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At least 523 records · Page 29

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DOE OSTI2018

Genarris: Random generation of molecular crystal structures and fast screening with a Harris approximation

Herein, we present Genarris, a Python package that performs configuration space screening for molecular crystals of rigid molecules by random sampling with physical constraints. For fast energy evaluations, Genarris employs a Harris approximation, whereby the total density of a molecular crystal is constructed via superposition of single molecule densities. Dispersion-inclusive density functional theory is then used for the Harris density without performing a self-consistency cycle. Genarris uses machine learning for clustering, based on a relative coordinate descriptor developed specifically for molecular crystals, which is shown to be robust in identifying packing motif similarity. In addition to random structure generation, Genarris offers three workflows based on different sequences of successive clustering and selection steps: the "Rigorous" workflow is an exhaustive exploration of the potential energy landscape, the "Energy" workflow produces a set of low energy structures, and the "Diverse" workflow produces a maximally diverse set of structures. The latter is recommended for generating initial populations for genetic algorithms. Here, the implementation of Genarris is reported and its application is demonstrated for three test cases. Published by AIP Publishing.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2018

Temporal feedback control of high-intensity laser pulses to optimize ultrafast heating of atomic clusters

We describe how active feedback routines can be applied at a limited repetition rate (5 Hz) to optimize high-power (>10 TW) laser interactions with clustered gases. Optimization of x-ray production from an argon cluster jet, using a genetic algorithm, approximately doubled the measured energy through temporal modification of the 150 mJ driving laser pulse. This method achieved an increased radiation yield through exploration of a multi-dimensional parameter space, without requiring detailed a priori knowledge of the complex cluster dynamics. The optimized laser pulses exhibited a slow rising edge to the intensity profile, which enhanced the laser energy coupling into the cluster medium, compared to the optimally compressed FWHM pulse (40 fs). This report suggests that this technique can be more widely utilized for control of intense pulsed secondary radiation from petawatt-class laser systems.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2018

On a physics-based model equation for shock-position evolution in PMMA

A governing differential equation for shock position in PMMA was derived from momentum conservation and an experimentally determined decay law for shock pressure. A new multi-diagnostic characterization method for measuring detonator pressure and wave shape output in PMMA witness blocks provided temporally resolved, 1-D, shock-position data that was iteratively fit by solutions to the governing equation via a unique genetic algorithm solver. The goal was to calculate a solution that describes the temporal evolution of shock pressure in PMMA starting at the detonator interface. The empirical decay law was investigated using experimental data, where different regimes were considered for the decay coefficients. A successful solution provides extensive performance information that is directly relevant to the understanding and characterization of detonator function.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

Investigation of high X-ray conversion efficiency Kr filled gas sources at the National Ignition Facility

In this work, we report on the performance of high x-ray fluence Kr K-shell sources that are being developed for high energy density experiments. These targets are 4.1 mm in diameter 4.4 mm tall hollow epoxy tubes having a 40 μm thick wall holding 1.5 atm of Kr gas. For these shots, the National Ignition Facility laser delivered a nominally constant total energy of ≈750 kJ of 351 nm (3ω) light at the three power levels [e.g., ≈120 (low), ≈145 (medium), and ≈210 TW (high)]. The Kr K-shell (E photon = 8–20 keV) x-ray radiant intensity and radiant energy (kJ/sr) of these sources were found to increase as a function of laser power but began to plateau at the highest laser power. The Kr K-shell radiant energy increased from ≈1 kJ/sr at ≈120 TW to ≈2 kJ/sr at ≈210 TW. Radiation hydrodynamics simulations predict radiant energies to be always higher than these measurements. The increase in K-shell emission is attributed to its strong dependence on the electron temperature. Electron temperature distributions were inferred from measured Heα and Lyα line emission through the use of a genetic algorithm and Scram modeling. The inferred temperatures from the experiment are 20% to 30% higher than those predicted from modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Pt 8 cluster on alumina under a pressure of hydrogen: Support-dependent reconstruction from first-principles global optimization

Alumina supported Pt nano clusters under hydrogen environment play a crucial role for many heterogeneous catalysis applications. As such, we conducted grand canonical genetic algorithm (GCGA) simulations for supported Pt 8 clusters in hydrogen gas environment to study the intra-cluster, cluster-support, and cluster-adsorbate interactions. Two alumina surfaces, α-Al 2 O 3 (0001) and $γ$-Al 2 O 3 (100), and two conditions T=600°C, p H2 = 0.1bar and T=25°C, p H2 = 1.0 bar were considered corresponding to low and high hydrogen chemical potential $μ$ H , respectively. The low free energy ensemble of Pt 8 is decorated by a medium (2–12 H), resp. high (20–30 H), number of hydrogen atoms under equilibrium at low $μ$ H , respectively, high $μ$ H , and undergoes different morphology transformations on the two surfaces. On α-Al2O3(0001), Pt8 is mostly 3D but very fluxional in structure at low μH and converts to open one-layer 2D structures with minimal fluxionality at high μH, whereas on $γ$-Al 2 O 3 (100), the exact opposite occurs, and Pt 8 clusters present one-layer 2D shapes at low $μ$ H and switch into compact 3D shapes under high $μ$ H , during which the Pt 8 cluster preserves moderate fluxionality. Further analysis reveals similar Pt–Pt bond length increase when switching from low $μ$ H to high $μ$ H on both surfaces, though morphology transformations are different. Electronic structure analysis shows the existence of bonding interactions between Pt and Lewis acidic Al 3+ sites along with the Pt – O interaction, which implies the necessity to include Al neighbors to discuss the electronic structure of small Pt clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Augmenting machine learning of energy landscapes with local structural information

We present a machine learning approach for accurately predicting formation energies of binary compounds in the context of crystal structure predictions. The success of any machine learning model depends significantly on the choice of representation used to encode the relevant physical information into machine-learnable data. We test different representation schemes based on partial radial and angular distribution functions (RDF+ADF) on Al–Ni and Cd–Te structures generated using our genetic algorithm for structure prediction. We observe a remarkable improvement in predictive accuracy upon transitioning from global to atom-centered representations, resulting in a threefold decrease in prediction errors. We show that a support vector regression model using a combination of atomic radial and angular distribution functions performs best at the formation energy prediction task, providing small root mean squared errors of 3.9 meV/atom and 10.9 meV/atom for Al–Ni and Cd–Te, respectively. We test the performance of our models against common traditional descriptors and find that RDF- and ADF-based representations significantly outperform many of those in the prediction of formation energies. The high accuracy of predictions makes our machine learning models great candidates for the exploration of energy landscapes.

Honrao, Shreyas J. (ORCID:0000000166155257)↗

DOE OSTI2021

Aperiodic optical coatings for neutral-color semi-transparent organic photovoltaics

Semi-transparent organic photovoltaics (ST-OPVs) have the potential for integration with windows for ubiquitous power generating applications. Typically, such applications require that ST-OPVs be neutrally transparent across the visible and exhibit both a high average photopic transmittance (APT) and color rendering index, as well as iso-energetic chromaticity coordinates. In this work, we demonstrate the design and use of optical coatings to achieve ST-OPVs with a neutral visible transmittance of APT = 50%, a power conversion efficiency of 8.3%, and optical properties that are independent of a ± 30° variation in the solar angle of incidence. As a result, these simple optical coatings are rapidly designed using a genetic algorithm and transfer matrix formalism.

14 SOLAR ENERGY↗

DOE OSTI2024

A transferable classical force field to describe glyme based lithium solvate ionic liquids

A non-polarizable force field for lithium (Li + ) and bis(trifluoromethanesulfonyl)imide (TFSI – ) ions solvated in diglyme at around 0.2 mol fraction salt concentration was developed based on ab initio molecular dynamics (AIMD) simulations and a modified polymer consistent force field model. A force–torque matching based scheme, in conjunction with a genetic algorithm, was used to determine the Lennard-Jones (LJ) parameters of the ion–ion and ion–solvent interactions. This force field includes a partial charge scaling factor and a scaling factor for the 1–4 interactions. The resulting force field successfully reproduces the radial distribution function of the AIMD simulations and shows better agreement compared to the unmodified force field. The new force field was then used to simulate salt solutions with glymes of increasing chain lengths and different salt concentrations. The comparison of the MD simulations, using the new force field, with experimental data at different salt concentrations and AIMD simulations on equimolar concentrations of the triglyme system demonstrates the transferability of the force field parameters to longer glymes and higher salt concentrations. Furthermore, the force field appears to reproduce the features of the experimental x-ray structure factors, suggesting accuracy beyond the first solvation shell, for equimolar salt solutions using both triglyme and tetraglyme as the solvent. Altogether, the new force field was found to accurately reproduce the molecular descriptions of LiTFSI-glyme systems not only at various salt concentrations but also with glymes of different chain lengths. Thus, the new force field provides a useful and accurate tool to perform in silico studies of this family of systems at the atomistic level.

25 ENERGY STORAGE↗

DOE OSTI2024

Enhancing Thomson scattering polychromator performance with multi-pass spectral filters

In photon-deficient, noncollective Thomson scattering diagnostics, filter polychromators are typically employed in the spectral analysis of Thomson-scattered signals to achieve acceptable signal-to-noise performance. Currently, the most common polychromator filter configuration employs a set of single-passband optical filters that define individual spectral channels. Here, we introduce a new spectral analysis method for Thomson scattering based on spectral filters with multiple passbands, referred to as Thomson scattering spectral multiplexing. Implementing multi-bandpass spectral filters on polychromators increases the achievable range of electron temperature measurement for a given number of filters employed. In addition, Thomson scattering spectral multiplexing reduces systematic measurement uncertainty, with fewer required spectral channels, thereby decreasing light loss from reduced optical element interactions. A multi-bandpass filter set, optimized by a genetic algorithm, has been successfully installed and tested on the Helically Symmetric eXperiment (HSX), demonstrating the benefits of the Thomson scattering spectral multiplexing method.

Instruments & Instrumentation↗

DOE OSTI2025

An experimentally informed design process for future inertial confinement fusion facilities

The achievement of ignition in the laboratory has renewed interest in defining the requirements for a future high-gain inertial confinement fusion (ICF) facility. Our best chance of predicting future ICF performance is with 3-D radiation hydrodynamic simulations that have been benchmarked against experimental data, but their high computational cost is prohibitive for use in practical design studies. We introduce a hierarchical approach where 3-D simulations are tuned to match experimental measurements and used to train 3-D degradation models in 1-D simulations allowing for accurate predictions over the entire OMEGA direct-drive database. A genetic algorithm was used in combination with the trained 1-D simulations to search for optimal direct-drive implosion designs at driver energies ranging from 20 kJ to 10 MJ. As the fidelity of 3-D codes improves, this approach will provide a viable experimentally informed tool for defining the next ICF facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Bridging material models across scales: An integrated approach to equation of state and molecular dynamics modeling of copper

New uncertainty-aware equation of state (EOS) and electrical conductivity (EC) models for copper have been developed. The multiphase EOS/EC models are fit to experimental solid/liquid EC isobar measurements as well as density-functional theory molecular dynamics (DFT-MD) EC calculations in both expanded and compressed regimes (0.1–16 g/ cm 3 ⁠). The liquid and solid EOS phases were fit to available experimental data along with additional DFT-MD data over the same range as the EC. Leveraging the DFT-MD data, a corresponding machine-learned interatomic potential (MLIAP) for copper was trained using genetic-algorithm optimization. The copper MLIAP was constrained by EOS shock points at high compressions. The final EOS bounded MLIAP proves to be stable over a large density range (approximately 0.1–20 g/ cm 3 ) with good agreement to an isothermal compression curve, shock Hugoniot, and liquid speed of sound measurements at high pressures (100s of GPa).

Acoustic measurements and instrumentation↗

DOE OSTI2015

High-yield hydrogen production from biomass by in vitro metabolic engineering: Mixed sugars coutilization and kinetic modeling

The use of hydrogen (H 2 ) as a fuel offers enhanced energy conversion efficiency and tremendous potential to decrease greenhouse gas emissions, but producing it in a distributed, carbon-neutral, low-cost manner requires new technologies. Herein we demonstrate the complete conversion of glucose and xylose from plant biomass to H 2 and CO 2 based on an in vitro synthetic enzymatic pathway. Glucose and xylose were simultaneously converted to H 2 with a yield of two H 2 per carbon, the maximum possible yield. Parameters of a nonlinear kinetic model were fitted with experimental data using a genetic algorithm, and a global sensitivity analysis was used to identify the enzymes that have the greatest impact on reaction rate and yield. After optimizing enzyme loadings using this model, volumetric H 2 productivity was increased 3-fold to 32 mmol H 2 ∙L ₋1 ∙h ₋1 . The productivity was further enhanced to 54 mmol H 2 ∙L ₋1 ∙h ₋1 by increasing reaction temperature, substrate, and enzyme concentrations—an increase of 67-fold compared with the initial studies using this method. The production of hydrogen from locally produced biomass is a promising means to achieve global green energy production.

08 HYDROGEN↗

DOE OSTI2022

Accelerating the discovery of novel magnetic materials using machine learning–guided adaptive feedback

Magnetic materials are essential for energy generation and information devices, and they play an important role in advanced technologies and green energy economies. Currently, the most widely used magnets contain rare earth (RE) elements. An outstanding challenge of notable scientific interest is the discovery and synthesis of novel magnetic materials without RE elements that meet the performance and cost goals for advanced electromagnetic devices. Here, we report our discovery and synthesis of an RE-free magnetic compound, Fe 3 CoB 2 , through an efficient feedback framework by integrating machine learning (ML), an adaptive genetic algorithm, first-principles calculations, and experimental synthesis. Magnetic measurements show that Fe 3 CoB 2 exhibits a high magnetic anisotropy ( K 1 = 1.2 MJ/m 3 ) and saturation magnetic polarization ( J s = 1.39 T), which is suitable for RE-free permanent-magnet applications. Our ML-guided approach presents a promising paradigm for efficient materials design and discovery and can also be applied to the search for other functional materials.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Technoeconomic Design Optimization for Fast Reactors. Part I: Workflow Development and Case Study for Small LFR District Energy Application

The nuclear industry is developing small reactor designs that can target a variety of deployment locations and energy products. Smaller nuclear designs have traditionally struggled to handle the steep trade-offs between size and cost that have historically incentivized large reactors. This motivates computational optimization of small reactors to minimize costs and quantify the trade-off between size and cost. In this paper, the cost/size trade-off for a small fast reactor is derived using a multi-objective genetic algorithm optimization, with steady-state, transient, and cost analysis of the fast reactor being performed. Specifically, the method is demonstrated on a small 10- to 120-MW(thermal) U-Pu-Zr–fueled lead-cooled fast reactor with a 10-year core life for district energy applications, which can have a thermal load compatible with this range. The results reinforced that fast reactor cores at the lower end of this power range suffer cost penalties due to critical mass considerations. It was found that high power density cores with strong reactivity swings and many control rods were favored over designing to minimize reactivity swing. Furthermore, this contrasts with some traditional configurations designed using engineering judgment and demonstrates that optimizers can find nontraditional but realistic solutions, along with demonstrating the value of incorporating cost functions into whole-reactor design optimization.

Fast reactor↗

DOE OSTI2015

A COUPLED 2 × 2D BABCOCK–LEIGHTON SOLAR DYNAMO MODEL. I. SURFACE MAGNETIC FLUX EVOLUTION

The need for reliable predictions of the solar activity cycle motivates the development of dynamo models incorporating a representation of surface processes sufficiently detailed to allow assimilation of magnetographic data. In this series of papers we present one such dynamo model, and document its behavior and properties. This first paper focuses on one of the model’s key components, namely surface magnetic flux evolution. Using a genetic algorithm, we obtain best-fit parameters of the transport model by least-squares minimization of the differences between the associated synthetic synoptic magnetogram and real magnetographic data for activity cycle 21. Our fitting procedure also returns Monte Carlo-like error estimates. We show that the range of acceptable surface meridional flow profiles is in good agreement with Doppler measurements, even though the latter are not used in the fitting process. Using a synthetic database of bipolar magnetic region (BMR) emergences reproducing the statistical properties of observed emergences, we also ascertain the sensitivity of global cycle properties, such as the strength of the dipole moment and timing of polarity reversal, to distinct realizations of BMR emergence, and on this basis argue that this stochasticity represents a primary source of uncertainty for predicting solar cycle characteristics.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

New stable Re-B phases for ultra-hard materials

As a distinct class of ultra-hard materials, transition metal borides are found to have superior mechanical properties that challenge the traditional materials. In this work, we explored new stable structures for rhenium borides with different stoichiometries using genetic algorithm in combination with first-principles calculations. Based on theoretical calculations, ReB in a P-3m1 structure is found to be stable against decomposition reactions below 10 GPa and ReB3 in a P-6m2 structure is stable above 22 GPa. Two new phases of Re(2)B are predicted to be thermodynamically stable at pressures higher than 55 GPa and 80 GPa respectively. We also show that a C2/m structure discovered for ReB(4) has energy lower than that of the R-3m structure reported earlier (Wang et al 2013 J. Alloys Compd. 573 20). Elastic and vibrational properties from first-principles calculations indicate that the low-energy structures obtained in our search are mechanically and dynamically stable and are promising targets as new ultra-hard materials.

36 MATERIALS SCIENCE↗

DOE OSTI2018

New structures of Fe3S for rare-earth-free permanent magnets

We applied adaptive genetic algorithm (AGA) to search for low-energy crystal structures of Fe 3 S. A number of structures with energies lower than that of the experimentally reported Pnma and I-4 structures have been obtained from our AGA searches. These low-energy structures can be classified as layer-motif and column-motif structures. In the column-motif structures, Fe atoms self-assemble into rods with bcc type of underlying lattice, which are separated by the holes terminated by S atoms. In the layer-motif structures, the bulk Fe is broken into slabs of several layers passivated by S atoms. Magnetic properties calculations showed that the column-motif structures exhibit reasonably high uniaxial magnetic anisotropy. In addition, we examined the effect of Co doping to Fe 3 S and found magnetic anisotropy can be enhanced through Co doping.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Generation and optimization of cross-sections for electron-C 4 F 7 N collisions

Abstract A complete and consistent set of electron-neutral collision cross-sections for the novel insulating gas C 4 F 7 N is reported. The set is composed of a combination of cross-sections previously reported in literature, optimized via a genetic algorithm in conjunction with a multi-term Boltzmann equation solver, and calculatedab initiousing the R-matrix code Quantemol-EC. The finalized set accurately reproduces reported macroscopic rate and transport coefficients as well as Townsend coefficients and critical electric field strengths in C 4 F 7 N and its mixtures with nitrogen, carbon dioxide, and argon.

Physics↗