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DOE OSTI2024

Underlying mechanism of structural transformation between GaSb and GaAs response to intense electronic excitation

Ion irradiation of semiconductors has emerged as a promising approach for fabricating self-organized nanosystems with high atomic precision, despite often being accompanied by undesirable phenomena. Exploring the mechanisms underlying structural transformations is crucial for assessing nanostructure array types under complex irradiation environments. By quantitatively calculating the thermodynamically driven processes and analyzing the impact of intrinsic structural parameters, distinct structural transformations in response to intense electronic excitation are systematically investigated in gallium antimonide (GaSb) and gallium arsenide (GaAs) systems. In high-energy regimes, the nanofibers layer of GaSb exhibits intriguing structural discrepancy, characterized by partial nanofibers with coherent boundaries, interspersed nanopores accompanied by antisite defects and Ga precipitates, distinguishing to a series of discontinuous latent tracks that emerged within cylindrical trajectories in GaAs. Furthermore, significant diffusion behaviors of the nanohillocks are discovered in GaAs, with higher average roughness than GaSb, driven by the gradient stress distribution influenced by the free-surface effects. The deposition energy for melting phase formation, Gibbs free energy, and Ga diffusion coefficients contribute to the distinctive structural features, evidencing relatively stable morphological configurations and higher irradiation resistance in GaAs. Consequently, special optoelectronic properties associated with structural discrepancies facilitate the design and optimization of material functionalities by irradiation technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2022

A High-Accuracy Power Loss Model of SiC MOSFETs in Current Source Inverter Considering Current Commutation and Parasitic Parameters

Power loss estimation of power electronic devices is important to the efficiency optimization of motor drives used in many applications. However, most existing simplified power loss models of silicon carbide (SiC) MOSFETs are not sufficiently accurate due to their neglect of parasitic parameters in the current commutation loop. In addition, the loss model of the voltage source inverter (VSI) cannot be directly applied to the current source inverter (CSI) because of differences between their commutation loops. First, the commutation processes for VSIs and CSIs are compared. The voltage and current trajectories of SiC MOSFETs in the switching transition of a CSI-based motor drive system are analyzed in detail. Based on these results, the conduction and switching losses of SiC MOSFETs in CSIs are modeled considering the current commutation details. In addition, the proposed analytical model includes parasitic inductances and capacitances in the current commutation loop. Experimental results have verified that the proposed power loss model delivers higher accuracy loss predictions than the conventional loss model.

current commutation, current source inverter, powe↗

DOE OSTI2018

Advanced Control Architecture and Sensor Information Development for Process Automation, Optimization, and Imaging of Chemical Looping Systems

The Syngas Chemical Looping (SCL) process developed at The Ohio State University (OSU) uses an iron-based oxygen carrier to convert syngas into high-purity hydrogen while simultaneously capturing carbon dioxide that is readily sequestrable. A 25 kWth sub-pilot unit was successfully demonstrated multiple times on the OSU Clean Coal Research Facility, and a 250 kWth – 3 MWth pilot demonstration unit has been designed and constructed at the National Carbon Capture Center (NCCC) in Wilsonville, Alabama. The focus of this project is to develop multiple technologies to automate the startup and shutdown of chemical looping system. Success of this project will propel the advanced carbon capture method toward commercialization, hence be disruptive to the fossil fuel and power industries. Advanced process automation control architecture and imaging and optimization sensor software were developed for OSU chemical looping process. A high-level controller (HLC) consisting of decision-making and controller-selection logic integrated with sliding mode controllers (SMCs) were developed to perform chemical looping process startup and shutdown. Babcock & Wilcox Power Generation Group’s FocalPoint Optimization System was implemented to optimize the process operating conditions. The process automation controller and optimization information were realized and tested on OSU’s existing sub-pilot chemical looping test unit under atmospheric condition. The implemented control architecture was able to perform the complete process procedure from startup, steady-state reaction operation to shutdown with minimal operator intervention. The controller was also implemented on the pressurized syngas chemical looping (SCL) pilot test unit constructed at the National Carbon Capture Center (NCCC), demonstrating its pressure control capability with a designed transient state trajectory. An electrical capacitance volume tomography (ECVT) sensor device and its software were developed to image the packed moving bed and slugging fluidized bed of oxygen carriers in chemical looping systems at elevated temperatures. The ECVT device constructed was capable of tracking the subtle voidage variance along the moving bed axis as a feature for directly measuring the oxygen carrier particles’ linear velocity. Also, the high temperature ECVT device was used to study the fluidization characteristics of Geldart Group D particles.

08 HYDROGEN↗

DOE OSTI2022

Dynamic Learning of Correlation Potentials for a Time-Dependent Kohn-Sham System

We develop methods to learn the correlation potential for a time-dependent Kohn-Sham (TDKS) system in one spatial dimension. We start from a low-dimensional two-electron system for which we can numerically solve the time-dependent Schr¨odinger equation; this yields electron densities suitable for training models of the correlation potential. We frame the learning problem as one of optimizing a least-squares objective subject to the constraint that the dynamics obey the TDKS equation. Applying adjoints, we develop efficient methods to compute gradients and thereby learn models of the correlation potential. Our results show that it is possible to learn values of the correlation potential such that the resulting electron densities match ground truth densities. We also show how to learn correlation potential functionals with memory, demonstrating one such model that yields reasonable results for trajectories outside the training set.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Fluid Flow, Dissolution, and Mixing Phenomena in Argon-Stirred Steel Ladles

In the current study, the multiphase fluid flow in argon-stirred steel ladles is simulated using an Eulerian–Lagrangian two-phase approach. The momentum source and the turbulent kinetic energy source due to the motion of the bubble are considered for the liquid phase. Argon bubbles are treated as discrete phase particles, and the interfacial forces between the bubbles and the liquid phase; the dependence of the gas density and the bubble diameter on the temperature and the static pressure; and the bubble size distribution are considered. When the fluid flow reaches the quasi-steady state, the ferroalloy melting and mixing phenomena is also modeled. The melting time and the trajectory length of each ferroalloy particle are recorded using a user-defined function (UDF). Local mixing time is predicted in the entire computational domain by checking the mixing criteria in every cell. The effects of gas flow rate, porous plug location, and separation angle of two porous plugs on the fluid flow and the mixing phenomena are investigated. The results show that the flow intensity increases, and the mixing time decreases with the increasing gas flow rate. The optimal porous plug’s radial position with one porous plug is 0.50R for its best mixing condition. When two porous plugs are adopted, the separation angle of 90 deg is recommended to improve the flow field and mixing phenomena.

42 ENGINEERING↗

DOE OSTI2025

Single-Molecule Fluorescence Microscopy Reveals Energy Transfer Active versus Inactive Nanocrystal/Dye Conjugate Pairs

Defect-mediated energy transfer (EnT) is a radiative process that occurs between donor defect states in the forbidden bandgap of semiconductor nanocrystals (NCs) and dye molecules bound to their surfaces. The EnT efficiency depends on the number of dye molecules attached to each NC, the donor–acceptor distance, and the dipole orientation factor between the donor and acceptor, all of which vary across all individual NCs in a sample. While ensemble-level fluorescence spectroscopy measurements have provided average values for donor–acceptor distances, dye-to-NC ratios, and EnT rate constants, questions remain about the impact of donor/acceptor heterogeneity on observed EnT efficiencies. Notably, ensemble-level measurements cannot distinguish between bare NCs and EnT-active versus inactive NC/dye pairs in the same sample batch, limiting the ability to design systems with 100% EnT efficiency. To address this, we studied defect-mediated EnT between AlexaFluor 555 dye acceptors chemically bound to ZnO NC donors at the level of single molecules and single NCs. Interestingly, 20% of bound NC/dye pairs are EnT-inactive, likely contributing to residual defect photoluminescence (PL) observed in ensemble-level measurements and reducing overall EnT efficiency. Single particle-level ZnO defect PL and acceptor fluorescence trajectories exhibited distinct microfluctuations, which are absent in bare ZnO NCs. We hypothesized that our observations can be explained with a competitive dye fluorescence quenching pathway, possibly due to charge transfer between the excited state dye and the ZnO NC. Numerical simulations of single-molecule PL traces for this scenario produced microfluctuations consistent with the experimental results. These findings highlight the impact of sample heterogeneity on EnT processes and provide insights for designing light-harvesting systems with optimized EnT efficiency.

25 ENERGY STORAGE↗

DOE OSTI2016

Controlling Nonsequential Double Ionization in Two-Color Circularly Polarized Femtosecond Laser Fields

Atoms undergoing strong-field ionization in two-color circularly polarized femtosecond laser fields exhibit unique two-dimensional photoelectron trajectories and can emit bright circularly polarized extreme ultraviolet and soft-x-ray beams. Here, we present the first experimental observation of nonsequential double ionization in these tailored laser fields. Moreover, we can enhance or suppress nonsequential double ionization by changing the intensity ratio and helicity of the two driving laser fields to maximize or minimize high-energy electron-ion rescattering. Our experimental results are explained through classical simulations, which also provide insight into how to optimize the generation of circularly polarized high harmonic beams.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2024

Effective optimization of atomic decoration in giant and superstructurally ordered crystals with machine learning

Crystals with complicated geometry are often observed with mixed chemical occupancy among Wyckoff sites, presenting a unique challenge for accurate atomic modeling. Similar systems possessing exact occupancy on all the sites can exhibit superstructural ordering, dramatically inflating the unit cell size. In this work, a crystal graph convolutional neural network (CGCNN) is used to predict optimal atomic decorations on fixed crystalline geometries. This is achieved with a site permutation search (SPS) optimization algorithm based on Monte Carlo moves combined with simulated annealing and basin-hopping techniques. Our approach relies on the evidence that, for a given chemical composition, a CGCNN estimates the correct energetic ordering of different atomic decorations, as predicted by electronic structure calculations. This provides a suitable energy landscape that can be optimized according to site occupation, allowing the prediction of chemical decoration in crystals exhibiting mixed or disordered occupancy, or superstructural ordering. Verification of the procedure is carried out on several known compounds, including the superstructurally ordered clathrate compound Rb8Ga27Sb16 and vacancy-ordered perovskite Cs2SnI6, neither of which was previously seen during the neural network training. In addition, the critical temperature of an order–disorder phase transition in solid solution CuZn is probed with our SPS routines by sampling site configuration trajectories in the canonical ensemble. This strategy provides an accurate method for determining favorable decoration in complex crystals and analyzing site occupation at unprecedented speed and scale.

Chemistry↗

DOE OSTI2024

Western Interconnection Baseline Study

The purpose of the baseline study is to evaluate the degree to which current industry planning processes meet the national 2035 decarbonization goals for the Western Interconnection. This analysis serves as a comparative baseline for the scenario analysis conducted in the NTP Study using a Western Interconnection dataset that is readily available to industry. This baseline analysis differs from the production cost modeling analysis and power flow analysis in the main NTP Study report (forthcoming). In particular, the analysis presented in this report reflects a business-as-usual future with an optimistic build out of specific planned transmission projects and foreseeable generation. In contrast, the NTP Study models a future generation and transmission expansion based on optimization from a capacity expansion model. The analysis presented herein also reflects a 2030 timeframe, whereas the main NTP Study production cost modeling analysis and power flow analysis reflect a 2035 time frame. This baseline analysis utilizes industry’s most reliable data to account for future transmission projects across various stages of development, with a particular focus on those in the permitting stage. Additionally, it incorporates projections for changes in generation capacity (both additions and retirements). This baseline analysis outlines a probable trajectory, given current process and practice, for the future of the bulk power system with a horizon extending to 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Energy‐aware relay positioning in flying networks

Summary The ability to move and hover has made rotary‐wing unmanned aerial vehicles (UAVs) suitable platforms to act as flying communications relays (FCRs), aiming at providing on‐demand, temporary wireless connectivity when there is no network infrastructure available or a need to reinforce the capacity of existing networks. However, since UAVs rely on their on‐board batteries, which can be drained quickly, they typically need to land frequently for recharging or replacing them, limiting their endurance and the flying network availability. The problem is exacerbated when a single FCR UAV is used. The FCR UAV energy is used for two main tasks: Communications and propulsion. The literature has been focused on optimizing both the flying network performance and energy efficiency from the communications point of view, overlooking the energy spent for the UAV propulsion. Yet, the energy spent for communications is typically negligible when compared with the energy spent for the UAV propulsion. In this article, we propose energy‐aware relay positioning (EREP), an algorithm for positioning the FCR taking into account the energy spent for the UAV propulsion. Building upon the conclusion that hovering is not the most energy‐efficient state, EREP defines the trajectory and speed that minimize the energy spent by the FCR UAV on propulsion, without compromising in practice the quality of service offered by the flying network. The EREP algorithm is evaluated using simulations. The obtained results show gains up to 26% in the FCR UAV endurance for negligible throughput and delay degradation.

Rodrigues, Hugo↗

DOE OSTI2017

Bend Magnet Heat Loads and Out of Orbit Scenarios

This paper presents an analytical calculation of the spatial power spectrum emitted from relativistic electrons passing through a series of bend magnets. Using lattice files from the software Elegant, both the ideal and missteered trajectories taken by the beam are considered in determination of the power profile. Calculations were performed for the Advanced Photon Source Upgrade multi-bend-achromat storage-ring. The power distribution and integrated total power values are in agreement with Synrad, a monte-carlo based program developed at CERN, within one percent error. The analytic solution used in this software gives a both quick and accurate tool for calculating the heat load on a photon absorber. The location and orientation can be optimized in order to reduce the peak intensity and thus the maximum thermal stress. The program can be used with any optimization or FEA software and gives rise to a versatile set of uses. [1]

MAGNET HEAT LOADS↗

DOE OSTI2025

Integral Field Probe for Mapping of Curved Magnets

The Single Stretched Wire (SSW) method allows highly precise integral field measurements by recording voltage across a tensioned wire mounted to 2-axis linear stages at either end of the magnet aperture. However, traditional SSW probes are not well suited for curved accelerator magnets, which are essential for steering charged particles along arced trajectories in storage rings or beamlines. The tension required to eliminate sag demands a purely straight path, making them incompatible with non-linear magnet geometries. To address this limitation for curved magnets, a modified approach was developed using a segmented, 3D-printed support structure that incorporates a pre-shaped anti-sag curve. Under its own weight and that of the wire bundle, the structure deforms to lie flat while conforming to the curvature of the magnet in the horizontal plane. The optimal geometry of the probe was derived using an iterative process combining FEA simulations in Ansys Mechanical with testing of various carbon fiber-reinforced filaments. The printed and assembled probe was successfully used to measure the SDD-059 magnet at Fermilab, yielding promising results.

Jakopin, Alexander [Northern Illinois U.]↗

DOE OSTI2014

WE-G-17A-03: MRIgRT: Quantification of Organ Motion

Purpose: To develop an MRI-based methodology and tools required for the quantification of organ motion on a dedicated MRI-guided radiotherapy system. A three-room facility, consisting of a TrueBeam 6X linac vault, a 1.5T MR suite and a brachytherapy interventional room, is currently under commissioning at our institution. The MR scanner can move and image in either room for diagnostic and treatment guidance purposes. Methods: A multi-imaging modality (MR, kV) phantom, featuring programmable 3D simple and complex motion trajectories, was used for the validation of several image sorting algorithms. The testing was performed on MRI (e.g. TrueFISP, TurboFLASH), 4D CT and 4D CBCT. The image sorting techniques were based on a) direct image pixel manipulation into columns or rows, b) single and aggregated pixel data tracking and c) using computer vision techniques for global pixel analysis. Subsequently, the motion phantom and sorting algorithms were utilized for commissioning of MR fast imaging techniques for 2D-cine and 4D data rendering. MR imaging protocols were optimized (e.g. readout gradient strength vs. SNR) to minimize the presence of susceptibility-induced distortions, which were reported through phantom experiments and numerical simulations. The system-related distortions were also quantified (dedicated field phantom) and treated as systematic shifts where relevant. Results: Image sorting algorithms were validated for specific MR-based applications such as quantification of organ motion, local data sampling, and 4D MRI for pre-RT delivery with accuracy better than the raw image pixel size (e.g. 1 mm). MR fast imaging sequences were commissioning and imaging strategies were developed to mitigate spatial artifacts with minimal penalty on the image spatial and temporal sampling. Workflows (e.g. liver) were optimized to include the new motion quantification tools for RT planning and daily patient setup verification. Conclusion: Comprehensive methods were developed and validated for the quantification of organ motion with applications in MRI-guided RT.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Optimal Spatial Separation of High-Order Harmonics from Infrared Driving Lasers with an Annular Beam in the Overdriven Regime

We study high-order harmonic generation (HHG) with an annularly shaped high-power, high-repetition-rate laser. In this work we investigate how the spatial separation (or divergence) of the incident laser and the generated high-order harmonics depends on the gas pressure when the laser intensity is in the overdriven regime. It is shown that, when the cone size of the incident annular beam is relatively large, the resulting harmonics are highly collimated along the propagation axis and are spatially separated from the incident beam. Under the overdriven condition, dynamic phase matching favors HHG emissions from short-trajectory electrons that are efficiently built up in the second half of the gas medium. We verify that using an annular beam is a simple and effective method for separating the intense incident infrared laser from the generated high harmonics. Such high-flux and low-divergence light pulses are expected to be powerful sources in the laboratory for ultrafast probing of electron dynamics.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Multi-Factor-Coupled, Ahead-of-Time Aggregation of Power Flexibility Under Forecast Uncertainty

The increasing penetration of distributed energy resources (DERs) is significantly reshaping the role of distribution systems under active energy management. To aggregate the active-reactive power flexibility of DERs dispersed at the feeder and provide capacity support to the transmission system, it is essential to efficiently identify feasible substation power injection trajectories. This paper introduces a novel ahead-of-time flexibility characterization method to address it. First, a polyhedral non-feeder-level power flexibility region (PFR) is constructed, accounting for various time-dependent, power-coupled, and forecast error uncertainties. Then, a polyhedral feeder-level PFR is analytically derived through a coordinate transformation, which can reveal the uncertainty propagation path, i.e., how uncertainty applies to the feeder-level PFR. To facilitate the high-level application, a tractable chance-constrained Chebyshev centering optimization model is further developed to find a ball-shaped inner approximation of the feeder-level PFR. Finally, the proposed method is validated on a modified IEEE 123-bus test system. Here, both theoretical and experimental results show that, with appropriate robustness parameter settings, the proposed method can make the approximated PFR less conservative with abundant robustness against forecast error uncertainty.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Evaluating the Effects of Missing Values and Mixed Data Types on Social Sequence Clustering Using t-SNE Visualization

© 2019 Association for Computing Machinery. The goal of this work is to investigate the impact of missing values in clustering joint categorical social sequences. Identifying patterns in sociodemographic longitudinal data is important in a number of social science settings. However, performing analytical operations, such as clustering on life course trajectories, is challenging due to the categorical and multidimensional nature of the data, their mixed data types, and corruption by missing and inconsistent values. Data quality issues were investigated previously on single variable sequences. To understand their effects on multivariate sequence analysis, we employ a dataset of mixed data types and missing values, a dissimilarity measure designed for joint categorical sequence data, together with dimensionality reduction methodologies in a systematic design of sequence clustering experiments. Given the categorical nature of our data, we employ an “edit” distance using optimal matching. Because each data record has multiple variables of different types, we investigate the impact of mixing these variables in a single dissimilarity measure. Between variables with binary values and those with multiple nominal values, we find that the ability to overcome missing data problems is more difficult in the nominal domain than in the binary domain. Additionally, alignment of leading missing values can result in systematic biases in dissimilarity matrices and subsequently introduce both artificial clusters and unrealistic interpretations of associated data domains. We demonstrate the usage of t-distributed stochastic neighborhood embedding to visually guide mitigation of such biases by tuning the missing value substitution cost parameter or determining an optimal sequence span.

Lazar, Alina↗

DOE OSTI2012

Target-specific optimization of four-dimensional cone beam computed tomography

Purpose: Under-sampling artifacts are a major problem in four-dimensional cone-beam computed tomography (4D-CBCT) and may compromise evaluation of target motion. Several studies have addressed scan parameter selection for minimizing under-sampling artifacts; however, the role of the target characteristics in scan parameter selection has not been investigated. In this work, the authors evaluated 4D-CBCT performance by assessing the accuracy of target motion measurements for various target sizes and motions. The results may serve as patient-specific guidelines for scan parameters selection in 4D-CBCT. Methods: The authors acquired 4D-CBCT scans of a moving phantom consisting of six water-filled sphere targets of sizes 10-37 mm, using various scan times ranging from 30 s to 3 min., setting the motion to 3-s and 6-s periods. The authors used automatic image registration to extract the target motion trajectories and evaluated these measurements for various target sizes and motions over various combinations of scan parameters including scan time, detector configuration, number of respiration phases, and reconstruction filters. Results: The most important object parameter to 4D-CBCT performance was the period of motion. Measurements for the 6-s motion were always systematically less accurate than measurements for the 3-s motion for 34 of 36 objects of various sizes and periods of motion. The 6-s motion required a greater scan time than the 3-s motion for equivalent measurement accuracy. The second most influential parameter was the target size. For the 3-s period of motion, objects larger than 13 mm were tracked with sub-millimeter accuracy with a 1-min scan time. For the 6-s period of motion, objects larger than 22-mm were tracked with sub-millimeter accuracy with a 1.5-min scan time. For all sizes and motions, temporal blurring was observed when the number of phases was fewer than 8. Offset detector configuration provided the same performance as centered detector except for small targets (20 mm.) at short scan times ({<=}1 min). Finally, reconstruction filtering and number of respiratory phases did not affect performance. Conclusions: Scan time should be set according to target size and motion. The authors have provided figures that provide the minimum scan time needed to achieve the particular motion measurement accuracy for a particular size and motion period.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Linking habitat suitability with a longleaf pine-hardwood model: Building a species-predictive fire-land management framework

Active management of fire-dependent ecosystems for specific species leads to complex tradeoffs, which affect conservation outcomes to other species. Therefore a multi-species evaluation of management actions is required. Habitat Suitability Models (HSMs) can help in predicting the likelihood of species occurrence using corresponding environmental variables and empirical relationships that link occurrence with specific environmental conditions. Incorporating multiple species into HSMs and relating them to habitat dynamics is crucial for ecosystems that require active management with prescribed fire. To address this issue, we developed multi-species HSM driven within an existing population model of the longleaf pine-hardwood ecosystem to assess the suitability of an ecosystem given different fire management strategies and environmental conditions. The population model used in this study provides spatial and temporal changes of longleaf pine-hardwood habitat structure in response to fire. These habitat values are used by the HSM to calculate habitat suitability for three threatened and endangered faunal species of this ecosystem, which all thrive with frequent fire, but have unique habitat requirements. Transient habitat conditions are traced to predict longleaf pine ecosystem trajectories under various management strategies, thereby evaluating current land management actions, such as thinning or prescribed fire frequencies. We tested a suite of environmental conditions to emphasize the sensitivity of the species to different fire management actions. The results of our modeling suggest that maximum suitable habitat for all three species can be achieved with fire frequency occurring at approximately once every three years. The modeling results support current management actions and provide a new habitat assessment tool that incorporates ecological factors for multiple species, thus providing for habitat optimization.

54 ENVIRONMENTAL SCIENCES↗