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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 1,009 records · Page 56
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NASA NTRS1979

Influence of optimized leading-edge deflection and geometric anhedral on the low-speed aerodynamic characteristics of a low-aspect-ratio highly swept arrow-wing configuration

An investigation conducted in the Langley 7 by 10 foot tunnel to determine the influence of an optimized leading-edge deflection on the low speed aerodynamic performance of a configuration with a low aspect ratio, highly swept wing. The sensitivity of the lateral stability derivative to geometric anhedral was also studied. The optimized leading edge deflection was developed by aligning the leading edge with the incoming flow along the entire span. Owing to spanwise variation of unwash, the resulting optimized leading edge was a smooth, continuously warped surface for which the deflection varied from 16 deg at the side of body to 50 deg at the wing tip. For the particular configuration studied, levels of leading-edge suction on the order of 90 percent were achieved. The results of tests conducted to determine the sensitivity of the lateral stability derivative to geometric anhedral indicate values which are in reasonable agreement with estimates provided by simple vortex-lattice theories.

Coe, P. L., Jr.↗
DOE OSTI2018

Effect of cooling rate and Co content on the formation of Fe-rich intermetallics in hypoeutectic Al7Si0.3Mg alloy with 0.5%Fe

Highlights: • Co element is firstly used in Al-0.7Si-0.3Mg alloy with 0.5 wt.% Fe to modify the morphology of Fe-rich intermetallics. • 0.75 wt.% Co addition is sufficient to suppress the undesirable effect of acicular Fe-rich intermetallics. • Co/Fe ratio determine the morphology and crystal structure of intermetallics and the optical ratio is in the range of 1-2. - Abstract: The effects of cooling rate and Co addition (0–1 wt%) on the Fe-rich intermetallics in Al7Si0.3Mg alloy with 0.5%Fe were studied in this study. The evolution of microstructure and crystal structure have been characterized by metallographic and transmission electron microscopy. The results indicated that higher cooling rate and Co addition were beneficial to modify the morphology and decrease the size of Fe-rich intermetallics. At the particular cooling rate of 2 k/s, 0.75 wt% Co was proved to be sufficient to improving the morphology of intermetallics from harmful acicular β-Al5FeSi phase to Chinese script or skeleton α-Al15(Fe,Co)3Si2 phase. Above all, the Co/Fe ratio in intermetallics was found to be an importance parameter in determining the morphology and crystal structure of (Fe,Co)-rich intermetallics. With the ratio increased from 0 to 3, the morphology changed gradually: acicular shape→short rod-like shape→Chinese script/skeleton like shape→rod-like shape. And the crystal structure of (Fe,Co)-rich intermetallics evolved from Monoclinic→Hexagonal→Simple cubic→Body-centered structure correspondingly. The optimal ratio of Co to Fe in intermetallics, which has Chinese script with hexagonal structure, was in the range of 1–2.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Quantum field as a quantum cellular automaton: The Dirac free evolution in one dimension

We present a quantum cellular automaton model in one space-dimension which has the Dirac equation as emergent. This model, a discrete-time and causal unitary evolution of a lattice of quantum systems, is derived from the assumptions of homogeneity, parity and time-reversal invariance. The comparison between the automaton and the Dirac evolutions is rigorously set as a discrimination problem between unitary channels. We derive an exact lower bound for the probability of error in the discrimination as an explicit function of the mass, the number and the momentum of the particles, and the duration of the evolution. Computing this bound with experimentally achievable values, we see that in that regime the QCA model cannot be discriminated from the usual Dirac evolution. Finally, we show that the evolution of one-particle states with narrow-band in momentum can be efficiently simulated by a dispersive differential equation for any regime. This analysis allows for a comparison with the dynamics of wave-packets as it is described by the usual Dirac equation. This paper is a first step in exploring the idea that quantum field theory could be grounded on a more fundamental quantum cellular automaton model and that physical dynamics could emerge from quantum information processing. In this framework, the discretization is a central ingredient and not only a tool for performing non-perturbative calculation as in lattice gauge theory. The automaton model, endowed with a precise notion of local observables and a full probabilistic interpretation, could lead to a coherent unification of a hypothetical discrete Planck scale with the usual Fermi scale of high-energy physics. - Highlights: • The free Dirac field in one space dimension as a quantum cellular automaton. • Large scale limit of the automaton and the emergence of the Dirac equation. • Dispersive differential equation for the evolution of smooth states on the automaton. • Optimal discrimination between the automaton evolution and the Dirac equation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Cation–Eutectic Transition via Sublattice Melting in CuInP 2 S 6 /In 4/3 P 2 S 6 van der Waals Layered Crystals

Single crystals of the van der Waals layered ferrielectric material CuInP 2 S 6 spontaneously phase separate when synthesized with Cu deficiency. In this paper, we identify a route to form and tune intralayer heterostructures between the corresponding ferrielectric (CuInP 2 S 6 ) and paraelectric (In 4/3 P 2 S 6 ) phases through control of chemical phase separation. We conclusively demonstrate that Cu-deficient Cu 1–x In 1+x/3 P 2 S 6 forms a single phase at high temperature. We also identify the mechanism by which the phase separation proceeds upon cooling. Above 500 K both Cu + and In 3+ become mobile, while P 2 S 6 4– anions maintain their structure. We therefore propose that this transition can be understood as eutectic melting on the cation sublattice. Such a model suggests that the transition temperature for the melting process is relatively low because it requires only a partial reorganization of the crystal lattice. As a result, varying the cooling rate through the phase transition controls the lateral extent of chemical domains over several decades in size. At the fastest cooling rate, the dimensional confinement of the ferrielectric CuInP 2 S 6 phase to nanoscale dimensions suppresses ferrielectric ordering due to the intrinsic ferroelectric size effect. Finally, intralayer heterostructures can be formed, destroyed, and re-formed by thermal cycling, thus enabling the possibility of finely tuned ferroic structures that can potentially be optimized for specific device architectures.

2D ferrielectric↗
DOE OSTI2022

Early-time measure in eternal inflation

In a situation like eternal inflation, where our data is replicated at infinitely-many other space-time events, it is necessary to make a prior assumption about our location to extract predictions. The principle of mediocrity entails that we live at asymptotic late times, when the occupational probabilities of vacua has settled to a near-equilibrium distribution. In this paper we further develop the idea that we instead exist during the approach to equilibrium, much earlier than the exponentially-long mixing time. In this case we are most likely to reside in vacua that are easily accessed dynamically. Using first-passage statistics, we prove that vacua that maximize their space-time volume at early times have: 1. maximal ever-hitting probability; 2. minimal mean first-passage time; and 3. minimal decay rate. These requirements are succinctly captured by an early-time measure. The idea that we live at early times is a predictive guiding principle, with many phenomenological implications. First, our vacuum should lie deep in a funneled region, akin to folding energy landscapes of proteins. Second, optimal landscape regions are characterized by relatively short-lived vacua, with lifetime of order the de Sitter Page time. For our vacuum, this lifetime is ~ 10 130 years, which is consistent with the Standard Model estimate due to Higgs metastability. Third, the measure favors vacua with small, positive vacuum energy. This can address the cosmological constant problem, provided there are sufficiently many vacua in the entire ensemble of funnels. As a concrete example, we study the Bousso-Polchinski lattice of flux vacua, and find that the early-time measure favors lattices with the fewest number of flux dimensions. This favors compactifications with a large hierarchy between the lightest modulus and all other Kähler and complex structure moduli.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Moment representation in the lattice Boltzmann method on massively parallel hardware

The widely-used lattice Boltzmann method (LBM) for computational fluid dynamics is highly scalable, but also significantly memory bandwidth-bound on current architectures. This paper presents a new regularized LBM implementation that reduces the memory footprint by only storing macroscopic, moment-based data. We show that the amount of data that must be stored in memory during a simulation is reduced by up to 47%. We also present a technique for cache-aware data re-utilization and show that optimizing cache utilization to limit data motion results in a similar improvement in time to solution. These new algorithms are implemented in the hemodynamics solver HARVEY and demonstrated using both idealized and realistic biological geometries. We develop a performance model for the moment representation algorithm and evaluate the performance on Summit.

Vardhan, Madhurima↗
DOE OSTI2025

Heterovalent Substitution of K 2 SrP 2 O 7 :Cr 3+ to Achieve Anti-Thermal-Quenching Broadband Near-Infrared Luminescence

Broadband near-infrared (NIR) light sources based on phosphor-converted light-emitting diodes are highly desirable for biochemical analysis and medical diagnosis applications. However, thermal quenching remains a demanding challenge for developing efficient NIR phosphors. Herein, we report the enhancement of both quantum efficiency and thermal stability in Cr 3+ -activated K 2 SrP 2 O 7 phosphors through a heterovalent substitution strategy by replacing Sr 2+ with Al 3+ in K 2 Sr 1–x Al x P 2 O 7 (0.05 ≤ x ≤ 0.2) to obtain optimized broadband NIR emission. Structural modulation via Al 3+ substitution leads to the optimized composition, K 2 Sr 0.88 Al 0.1 P 2 O 7 :0.02Cr 3+ , which emits across a broad NIR range of 650–1100 nm peaking at 807 nm with a full width at half-maximum of ∼130 nm under 448 nm excitation. Remarkably, its emission intensity at 150 °C remains 120% of the initial value at room temperature, demonstrating a rare antithermal-quenching behavior. Temperature-dependent XRD studies further reveal that Al 3+ substitution effectively suppresses lattice expansion at elevated temperatures, indicating enhanced lattice stability under thermal excitation. Detailed structural and spectral analyses show that the substitution enhances local site symmetry, reduces electron–phonon coupling, increases thermally induced absorption probability, and fortifies energetic barriers against nonradiative transitions. These synergistic effects collectively endow this NIR phosphor with a superior thermal stability. Furthermore, NIR light-emitting diodes fabricated with this phosphor exhibit strong potential for applications in information identification, nondestructive detection, and night vision technologies. This study demonstrates a local structure engineering strategy for designing thermally robust Cr 3+ -activated NIR phosphors, offering valuable insights into material discovery and NIR spectroscopy device development.

Cr3+↗
DOE OSTI2015

Theoretical and experimental investigations of the thermoelectric properties of Bi{sub 2}S{sub 3}

Electronic and transport properties of Bi{sub 2}S{sub 3} with various dopants are studied using density functional theory and experimental characterizations. First, principle calculations of thermoelectric properties are used to evaluate the thermoelectric potential of the orthorhombic Bi{sub 2}S{sub 3} structure. The computational screening of extrinsic defects is used to select the most favorable n-type dopants. Among all the dopants considered, hafnium and chlorine are identified as prospective dopants, whereas, e.g., germanium is found to be unfavorable. This is confirmed by experiment. Seebeck coefficient (S) and electrical conductivity (σ) measurements are performed at room temperature on pellets obtained by spark plasma sintering. An increase of power factors (S{sup 2}·σ) from around 50 up to 500 μW K{sup −2} m{sup −1} is observed for differently doped compounds. In several series of samples, we observed an optimum of power factor above 500 μW K{sup −2} m{sup −1} at room temperature for a chlorine equivalence of 0.25 mol. % BiCl{sub 3}. The obtained results are plotted on a semilogarithmic log (σ) versus S graph to demonstrate that a very strong linear trend that limits the power factor around 500 μW K{sup −2} m{sup −1} exists. Further improvement of Bi{sub 2}S{sub 3} as thermoelectric material will require finding new doping modes that will break through the observed trend. The results of stability tests demonstrate that properties of optimally doped Bi{sub 2}S{sub 3} are stable.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Iterated projected position algorithm for constructing exponentially localized generalized Wannier functions for periodic and nonperiodic insulators in two dimensions and higher

Localized bases play an important role in understanding electronic structure. In periodic insulators, a natural choice of localized basis is given by the Wannier functions which depend on a choice of unitary transform known as a gauge transformation. Over the past few decades, there have been many works that have focused on optimizing the choice of the gauge so that the corresponding Wannier functions are maximally localized or reflect some symmetry of the underlying system. In this work, we consider fully nonperiodic materials where the usual Wannier functions are not well defined and gauge optimization is impractical. To tackle the problem of calculating exponentially localized generalized Wannier functions in both periodic and nonperiodic systems, we discuss the ‘iterated projected position (IPP)” algorithm. Here, the IPP algorithm is based on matrix diagonalization and therefore unlike optimization-based approaches, it does not require initialization and cannot get stuck at a local minimum. Furthermore, the IPP algorithm is guaranteed by a rigorous analysis to produce exponentially localized functions under certain mild assumptions. We numerically demonstrate that the IPP algorithm can be used to calculate exponentially localized bases for the Haldane model, the Kane-Mele model (in both Z 2 invariant even and Z 2 invariant odd phases), and the p x + ip y model on a quasicrystal lattice.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Robust palladium hydride catalyst for electrocatalytic formate formation with high CO tolerance

Palladium is unique in the electrocatalytic reduction of CO 2 to formate because of its low or even near-equilibrium onset potential. However, the inevitably produced CO molecules poison and deactivate the catalyst surface, resulting in an insufficient operating lifetime (<30 min) for conventional and optimized Pd catalysts. In this work, we present a hydrogen-rich Palladium hydride catalyst (PdH0.5/C) derived from a one-step solvothermal synthesis. This catalyst showed a 93.1 % faradaic efficiency towards formate at – 0.4 V (vs RHE). The working lifetime reached a record of 4 h, which was ~15 times longer than a commercial Pd catalyst and outperformed all previous Pd-based electrocatalysts for CO 2 -HCOO – conversion. The high CO tolerance was attributed to the selectivity improvement induced by lattice hydrogen and the weak CO adsorption strength on diverse active sites (i.e. kink, step, and terrace). Isotopic analysis revealed a direct participation of the lattice hydrogen in the protonation of CO 2 molecules in formate formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

A Comparison Study of Offshore Wind Support Structures with Monopiles and Jackets for U.S. Waters: Preprint

U.S. experience in offshore wind is limited, and high costs are expected unless innovations are introduced in one or multiple aspects of the project, from the installed technology to the balance of system (BOS). The substructure is the main single component responsible for the BOS capital expenditure (CapEx) and thus one that, if improved, could yield significant levelized cost of energy (LCOE) savings. For projects in U.S. waters, multimember, lattice structures (also known as jackets) can render required stiffness for transitional water depths at potentially lower costs than monopiles (MPs). In this study, we used a systems engineering approach to evaluate the LCOE of prototypical wind power plants at six locations along the eastern seaboard and the Gulf of Mexico for both types of support structures. Using a reference wind turbine and actual metocean conditions for the selected sites, we calculated loads for a parked and an operational situation, and we optimized the MP- and jacket-based support structures to minimize their overall mass. Using a suite of cost models, we then computed their associated LCOE. For all water depths, the MP-based configurations were heavier than their jacket counterparts, but the overall costs for the MPs were less than they were for jackets up to depths of slightly less than 30 m. When the associated manufacturing and installation costs were included, jackets resulted in lower LCOE for depths greater than 40 m. These results can be used by U.S. stakeholders to understand the potential for different technologies at different sites, but the methodology illustrated in this study can be further employed to analyze the effects of innovations and design choices throughout wind power plant systems.

17 WIND ENERGY↗
DOE OSTI2019

Pressure-enhanced interplay between lattice, spin, and charge in the mixed perovskite La 2 FeMnO 6

Spin crossover plays a central role in the structural instability, net magnetic moment modification, metallization, and even in superconductivity in corresponding materials. Most reports on the pressure-induced spin crossover with a large volume collapse have so far focused on compounds with a single transition metal. Here we report a comprehensive high-pressure investigation of a mixed Fe-Mn perovskite La 2 FeMnO 6 . Under pressure, the strong coupling between Fe and Mn leads to a combined valence/spin transition: Fe 3+ (S=5/2) → Fe 2 + (S = 0) and Mn 3+ (S = 2) → Mn 4+ (S = 3/2), with an isostructural phase transition. The spin transitions of both Fe and Mn are offset by ~20 GPa of the onset pressure, and the lattice collapse occurs in between. Interestingly, Fe 3+ ion shows an abnormal behavior when it reaches a lower valence state (Fe 2+ ) accompanied by a +0.5 eV energy shift in the Fe K -absorption edge at 15 GPa. This process is associated with the charge-spin-orbital state transition from high spin Fe 3+ to low spin Fe 2+ , caused by the significantly enhanced t 2 g -e g crystal field splitting in the compressed lattice under high pressure. Density functional theory calculations confirm the energy preference of the high-pressure state with charge redistribution accompanied by spin state transition of Fe ions. Moreover, La 2 FeMnO 6 maintains semiconductor behaviors even when the pressure reached 144.5 GPa as evidenced by the electrical transport measurements, despite the huge resistivity decreasing seven orders of magnitude compared with that at ambient pressure. The investigation carried out here demonstrates high flexibility of double perovskites and their good potentials for optimizing the functionality of these materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Flux growth and magneto-transport properties of cubic antiperovskite Ca3PbO single crystals

Highlights: • Antiperovskite Ca{sub 3}PbO is predicted to be a three-dimensional Dirac fermion system. • Cubic crystals, 1 mm in size, were obtained by a Ca-self-flux method. • The crucible and sealing method were critical factors to reduce carrier density. • Shubnikov-de Haas oscillations were clearly observed, indicating its high purity. - Abstract: We report the single crystal growth of cubic antiperovskite Ca{sub 3}PbO by a Ca-self-flux method. Cubic crystals, 1 mm in size, were successfully obtained through the use of iron crucibles sealed in stainless steel capsules. The crucible material and sealing method were found to be critical factors for achieving large crystals with low carrier density. The crystals were subsequently characterized by powder and single-crystal x-ray diffraction experiments, electron-probe microanalysis, and Hall effect measurements. Through the use of short stainless steel rods as tight caps for the crucible and fillers to occupy extra space in the capsule, the Ca evaporation loss of the flux, which contributes to Ca vacancy formation, was effectively reduced. Hence, the hole carrier density in the single crystal was reduced to 4.0 × 10{sup 19} cm{sup −3}. The crystal synthesized under optimized growth conditions showed clear Shubnikov-de Haas oscillations, indicating its high purity and homogeneity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Anharmonic theory of superconductivity in the high-pressure materials

Electron-phonon superconductors at high pressures have displayed the highest values of critical superconducting temperature Tc on record, now rapidly approaching room temperature. Despite the importance of high-P superconductivity in the quest for room-temperature superconductors, a mechanistic understanding of the effect of pressure and its complex interplay with phonon anharmonicity and superconductivity is missing, as numerical simulations can bring only system-specific details, clouding out key players controlling the physics. In this work, we develop a minimal model of electron-phonon superconductivity under an applied pressure which takes into account the anharmonic decoherence of the optical phonons. We find that T c behaves nonmonotonically as a function of the ratio Γ/ω 0 , where Γ is the optical phonon damping and ω 0 is the optical phonon energy at zero pressure and momentum. Optimal pairing occurs for a critical ratio Γ/ω 0 when the phonons are on the verge of decoherence (“diffusonlike” limit). Our framework gives insights into recent experimental observations of T c as a function of pressure in the complex BCS material TlInTe 2 .

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Machine Learning Approaches for Rare-Earth Silicate Environmental Barrier Coating Thermochemical and Thermomechanical Property Predictions

Environmental barrier coatings (EBCs) are a necessary enabling technology for the transition from superalloys to silicon carbide (SiC) ceramic matrix composites (CMCs) in gas turbine engines for increased efficiency and decreased fuel costs. SiC-based CMCs are prone to oxidation-based degradation in the engine hot section, and rare-earth (RE) silicates are promising candidates for EBCs due to their close thermal expansion match to the composite substrate and oxidation resistance. However, the design of EBCs is hindered by the large chemical space of candidate materials and the difficulty in obtaining material properties for engineering optimization. This is especially difficult as research continues into mixed-cation or “high-entropy” RE silicates. First-principles computational methods such as density functional theory (DFT) are highly effective at calculating material properties to guide coating design but are limited by their computational cost. Atomistic simulations have the potential to both accelerate property calculations and expand the properties able to be calculated due to their lower computational compared to DFT. However, they require interatomic potentials (IAPs) specific to the material system of interest, and, to our knowledge, there are no suitable IAPs for RE silicates. Machine learning (ML) is a promising technique to accelerate material property predictions indirectly by generating IAPs for atomistic simulations or via direct prediction. In this work, we present two ML approaches to accelerate the calculation of RE silicate properties relevant to EBC design: 1) a ML-derived interatomic potential (IAP) for atomistic simulations of yttrium disilicate (Y2Si2O7) from DFT training data, and 2) a neural network (NN) model to directly predict thermochemical properties of RE silicates and oxides directly from easily obtainable unit cell parameters. Classical MD simulations using the IAP yield lattice properties and bond lengths in good agreement with both DFT and experimental results from x-ray diffraction. Thermodynamic properties calculated using the finite-displacement phonon method and quasi-harmonic approximation were orders of magnitude faster than DFT with good agreement to the DFT results. The IAP was also used to calculate properties such as coefficient of thermal expansion (CTE) that require large simulation supercells and are therefore difficult with DFT. The IAP correctly predicted the anisotropic nature of the CTE in three different phases of Y2Si2O7. The NN model predicts constant pressure heat capacity, Cp, orders of magnitude faster than DFT calculations, which can enable its use as a surrogate model for multiscale simulations. The two methods presented in this work demonstrate the utility of ML for accelerating the prediction of RE silicate properties, which can in turn accelerate EBC design and optimization.

machine learning↗
DOE OSTI2021

Spectral properties of three-dimensional Anderson model

The three-dimensional Anderson model represents a paradigmatic model to understand the Anderson localization transition. In this work we first review some key results obtained for this model in the past 50 years, and then study its properties from the perspective of modern numerical approaches. Our main focus is on the quantitative comparison between the level sensitivity statistics and the level statistics. While the former studies the sensitivity of Hamiltonian eigenlevels upon inserting a magnetic flux, the latter studies the properties of unperturbed eigenlevels. We define two versions of dimensionless conductance, the first corresponding to the width of the level curvature distribution relative to the mean level spacing, and the second corresponding to the ratio of the Heisenberg time and the Thouless time obtained from the spectral form factor. We show that both conductances look remarkably similar around the localization transition, in particular, they predict a nearly identical critical point consistent with other well-established measures of the transition. We then study some further properties of those quantities: for level curvatures, we discuss particular similarities and differences between the width of the level curvature distribution and the characteristic energy studied by Edwards and Thouless (1972) in their pioneering work, in which the hopping at one lattice edge is changed from periodic to antiperiodic boundary conditions. In the context of the spectral form factor, we show that at the critical point it enters a broad time-independent regime, in which its value is consistent with the level compressibility obtained from the level variance. Finally, we test the scaling solution of the average level spacing ratio in the crossover regime using the cost function minimization approach introduced recently in Šuntajs et al. (2020). The latter approach seeks for the optimal scaling solution in the vicinity of the crossing point, while at the same time it allows for the crossing point to drift due to finite-size corrections. We find that the extracted transition point and the scaling coefficient agree with those from the literature to high numerical accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Data-driven reduced-order models for port-Hamiltonian systems with operator inference

Hamiltonian operator inference has been developed in Sharma et al. (2022) to learn structure-preserving reduced-order models (ROMs) for Hamiltonian systems. The method constructs a low-dimensional model using only data and knowledge of the functional form of the Hamiltonian. The resulting ROMs preserve the intrinsic structure of the system, ensuring that the mechanical and physical properties of the system are maintained. In this work, we extend this approach to port-Hamiltonian systems, which generalize Hamiltonian systems by including energy dissipation, external input, and output. Based on snapshots of the system’s state and output, together with the information about the functional form of the Hamiltonian, reduced operators are inferred through optimization and are then used to construct data-driven ROMs. To further alleviate the complexity of evaluating nonlinear terms in the ROMs, a hyper-reduction method via discrete empirical interpolation is applied. Accordingly, we derive error estimates for the ROM approximations of the state and output. Lastly, we demonstrate the structure preservation, as well as the accuracy of the proposed port-Hamiltonian operator inference framework, through numerical experiments on a linear mass–spring-damper problem and a nonlinear Toda lattice problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Neural network interatomic potential-driven analysis of phase stability in Ti–V alloys at the atomistic scale

The evolution of the ω phase in titanium–vanadium (Ti–V) alloys is critical for their mechanical properties, particularly in aerospace and biomedical applications. Here, this study employs a Rapid Artificial Neural Network (RANN) potential to model the ω phase evolution at the atomistic level, demonstrating a high degree of consistency with experimental observations, unlike the Modified Embedded Atom Method (MEAM), which fails to capture this phase transformation accurately. RANN simulations replicate key phenomena such as the nucleation of α precipitates at ω/β interfaces and accurate lattice orientations, enhancing our understanding of phase stability and transformation kinetics. The findings affirm that RANN potentials can significantly improve the prediction accuracy of complex material behaviors, offering a powerful tool for designing advanced materials with tailored properties such as solute effect in various stacking fault energies. This approach not only bridges the gap between theoretical predictions and empirical data but also sets a new direction for future research in materials science, emphasizing the integration of machine learning techniques in the development and optimization of new alloys.

36 MATERIALS SCIENCE↗