer planets are ripe for atmospheric characterization using transmission spectroscopy, especially given their position in the CVZ of James Webb Space Telescope . The data obtained to date are consistent with resonant (librating) and non-resonant (circulating) solutions; additional observations will show whether the pair is actually locked in resonance or just near-resonant.

Georgina Dransfield↗
DOE OSTI2024

HTESP (High-throughput electronic structure package): A package for high-throughput ab initio calculations

High-throughput ab initio calculations are the indispensable parts of data-driven discovery of new materials with desirable properties, as reflected in the establishment of several online material databases. The accumulation of extensive theoretical data through computations enables data-driven discovery by constructing machine learning and artificial intelligence models to predict novel compounds and forecast their properties. Efficient usage and extraction of data from these existing online material databases can accelerate the next stage materials discovery that targets different and more advanced properties, such as electron–phonon coupling for phonon-mediated superconductivity. However, extracting data from these databases, generating tailored input files for different ab initio calculations, performing such calculations, and analyzing new results can be demanding tasks. Here, in this work, we introduce a software package named “HTESP” (High-Throughput Electronic Structure Package) written in Python and Bash languages, which automates the entire workflow including data extraction, input file generation, calculation submission, result collection and plotting. Our HTESP will help speed up future computational materials discovery processes.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Violation of the Cauchy–Born rule in multi-principal element alloys

Multi-principal element alloys are a novel class of materials that are formed by combining multiple elements in high concentrations and show exceptional properties compared to conventional alloys. These alloys have high configurational entropy due to inherent atomic disorder. The Cauchy–Born rule is a popular homogenization method for linking atomistic to continuum length scales. In this Letter, we use ab initio density functional theory calculations to report that the Cauchy–Born rule, which holds in conventional alloys in the absence of defects, is not valid in multi-principal element alloys. Further, the violation of the Cauchy–Born rule in these alloys is attributed to the presence of atomic disorder due to which the deformations are inhomogeneous. Our results also show the deviations in deformation are related to the magnitude of the stretch and shear by power laws.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Li1−xNiO2 Many-body DMC Benchmark Dataset

The dataset contains all numerical data generated in support of the manuscript “Many‑body Benchmark of Electronic Charge and Spin Densities for Li1–xNiO2​” (Journal of Chemical Theory and Computation, DOI: 10.1021/acs.jctc.5c02097, URL: https://pubs.acs.org/doi/10.1021/acs.jctc.5c02097). The materials included in this repository are: 1. Data files used to produce all figures and tables in the main manuscript and supporting information. 2. Benchmark density‑functional theory (DFT) datasets used for the charge‑ and spin‑density analyses. 3. Reference many‑body diffusion Monte Carlo (DMC) calculations and associated input/output files.

36 MATERIALS SCIENCE↗