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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Predicting phase behavior of grain boundaries with evolutionary search and machine learning

The study of grain boundary phase transitions is an emerging field until recently dominated by experiments. The major bottleneck in the exploration of this phenomenon with atomistic modeling has been the lack of a robust computational tool that can predict interface structure. Here we develop a computational tool based on evolutionary algorithms that performs efficient grand-canonical grain boundary structure search and we design a clustering analysis that automatically identifies different grain boundary phases. Its application to a model system of symmetric tilt boundaries in Cu uncovers an unexpected rich polymorphism in the grain boundary structures. We find new ground and metastable states by exploring structures with different atomic densities. Our results demonstrate that the grain boundaries within the entire misorientation range have multiple phases and exhibit structural transitions, suggesting that phase behavior of interfaces is likely a general phenomenon.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Artificial intelligence-driven approaches for materials design and discovery

Materials design is an important component of modern science and technology, yet traditional approaches rely heavily on trial and error and can be inefficient. Computational techniques, enhanced by modern artificial intelligence, have reshaped the landscape of designing new materials. Among these approaches, inverse design has shown great promise in designing materials that meet specific property requirements. Here, in this Review, we present key computational advances in materials design over the past few decades. We follow the evolution of relevant materials design techniques, from high-throughput forward machine learning methods and evolutionary algorithms, to advanced artificial intelligence strategies such as reinforcement learning and deep generative models. We highlight the paradigm shift from conventional screening approaches to inverse generation driven by deep generative models. Finally, we discuss current challenges and future perspectives of materials inverse design. This Review may serve as a brief guide to the approaches, progress and outlook of designing future functional materials with technological relevance.

computational methods↗
DOE OSTI2015

In silico prediction of MOFs with high deliverable capacity or internal surface area

Metal–organic frameworks (MOFs) offer unprecedented atom-scale design and structural tunability, largely due to the vast number of possible organic linkers which can be utilized in their assembly. Exploration of this space of linkers allows identification of ranges of achievable material properties as well as discovery of optimal materials for a given application. Experimental exploration of the linker space has to date been quite limited due to the cost and complexity of synthesis, while high-throughput computational studies have mainly explored MOF materials based on known or readily available linkers. Here an evolutionary algorithm for de novo design of organic linkers for metal–organic frameworks is used to predict MOFs with either high methane deliverable capacity or methane accessible surface area. Known chemical reactions are applied in silico to a population of linkers to discover these MOFs. Through this design strategy, MOF candidates are found in the ten symmetric networks acs, cds, dia, hxg, lvt, nbo, pcu, rhr, sod, and tbo. Furthermore, the correlation between deliverable capacities and surface area is network dependent.

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

Super-oxidation of silicon nanoclusters: magnetism and reactive oxygen species at the surface

Oxidation of silicon nanoclusters depending on the temperature and oxygen pressure is explored from first principles using the evolutionary algorithm, and structural and thermodynamic analysis. From our calculations of 90 SinOm clusters we found that under normal conditions oxidation does not stop at the stoichiometric SiO2 composition, as it does in bulk silicon, but goes further placing extra oxygen atoms on the cluster surface. These extra atoms are responsible for light emission, relevant to reactive oxygen species and many of them are magnetic. We argue that the super-oxidation effect is size-independent and discuss its relevance to nanotechnology and miscellaneous applications, including biomedical ones.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Ferroelectric 2D antimony oxides with wide bandgaps

The first two-dimensional (2D) polymorphs of antimony dioxide, namely, γ-Sb 2 O 4 and δ-Sb 2 O 4 , are predicted using the evolutionary algorithm combined with first-principles density functional theory (DFT) calculations. Out-of-plane ferroelectricity is found in γ-Sb 2 O 4 , while in-plane ferroelectricity is found in δ-Sb 2 O 4 . The predicted dipole moments of γ-Sb 2 O 4 and δ-Sb 2 O 4 phases are 36.63 and 14.96 eÅ, respectively, implying that they can be good candidates for making ferroelectric devices. Further, the calculations show that doping with other group V elements or applying strain can lower the switching energy barriers and thus facilitate switching. Results from GW calculations show indirect band gaps of 5.51 and 3.39 eV for γ-Sb 2 O 4 and δ-Sb 2 O 4 in their monolayers, respectively. Raman spectra are calculated to facilitate the experimental investigation of the predicted structures. The existence of both in-plane and out-of-plane 2D ferroelectricity and the large band gaps make this material system particularly interesting for potential applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Realization of a reversible switching in TaO{sub 2} polymorphs via Peierls distortion for resistance random access memory

Transition-metal-oxide based resistance random access memory (RRAM) is a promising candidate for next-generation universal non-volatile memories. Searching and designing appropriate materials used in the memories becomes an urgent task. Here, a structure with the TaO{sub 2} formula was predicted using evolutionary algorithms in combination with first-principles calculations. This triclinic structure (T-TaO{sub 2}) is both energetically and dynamically more favorable than the commonly believed rutile structure (R-TaO{sub 2}). The metal-insulator transition (MIT) between metallic R-TaO{sub 2} and T-TaO{sub 2} (band gap: 1.0 eV) is via a Peierls distortion, which makes TaO{sub 2} a potential candidate for RRAM. The energy barrier for the reversible phase transition is 0.19 eV/atom and 0.23 eV/atom, respectively, suggesting low power consumption for the resistance switch. The present findings about the MIT as the resistance-switch mechanism in Ta-O system will stimulate experimental work to fabricate tantalum oxides based RRAM.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Coherent control of plasma dynamics by feedback-optimized wavefront manipulation

Plasmas generated by an intense laser pulse can support coherent structures such as large amplitude wakefield that can affect the outcome of an experiment. We investigate the coherent control of plasma dynamics by feedback-optimized wavefront manipulation using a deformable mirror. The experimental outcome is directly used as feedback in an evolutionary algorithm for optimization of the phase front of the driving laser pulse. In this paper, we applied this method to two different experiments: (i) acceleration of electrons in laser driven plasma waves and (ii) self-compression of optical pulses induced by ionization nonlinearity. The manipulation of the laser wavefront leads to orders of magnitude improvement to electron beam properties such as the peak charge, beam divergence, and transverse emittance. The demonstration of coherent control for plasmas opens new possibilities for future laser-based accelerators and their applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Determination of ground and excited state dipole moments via electronic Stark spectroscopy: 5-methoxyindole

The dipole moments of the ground and lowest electronically excited singlet state of 5-methoxyindole have been determined by means of optical Stark spectroscopy in a molecular beam. The resulting spectra arise from a superposition of different field configurations, one with the static electric field almost parallel to the polarization of the exciting laser radiation, the other nearly perpendicular. Each field configuration leads to different intensities in the rovibronic spectrum. With an automated evolutionary algorithm approach, the spectra can be fit and the ratio of both field configurations can be determined. A simultaneous fit of two spectra with both field configurations improved the precision of the dipole moment determination by a factor of two. We find a reduction of the absolute dipole moment from 1.59(3) D to 1.14(6) D upon electronic excitation to the lowest electronically excited singlet state. At the same time, the dipole moment orientation rotates by 54{sup ∘} showing the importance of the determination of the dipole moment components. The dipole moment in the electronic ground state can approximately be obtained from a vector addition of the indole and the methoxy group dipole moments. However, in the electronically excited state, vector addition completely fails to describe the observed dipole moment. Several reasons for this behavior are discussed.

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

On the adaptivity and complexity embedded into differential evolution

This research deals with the comparison of the two modern approaches for evolutionary algorithms, which are the adaptivity and complex chaotic dynamics. This paper aims on the investigations on the chaos-driven Differential Evolution (DE) concept. This paper is aimed at the embedding of discrete dissipative chaotic systems in the form of chaotic pseudo random number generators for the DE and comparing the influence to the performance with the state of the art adaptive representative jDE. This research is focused mainly on the possible disadvantages and advantages of both compared approaches. Repeated simulations for Lozi map driving chaotic systems were performed on the simple benchmark functions set, which are more close to the real optimization problems. Obtained results are compared with the canonical not-chaotic and not adaptive DE. Results show that with used simple test functions, the performance of ChaosDE is better in the most cases than jDE and Canonical DE, furthermore due to the unique sequencing in CPRNG given by the hidden chaotic dynamics, thus better and faster selection of unique individuals from population, ChaosDE is faster.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

First principles crystal engineering of nonlinear optical materials. I. Prototypical case of urea

The crystalline materials with nonlinear optical (NLO) properties are critically important for several technological applications, including nanophotonic and second harmonic generation devices. Urea is often considered to be a standard NLO material, due to the combination of non-centrosymmetric crystal packing and capacity for intramolecular charge transfer. Various approaches to crystal engineering of non-centrosymmetric molecular materials were reported in the literature. Here we propose using global lattice energy minimization to predict the crystal packing from the first principles. We developed a methodology that includes the following: (1) parameter derivation for polarizable force field AMOEBA; (2) local minimizations of crystal structures with these parameters, combined with the evolutionary algorithm for a global minimum search, implemented in program USPEX; (3) filtering out duplicate polymorphs produced; (4) reoptimization and final ranking based on density functional theory (DFT) with many-body dispersion (MBD) correction; and (5) prediction of the second-order susceptibility tensor by finite field approach. This methodology was applied to predict virtual urea polymorphs. After filtering based on packing similarity, only two distinct packing modes were predicted: one experimental and one hypothetical. DFT + MBD ranking established non-centrosymmetric crystal packing as the global minimum, in agreement with the experiment. Finite field approach was used to predict nonlinear susceptibility, and H-bonding was found to account for a 2.5-fold increase in molecular hyperpolarizability to the bulk value.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Measurements of low-mode asymmetries in the areal density of laser-direct-drive deuterium–tritium cryogenic implosions on OMEGA using neutron spectroscopy

Areal density is one of the key parameters that determines the confinement time in inertial confinement fusion experiments, and low-mode asymmetries in the compressed fuel are detrimental to the implosion performance. The energy spectra from the scattering of the primary deuterium–tritium (DT) neutrons off the compressed cold fuel assembly are used to investigate low-mode nonuniformities in direct-drive cryogenic DT implosions at the Omega Laser Facility. For spherically symmetric implosions, the shape of the energy spectrum is primarily determined by the elastic and inelastic scattering cross sections for both neutron-deuterium and neutron-tritium kinematic interactions. Two highly collimated lines of sight, which are positioned at nearly orthogonal locations around the OMEGA target chamber, record the neutron time-of-flight signal in the current mode. An evolutionary algorithm is being used to extract a model-independent energy spectrum of the scattered neutrons from the experimental neutron time-of-flight data and is used to infer the modal spatial variations (l = 1) in the areal density. Experimental observations of the low-mode variations of the cold-fuel assembly (ρL 0 + ρL 1 ) show good agreement with a recently developed model, indicating a departure from the spherical symmetry of the compressed DT fuel assembly. As a result, another key signature that has been observed in the presence of a low-mode variation is the broadening of the kinematic end-point due to the anisotropy of the dense fuel conditions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

High pressure-induced distortion in face-centered cubic phase of thallium

The complex and unusual high-pressure phase transition of III-A (i.e. Al, Ga, and In) metals have been investigated in the last several decades because of their interesting periodic table position between the elements having metallic and covalent bonding. Here, our present first principles-based electronic structure calculations and experimental investigation have revealed the unusual distortion in face-centered cubic (f.c.c.) phase of the heavy element thallium (Tl) induced by the high pressure. We have predicted body-centered tetragonal (b.c.t) phase at 83 GPa using an evolutionary algorithm coupled with ab initio calculations, and this prediction has been confirmed with a slightly distorted parameter (2–√ × a-c)/c lowered by 1% using an angle-dispersive X-ray diffraction technique. The density functional theory (DFT)-based calculations suggest that s–p mixing states and the valence-core overlapping of 6s and 5d states play the most important roles for the phase transitions along the pathway h.c.p→f.c.c.→b.c.t.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Genetic programming for the nuclear many-body problem: a guide

Genetic Programming (GP) is an evolutionary algorithm that generates computer programs, or mathematical expressions, to solve complex problems. In this Guide, we demonstrate how to use GP to develop surrogate models to mitigate the computational costs of modeling atomic nuclei with ever increasing complexity. The computational burden escalates when uncertainty quantification is pursued, or when observables must be globally computed for thousands of nuclei. By studying three models in which the mean field depends on the total particle density self-consistently, we show that by constructing reduced order models supported by GP one can speed up many-body computations by several orders of magnitude with a negligible loss in accuracy.

dimensionality reduction↗
DOE OSTI2025

Harnessing the power of gradient-based simulations for multi-objective optimization in particle accelerators

Abstract Particle accelerator operation requires simultaneous optimization of multiple objectives. Multi-objective optimization (MOO) is particularly challenging due to trade-offs between the objectives. Evolutionary algorithms, such as genetic algorithms (GAs), have been leveraged for many optimization problems, however, they do not apply to complex control problems by design. This paper demonstrates the power of differentiability for solving MOO problems in particle accelerators using a deep differentiable reinforcement learning (DDRL) algorithm. We compare the DDRL algorithm with model-free reinforcement learning (MFRL), GA, and Bayesian optimization (BO) for simultaneous optimization of heat load and trip rates in the continuous electron beam accelerator facility. The underlying problem enforces strict constraints on both individual states and actions as well as cumulative (global) constraints on energy requirements of the beam. Using historical accelerator data, we develop a physics-based surrogate model which is differentiable and allows for back-propagation of gradients. The results are evaluated in the form of a Pareto-front with two objectives. We show that the DDRL outperforms MFRL, BO, and GA on high dimensional problems.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Predicting the ground-state structure of sodium boride

Binary borides has been a subject of extensive research. However, the exact compositions and crystal structures of sodium borides remained controversial. Furthermore, using the ab initio variable-composition evolutionary algorithm, a new stable Na 2 B 30 with I2 1 2 1 2 1 symmetry (I2 1 2 1 2 1 –Na 2 B 30 ) is found, which is –7.38 meV / atom lower in energy than the Imma–Na 2 B 30 structure reported by experimentalists. Interestingly, the Imma–Na 2 B 30 structure is predicted to be a topological nodal line semimetal, which may result in superior electronic transport. In contrast, I2 1 2 1 2 1 –Na 2 B 30 is an ultrahard semiconductor with an unprecedented open-framework structure, whose interstitial helical boron sublattice enhances its hardness and energetic stability.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Magnetic borophenes from an evolutionary search

A computational methodology based on ab initio evolutionary algorithms and spin-polarized density functional theory was developed to predict two-dimensional magnetic materials. Its application to a model system borophene reveals an unexpected rich magnetism and polymorphism. A metastable borophene with nonzero thickness is an antiferromagnetic semiconductor from first-principles calculations, and can be further tuned into a half-metal by finite electron doping. In this borophene, the buckling and coupling among three atomic layers are not only responsible for magnetism, but also result in an out-of-plane negative Poisson's ratio under uniaxial tension, making it the first elemental material possessing auxetic and magnetic properties simultaneously.

2-dimensional systems↗
DOE OSTI2019

Anharmonic and Anomalous Trends in the High-Pressure Phase Diagram of Silicon

A multifaceted first-principles approach utilizing density functional theory, evolutionary algorithms, and lattice dynamics was used to construct the phase diagram of silicon up to 4 TPa and 26,000 K. These calculations predicted that (1) an anomalous sequence of face-centered cubic (fcc) to body-centered cubic (bcc) to simple cubic (sc) crystalline phase transitions occur at pressures of 2.87 TPa and 3.89 TPa, respectively, along the cold curve; (2) the orthorhombic phases of Imma and Cmce-16 appear on the phase diagram only when the anharmonic contribution to the Gibbs free energy is taken into account; and (3) a drastic change in the slope of the principal Hugoniot is observed if the negative thermal expansion coefficient of the cubic diamond phase is taken into account through anharmonic effects.

36 MATERIALS SCIENCE↗