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At least 271 records · Page 15

A semiempirical transparency model for dual energy cargo radiography applications

Cargo containers passing through ports are scanned by non-intrusive inspection systems to search for concealed illicit materials. By using two photon beams with different energy spectra, dual energy inspection systems are sensitive to both the area density and the atomic number of cargo contents. Most literature on the subject assumes a simple exponential attenuation model for photon intensity in which only free streaming photons are detected. However, this approximation neglects second order effects such as scattering, leading to a biased model and thus incorrect material predictions. This work studies the accuracy of the free streaming model by comparing it to simulation outputs, finding that the model shows poor atomic number reconstruction accuracy at high- Z and suffers significantly if the source energy spectra and detector response function are not known exactly. To address these challenges, this work introduces a semiempirical transparency model which modifies the free streaming model by rescaling different components of the mass attenuation coefficient, allowing the model to capture secondary effects ignored by the free streaming model. The semiempirical model displays improvement agreement with simulated results at high- Z and shows excellent extrapolation to materials and thicknesses which were not included during the calibration step. Furthermore, this work demonstrates that the semiempirical model yields accurate atomic number predictions even when the source spectra and detector response are not known exactly. In conclusion, using the semiempirical model, manufacturers can perform a simple calibration to enable more precise Z reconstruction capabilities, which has the potential to significantly improve the performance of existing dual energy radiographic systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Validation of Computational Fluid Dynamics Simulations for Biological Performance Assessment in Hydropower units (Final Report)

The biological performance assessment (BioPA) toolset developed by Pacific Northwest National Laboratory (PNNL) estimates the relative biological performance of fish passage at a hydroelectric power turbine unit. The tool is based on the use of computational fluid dynamics (CFD) and fish biological response relationships. The recent release, BioPA-v3, is based on directly computed trajectory and collision of material Lagrangian particles using CFD simulation codes rather than the prior version that relies on Tecplot to compute streamtrace trajectories. Before modifying the toolset, a series of validation tests were performed at the various steps of modification in the toolset. Validation is a critical step of any numerical investigation that reflects the accuracy and reliability of the predicted results. It raises the confidence level of the user to use the modified version of the BioPA toolset. Several test cases were simulated and compared, where available, to observed data. The trajectory and collision of the small spherical and cylindrical particles in a water flume were compared to in-house experiments. The CFD predicted collision rate and flow field compared well with experimental observation for vane array and large cylinder as target bodies. Next, the CFD-predicted flow field and hydraulic performance of a laboratory-scale model of a Francis turbine was also successfully validated. Note that the trajectory of the particles is significantly affected by the flow field in such extreme conditions. In addition to the particle trajectories and flow field, the collision detection method employed in the CFD simulations was also successfully validated. The CFD predicted impact velocity, collision time, velocity, and trajectory of a sphere excellently matched with analytical value for a bouncing ball in the elastic collision. A similar approach was also tested and successfully validated for a collision of sphere with a 45° inclined plane. After successfully validating different cases, the BioPA toolset was modified to use direct output of the CFD prediction and the new version can be used in evaluating biological performance at hydroelectric turbines.

13 HYDRO ENERGY↗

Challenges in Qualification of Thermal Protection Systems in Extreme Entry Environments

Planetary entry vehicles employ ablative TPS materials to shield the aeroshell from entry aeroheating environments. To ensure mission success, it must be demonstrated that the heat shield system, including local features such as seams, does not fail at conditions that are suitably margined beyond those expected in flight. Furthermore, its thermal response must be predictable, with acceptable fidelity, by computational tools used in heat shield design. Mission assurance is accomplished through a combination of ground testing and material response modelling. A material's robustness to failure is verified through arcjet testing while its thermal response is predicted by analytical tools that are verified against experimental data. Due to limitations in flight-like ground testing capability and lack of validated high-fidelity computational models, qualification of heat shield materials is often achieved by piecing together evidence from multiple ground tests and analytical simulations, none of which fully bound the flight conditions and vehicle configuration. Extreme heating environments (>2000 W/sq. cm heat flux and >2 atm pressure), experienced during entries at Venus, Saturn and Ice Giants, further stretch the current testing and modelling capabilities for applicable TPS materials. Fully-dense Carbon Phenolic was the material of choice for these applications; however, since heritage raw materials are no longer available, future uses of re-created Carbon Phenolic will require re-qualification. To address this sustainability challenge, NASA is developing a new dual-layer material based on 3D weaving technology called Heat shield for Extreme Entry Environments (HEEET). Regardless of TPS material, extreme environments pose additional certification challenges beyond what has been typical in recent NASA missions. Scope of this presentation: This presentation will give an overview of challenges faced in verifying TPS performance at extreme heating conditions. Examples include: (1) Bounding aeroheating parameters (heat flux, pressure, shear and enthalpy) in ground facilities. How to certify TPS if environments can't be bounded or aeroheating parameters can't be simultaneously achieved. (2) Higher uncertainties in ground test environments (facility calibration and analytical predictions) at extreme conditions. (3) Testing in flows similar to planetary atmosphere composition (H2/He for Gas and Ice Giants). (4) Test sample size limitations for qualifying seam designs. (5) Lack of computational tools capable of simulating all significant aspects of TPS performance (including initiation and propagation of failures). This presentation will provide recommendations on how the EDL community can address these challenges and mitigate some of the risks involved in flying TPS materials at extreme conditions. Examples include: (1) Dedicated activity to understanding TPS failure modes. Develop computational tools capable of modelling fluid interaction with material's thermostructural response. Validate these tools through failure testing. A better understanding of failure mechanisms may eliminate the need to fully bound all aeroheating parameters in ground testing. (2) Enhancements to current testing facilities to simulate flight-like ablation mechanism (ex. testing in Nitrogen at Ames Interaction Heating Facility to limit oxidation in favor of more sublimation). (3) Improved characterization of test conditions with new diagnostic methods and determination of environment uncertainty through rigorous statistical analysis of available data. (4) Design margin policies that are directly tied to uncertainties in ground test environments and modelling fidelity

Mahzari, Milad↗

Three-Dimensional Heat Flux and Thermal Analysis of Angled Tungsten Samples on DIII-D

ITER-grade tungsten and dispersoid-strengthened tungsten samples with the top surface angled at ~15° towards the incident plasma flux were exposed to 9 H-mode discharges with edge-localized modes (ELMs) in the lower divertor of DIII-D tokamak using the Divertor Material Evaluation System (DiMES). Surface damage included cracking and flaking of material on the two samples farthest away from the plasma strike point, and significant melting of the two samples closest to the strike point. Heat flux and thermal analysis tools new to DIII-D have been applied to better understand this material response and to help optimize the exposure conditions for future experiments. SMITER field-line tracing simulations based on IRTV data and EFIT equilibria estimate an average inter-ELM perpendicular heat flux, 𝑞⊥,𝑖nter−𝐸LM , on the angled surfaces of 10.1 – 19.6 MW/m² for a majority of the 9 discharges, increasing to 15.6 – 24.5 MW/m² for the single, higher-power shot where samples melted. Fast camera data showed shallow intra-ELM melting and re-solidification, which transitioned to bulk inter-ELM melting with melt motion in the 𝐽⃗ 𝑥 𝐵⃗ direction. About 50% of the protruding volume of the most affected sample was displaced via melt-motion. SIERRA thermal modeling software was able to reproduce an onset time of melting consistent with fast camera data and final sample conditions, within < 200 ms. Maximum surface temperatures of 3122 K and 2787 K are estimated for the samples farthest away from the strike point, while the closest samples achieve melting at 4067 ms and 4750 ms into the ~5000 ms plasma exposure. A +10% increase in both the SMITER 𝑞⊥,𝑖nter−𝐸LM calculations and the estimated ELM heat loads 𝑞⊥, 𝐸LM was required to achieve this result, which is within the uncertainty of the diagnostic data but likely accounts for non-ideal geometry effects plus other physics uncertainties not included in this first iteration of modeling. This work provided valuable estimates of the 3D temperature evolution to help better understand the observed surface morphology and internal recrystallization of samples, which are discussed in detail in a complementary manuscript [1]. Benchmarking efforts with more diagnosed DIII-D experiments are underway to further refine the SMITER and SIERRA models for DiMES. Future use of these tools will enable researchers to precisely target heat flux exposure conditions in DIII-D to test, but not exceed, the thermomechanical limitations of novel plasma-facing materials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optimization Simulations for a Gamma-Ray Calibration Standard for a Cyclic Neutron Activation Analysis Pneumatic System at the Penn State Breazeale Reactor

For new experimental setups, the initial testing and calibrations can be expensive and time consuming without prior optimization. However, these issues can be mitigated using realistic modeling and simulation studies of the proposed system a priori. Specifically, an experiment can be performed virtually using realistic simulations and the expected results evaluated to inform adjustments of the experimental setup to achieve optimum results. At the Penn State Breazeale Reactor, a new pneumatic transfer system has been developed for the detection and characterization of short-lived fission fragments to enhance and complement existing nuclear data. The system accomplishes this task by transporting samples cyclically between an assortment of gamma-ray/neutron detectors and the reactor-core vicinity with sub-second transit times. The measured neutron flux paired with simulations of detector response using Geant4 and a custom module for estimating cascade summing effects and corrections were used to select sample-material masses for system characterization. With the optimized sample masses, an experimental counting plan for characterizing the repeatability of the newly developed pneumatic system was developed. Finally, the predictions made with these simulations allowed for optimization of the irradiation sample characteristics and gamma-ray detection system.

cyclic neutron activation, gamma-ray spectroscopy↗

Application of a Developmental Composite Material Model to Predict the Crush Response of Two Energy Absorbers

In 2012, a consortium was formed with the goal of creating a new composite material model capable of predicting the wide range of properties, accumulated damage behavior, and the many different types of failure in composites under impact loading. The material model was developed for execution in the commercially available nonlinear, explicit transient dynamic finite element code, LS-DYNA®. This material model incorporates three sub-models: deformation, damage, and failure. In addition, the model accounts for strain rate and temperature effects and relies heavily on the input of tabulated material response data. The model is designated *MAT_COMPOSITE_TABULATED_PLASTICITY_DAMAGE, or *MAT_213. Initially, *MAT_213 was developed for use with solid elements only; however, a thin shell element formulation for *MAT_213 has been adapted recently. The objective of this project was to find a suitable modeling example to investigate the capabilities and performance of *MAT_213. In 2012, two composite energy absorbers were designed and evaluated at NASA Langley Research Center through multi-level testing and simulation. The first was a conical-shaped energy absorber, designated the conusoid, which consisted of four layers of hybrid carbon-Kevlar® plain-weave fabric oriented at [+45°/-45°/-45°/+45°] with respect to the vertical direction. The second was a sinusoidal-shaped energy absorber, designated the sinusoid, which consisted of hybrid carbon-Kevlar® plain-weave fabric face sheets, two layers for each face sheet oriented at ±45° with respect to the vertical direction, and a closed-cell ELFOAM® P200 polyisocyanurate foam core. Finite element models were developed of the energy absorbers and simulations were performed using LS-DYNA®. In this paper, the development of a *MAT_213 model of a hybrid carbon-Kevlar® plain-weave fabric is presented. Next, comparisons with material characterization tests are presented. Then, test-analysis results are documented for each energy absorber as comparisons of time-history responses, as well as predicted and experimental structural deformations and progressive damage under impact loading using the *MAT_213 material model. Since a prior *MAT_58, or *MAT_LAMINATED_COMPOSITE_FABRIC material model was used in previous simulations of the energy absorbers, comparisons are made between *MAT_58 and *MAT_213 model predictions with test data. Finally, the paper includes a comprehensive list of “lessons learned,” in which a series of parametric studies are documented that were performed to investigate specific issues related to the material model. These “lessons learned” are included in hopes that they may help future *MAT_213 users.

crashworthiness, LS-DYNA transient dynamic simulat↗

Performance Dependences of Multiplication Layer Thickness for InP/InGaAs Avalanche Photodiodes Based on Time Domain Modeling

InP/InGaAs avalanche photodiodes (APDs) are being widely utilized in optical receivers for modern long haul and high bit-rate optical fiber communication systems. The separate absorption, grading, charge, and multiplication (SAGCM) structure is an important design consideration for APDs with high performance characteristics. Time domain modeling techniques have been previously developed to provide better understanding and optimize design issues by saving time and cost for the APD research and development. In this work, performance dependences on multiplication layer thickness have been investigated by time domain modeling. These performance characteristics include breakdown field and breakdown voltage, multiplication gain, excess noise factor, frequency response and bandwidth etc. The simulations are performed versus various multiplication layer thicknesses with certain fixed values for the areal charge sheet density whereas the values for the other structure and material parameters are kept unchanged. The frequency response is obtained from the impulse response by fast Fourier transformation. The modeling results are presented and discussed, and design considerations, especially for high speed operation at 10 Gbit/s, are further analyzed.

Xiao, Yegao↗

Hydrodynamic Simulations of Oxygen–Neon Classical Novae as Galactic 7 Li Producers and Potential Accretion-induced Collapse Progenitors*

Abstract We report on studies of classical nova (CN) explosions where we follow the evolution of thermonuclear runaways (TNRs) on oxygen–neon (ONe) white dwarfs (WDs). Using NOVA, a 1D hydrodynamic computer code, we accrete solar matter until the TNR is ongoing and then switch to a mixed composition. This approach is guided by the results of multidimensional studies of TNRs in WDs, which find that sufficient mixing with WD core material occurs after the TNR is well underway, and levels of enrichment of the CNONeMg elements are reached that agree with observations of CN ejecta abundances. Because the amount of accreted material is inversely proportional to the oxygen abundance, by first accreting solar matter, the amount of accreted material is larger than in those simulations with an initially enriched composition. We vary the mass of the WD (from 0.6 M ⊙ to 1.35 M ⊙ ) and the composition of the mixed materials. Our results show large enrichments of 7 Be in the ejected gases, implying that ONe CNe and CO CNe may be responsible for a significant fraction (∼100 M ⊙ ) of the Galactic 7 Li (∼1000 M ⊙ ). The production of 22 Na and 26 Al in CN explosions and the γ -ray emission predicted by our simulations are discussed. The WDs in all our simulations eject less material than they accrete and we predict that the WD is growing in mass as a consequence of the CN outburst. ONe CNe, therefore, may be an important channel for accretion-induced collapse events.

Starrfield, Sumner (ORCID:0000000213596312)↗

FEA-aided investigation of the effective thermal conductivity in a medium with embedded spheres

For multiple applications in nuclear energy, the ability to accurately represent material behavior with a simplified model is important to facilitate practical engineering-scale simulations. Here, we focus on the homogenized thermal response of a medium containing spherical inclusions, similar to a fuel form (compact or pebble) containing (TRISO) particles. A review on effective thermal conductivity (ETC) modeling is performed considering a random distribution of mono-sized spherical inclusions in a continuous matrix, with a primary focus on the analytical models. Finite element simulations are performed to evaluate each analytical model in varying material conditions. The model predictions are compared with the expected results obtained from the finite element predictions in addition to the Wiener and Hashin-Shtrikman bounds. Lastly, we included a practical discussion on the homogenization applied to a TRISO fuel pebble.

42 ENGINEERING↗

Thermal-Mechanical Elastic-Plastic and Ductile Failure Model Calibrations for 304L Stainless Steel Alloy

Numerical simulations of metallic structures undergoing rapid loading into the plastic range require material models that accurately represent the response. In general, the material response can be seen as having four interrelated parts: the baseline response under slow loading, the effect of strain rate, the conversion of plastic work into heat and the effect of temperature. In essence, the material behaves in a thermal-mechanical manner if the loading is fast enough so when heat is generated by plastic deformation it raises the temperature and therefore influences the mechanical response. In these cases, appropriate models that can capture the aspects listed above are necessary. The material of interest here is 304L stainless steel, and the objective of this work is to calibrate thermal-mechanical models: one for the constitutive behavior and another for failure. The work was accomplished by first designing and conducting a material test program to provide data for the calibration of the models. The test program included uniaxial tension tests conducted at room temperature, 150 and 300 C and at strain rates between 10 –4 and 10 3 1/s. It also included notched tension and shear-dominated compression hat tests specifically designed to calibrate the failure model. All test specimens were extracted from a single piece of plate to maintain consistency. The constitutive model adopted was a modular $J_2$ plasticity model with isotropic hardening that included rate and temperature dependence. A criterion for failure initiation based on a critical value of equivalent plastic strain fitted the failure data appropriately and was adopted. Possible ranges of the values of the parameters of the models were determined partially on historical data from calibrations of the same alloy from other lots and are given here. The calibration of the parameters of the models were based on finite element simulations of the various material tests using relatively ne meshes and hexahedral elements. When using the model in structural finite element calculations, however, element formulations and sizes different from those in the calibration are likely to be used. A brief investigation demonstrated that the failure initiation predictions can be particularly sensitive to the element selection and provided an initial guide to compensate for the effect of element size in a specific example.

36 MATERIALS SCIENCE↗

Complex Oxides under Simulated Electric Field: Determinants of Defect Polarization in AB O 3 Perovskites

Abstract Polarization of ionic and electronic defects in response to high electric fields plays an essential role in determining properties of materials in applications such as memristive devices. However, isolating the polarization response of individual defects has been challenging for both models and measurements. Here the authors quantify the nonlinear dielectric response of neutral oxygen vacancies, comprised of strongly localized electrons at an oxygen vacancy site, in perovskite oxides of the form AB O 3 . Their approach implements a computationally efficient local Hubbard U correction in density functional theory simulations. These calculations indicate that the electric dipole moment of this defect is correlated positively with the lattice volume, which they varied by elastic strain and by A‐site cation species. In addition, the dipole of the neutral oxygen vacancy under electric field increases with increasing reducibility of the B‐site cation. The predicted relationship among point defect polarization, mechanical strain, and transition metal chemistry provides insights for the properties of memristive materials and devices under high electric fields.

36 MATERIALS SCIENCE↗

Evolution of anisotropy with saturation and its implications for the elastoplastic responses of clay rocks

Many clay rocks have distinct bedding planes. Experimental studies have shown that their mechanical properties evolve with the degree of saturation (DOS), often with higher stiffness and strength after drying. For transversely isotropic rocks, the effects of saturation can differ between the bed-normal (BN) and bed-parallel (BP) directions, which gives rise to saturation-dependent stiffness and strength anisotropy. Accurate prediction of the mechanical behavior of clay rocks under partially saturated conditions requires numerical models that can capture the evolving elastic and plastic anisotropy with DOS. In this study, we present an anisotropy framework for coupled solid deformation-fluid flow in unsaturated elastoplastic media. Here we incorporate saturation-dependent strength anisotropy into an anisotropic modified Cam-Clay (MCC) model and consider the evolving anisotropy in both the elastic and plastic responses. The model was calibrated using experimental data from triaxial tests to demonstrate its capability in capturing strength anisotropy at various levels of saturation. Through numerical simulations, we demonstrate the role of evolving stiffness and strength anisotropy in the mechanical behavior of clay rocks. Plane strain simulations of triaxial compression tests were also conducted to demonstrate the impacts of material anisotropy and DOS on the mechanical and fluid flow responses.

36 MATERIALS SCIENCE↗

Improving Additive Manufactured Component Performance through Multi-Scale Microstructure Simulation and Process Optimization

The purpose of this project was to utilize computational tools to understand the relationships between processing, microstructure, and properties for additively manufactured (AM) aluminum alloys for automotive applications, and to provide an engineering solution for helping to optimize process conditions. The project leverages ORNL developments in computational modeling, including AM process modeling, phase-field based microstructure evolution predictions, and data analytics techniques for mapping process conditions to material outcomes. The project utilized an Al-Cu-Mn-Zr alloy as a model material for studying formation of defects and microstructural features in response to variations in process conditions. Based on both pre-existing experimental data and simulation results, statistical process maps were constructed to identify regions of process space with minimal defect formation and advantageous microstructures and properties. The software tools used for this purpose were successful disseminated to GM, who were able to successful compile the relevant HPC codes within their own computing ecosystem and perform initial calculations to reproduce ORNL results.

36 MATERIALS SCIENCE↗

Sensitivity Study of Multiscale and Phenomenological Elasto-Viscoplastic Grade 91 Material Models for Component-Scale Response

Many advanced nuclear reactor concepts currently being developed are targeting higher operating temperatures relative to the current fleet of light water nuclear reactors, for efficiency gains and other operational considerations. The design of high temperature structural components with reliable long-term operational performance will depend on material models that accurately capture the inelastic deformation mechanisms active in these environments. In this work, we perform a detailed parameter sensitivity analysis of two unified elasto-viscoplastic Grade 91 material models capable of capturing long term high temperature creep deformation. The first model is a phenomelogical material model from the Nuclear Engineering Material Library (NEML) developed at Argonne National Lab. The NEML model parameters and their uncertainty were fit to a range of Grade 91 experimental data using Bayesian Markov Chain Monte Carlo analysis. The second model is a LAROMance data-driven surrogate material model developed at Los Alamos National Lab. The LAROMance model is fit to a large database of responses produced by a mechanistic crystal plasticity based polycrystal model. Parameters for the LAROMance surrogate material model reflect the pedigree of the Grade 91 microstructure. Both material models have been integrated into the Grizzly code, based on the open-source MOOSE multiphysics simulation framework, to simulate both the progression of aging mechanisms and the effects of that aging on nuclear power plant structures. Grizzly is used analyze a three-dimensional Grade 91 piping system to compare the long-term inelastic response predicted by these two fundamentally different models and assess the sensitivity of the material model input parameters on this quantity of interest.

42 ENGINEERING↗

Hardening in Au-Ag nanoboxes from stacking fault-dislocation interactions

Porous, nano-architected metals with dimensions down to ~10 nm are predicted to have extraordinarily high strength and stiffness per weight, but have been challenging to fabricate and test experimentally. Here, we use colloidal synthesis to make ~140 nm length and ~15 nm wall thickness hollow Au-Ag nanoboxes with smooth and rough surfaces. In situ scanning electron microscope and transmission electron microscope testing of the smooth and rough nanoboxes show them to yield at 130 ± 45 MPa and 96 ± 31 MPa respectively, with significant strain hardening. A higher strain hardening rate is seen in rough nanoboxes than smooth nanoboxes. Finite element modeling is used to show that the structure of the nanoboxes is not responsible for the hardening behavior suggesting that material mechanisms are the source of observed hardening. Molecular dynamics simulations indicate that hardening is a result of interactions between dislocations and the associated increase in dislocation density.

42 ENGINEERING↗

Testing of an Optical Fiber--Based Gamma Thermometer in the High Flux Isotope Reactor Gamma Irradiation Facility

This report describes the design, thermal modeling, and gamma irradiation testing of an optical fiber–based gamma thermometer (OFBGT), which was irradiated in the High Flux Isotope Reactor (HFIR) Gamma Irradiation Facility (GIF). OFBGTs are a promising technology for application in nuclear reactors because they can provide a distributed measurement of gamma ray heating rate, unlike thermocouple-based gamma thermometers, which are fixed in-core sensors that can be used in boiling water reactors to calibrate local power range monitors. OFBGTs measure gamma ray heating rate by measuring the temperature difference between a pair of optical fibers; one fiber is in thermal contact with a heat sink (usually the reactor coolant), and the other is in thermal contact with a thermally isolated mass. The device can be calibrated with a heating wire within the thermal mass. The OFBGT that was designed and fabricated at Oak Ridge National Laboratory can measure distributed gamma ray heating rate over an effective measurement length of 61 cm, and the outer diameter of the sensor is 12.7 mm, giving the prototypical sensor design a relatively small footprint. The sensor housing is backfilled with Ar to ensure a well-predicted thermal response that is not affected by humidity or chemical interactions during operation. For calibration, the sensor design uses a Ni–Cr wire, which can be supplied with currents from 0 to 1 A to capture the wide range of potential gamma ray heating rates expected in HFIR’s spent fuel elements. The OFBGT was thermally modeled analytically and numerically; both models account for temperature-dependent thermal conductivities of the materials and show good agreement. The thermal response of the sensor inside spent HFIR fuel elements was simulated for times up to 1 year after discharge of the fuel element. Out-of-pile open-air tests indicated that the steady-state response of the sensor matches modeled results within experimental uncertainty. Calibration tests were performed using electrical heating in the HFIR spent fuel pool, above the fuel elements, to establish a relationship between the difference in spectral shift measured by optical fibers located inside and outside the OFBGT and the applied electrical heating. Subsequently, the OFBGT was placed within the the spent fuel element from HFIR cycle 501 to measure the spatial profile of the gamma heating rates. Results showed good agreement between the theoretical and measured gamma dose rate profiles, with maximum deviations of ~10% or less.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Applications of Nickelate perovskites for neuromorphic computing from electronic structure and Machine Learning

While the limit of Moore's law is presently being reached with current microelectronic technologies, we need to develop new paradigms that overcome this limitation. In that respect, neuromorphic computing is a concept that emulates the neural behavior and response of the human brain, and it has been recognized as a promising alternative approach. In this research project, we will perform multi-fidelity scale bridging to explore the potential use of materials with metal to insulator transition for neuromorphic applications. In particular, rare earth nickelates are promising for such purposes, as the transition in these materials is quite sensitive to a broad set of different external stimuli. Our multi-fidelity approach will bridge the high-fidelity electronic structure calculations with classical potentials. We will bridge dynamical mean field theory with a classical atomistic representation via a deep learning force field. The neural network is trained with energies, charges, and forces obtained by accurate electronic structure theories based on Dynamical Mean Field Theory. The configurational space is generated from known crystal phases, ab initio molecular dynamics with exchange-correlation functionals corrected with the Hubbard model, disordered phases with different concentrations of oxygen vacancies, and nonsymmetrical positions and induced strain by grain interfaces or contact with a substrate. Strategies to train the model with a reduced number of training examples are obtained from active learning methods, and new structures for improving the learning process are generated by using machine learning autoencoders. This classical potential will be validated through a diversity of electronic structure methods and represents an important step to combine the flexibility and accuracy of first-principles with the speed of classical potentials. The generated multi-fidelity surrogate model will be used to understand the role of strain, oxygen vacancies, proton doping, the variation of the crystal phase, substrate effects, vibrational effects as the octahedral rotation, grain boundaries and defect effects on the response of a Metal to Insulator Transition (MIT) in correlated materials. Long time and large-scale simulations will help understand the role of different stimuli to control the hysteresis of the MIT, as it has been experimentally suggested. Selected configurations will be analyzed with higher-level theories to provide an accurate electronic description and to study how the orbitals and charges are rearranged under different conditions.

36 MATERIALS SCIENCE↗

Photovoltaic characteristics of diffused P/+N bulk GaAs solar cells

The photovoltaic characteristics of P(+)N junction solar cells fabricated on bulk GaAs by an open tube diffusion technique are described in this paper.Spectral response measurements were analyzed in detail and compared to a computer simulation in order to determine important material parameters. It is projected that proper optimization of the cell parameters can increase the efficiency of the cells from 12.2 percent to close to 20 percent.

Borrego, J. M.↗