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DOE OSTI2023

Determining best practices for using genetic algorithms in molecular discovery

Genetic algorithms (GAs) are a powerful tool to search large chemical spaces for inverse molecular design. However, GAs have multiple hyperparameters that have not been thoroughly investigated for chemical space searches. In this tutorial, we examine the general effects of a number of hyperparameters, such as population size, elitism rate, selection method, mutation rate, and convergence criteria, on key GA performance metrics. Here, we show that using a self-termination method with a minimum Spearman’s rank correlation coefficient of 0.8 between generations maintained for 50 consecutive generations along with a population size of 32, a 50% elitism rate, three-way tournament selection, and a 40% mutation rate provides the best balance of finding the overall champion, maintaining good coverage of elite targets, and improving relative speedup for general use in molecular design GAs.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks

Physics-informed deep learning has emerged as a promising alternative for solving partial differential equations. However, for complex problems, training these networks can still be challenging, often resulting in unsatisfactory accuracy and efficiency. In this work, we demonstrate that the failure of plain physics-informed neural networks arises from the significant discrepancy in the convergence rate of residuals at different training points, where the slowest convergence rate dominates the overall solution convergence. Based on these observations, we propose a pointwise adaptive weighting method that balances the residual decay rate across different training points. The performance of our proposed adaptive weighting method is compared with current state-of-the-art adaptive weighting methods on benchmark problems for both physics-informed neural networks and physics-informed deep operator networks. In conclusion, through extensive numerical results we demonstrate that our proposed approach of balanced residual decay rates offers several advantages, including bounded weights, high prediction accuracy, fast convergence rate, low training uncertainty, low computational cost, and ease of hyperparameter tuning.

Balanced convergence rate↗

DOE OSTI2019

Enhancing the Rate Capability of Niobium Oxide Electrode through Rare‐Earth Doping Engineering

Abstract Niobium oxide is considered one of the most promising electrode materials for ultrafast electrochemical energy storage devices with high energy density. In this work, we first found that trace amounts (<1 %) of Yb 3+ doping remarkably enhanced the rate capability of T−Nb 2 O 5 , which was further proved to be because of the formation of a thin layer of amorphous YbNbO x . The capacity of YbNbO x ‐coated Nb 2 O 5 reached 124 mAh g −1 at 20 C, which is the highest value reported among pristine Nb 2 O 5 electrodes. Besides, we found that doping with other rare‐earth elements such as Nd 3+ , Sm 3+ , and Gd 3+ can also improve the rate capability of T−Nb 2 O 5 . It can be concluded that rare‐earth doping can be an effective and robust method to enhance the intrinsic rate performance of electrode materials without complicated modifications.

Yin, Dandan↗

DOE OSTI2019

EGS Collab Project: Accomplishments and Plan

To better understand stimulation and inter-well flow in crystalline rock with the goal of developing and improving subsurface heat exchangers for enhanced geothermal energy recovery, the EGS (Enhanced Geothermal Systems) Collab project is developing highly monitored, well- characterized intermediate scale (~10-20 m) field test beds, stimulating, and performing flow tests. These tests provide the ability to evaluate concepts, data to test and validate models, and tools to be used for EGS development, which may be evaluated at DOE’s Frontier Observatory for Research in Geothermal Energy (FORGE) project. Numerical simulation is key to the project, for experiment design and interpretation of results. Testbed characterization included optical and acoustic televiewers, full waveform seismic, electromagnetic, gamma, and temperature. The test block was further characterized using seismic tomography (p- and s-), electrical resistance tomography (ERT), and hydrologic characterization including tracer tests. Coupled process models are constrained by the detailed site characterization data. Installed monitoring systems include: 1) passive seismic/acoustic emissions; 2) continuous active source seismic; 3) ERT, with dynamic imaging using high contrast fluids; and 4) distributed acoustic, temperature, and strain fiber optic sensors. During flow and stimulation tests, fracture aperture strain monitoring is performed using the Step-rate Injection Method for Fracture In-situ Properties (SIMFIP) tool. Pressure and flow in the injection and production boreholes are monitored, and tracer tests and wavefield imaging and inversion are performed to provide additional constraints. Stimulations have been performed at several locations, connecting our injection and production wells. An overview of the EGS Collab project is presented to provide a framework for other EGS Collab presentations, along with results from numerical simulations and experiments performed at the Sanford Underground Research Facility in South Dakota.

Enhanced Geothermal Systems, EGS Collab, stimulati↗

DOE OSTI2026

Stochastic Microgrid Scheduling With Chance‐Constrained Resilience Consideration

Traditionally, it is assumed that microgrids transition seamlessly from grid‐connected operation to islanded mode in the event of sudden main grid outages. In reality, the islanding process, especially unintentional islanding, is rarely seamless. Instead, it is subject to voltage and frequency fluctuations caused by the instantaneous disconnection of the point of common coupling (PCC) switch, variations in loads and renewable generation output and even the protection tripping of distributed energy resources (DERs). To mitigate these fluctuations and facilitate a smooth islanding process, we propose a stochastic microgrid scheduling model that incorporates chance‐constrained resilience measures. Specifically, the resilience measure is defined as the probability of successful islanding (PSI), that is, the probability that a microgrid can mitigate the generation‐demand imbalance caused by the disconnection of the PCC switch, variations in load and renewable generation and DER tripping. This measure is modelled using chance constraints. Unlike existing reliability and resilience indices, which typically neglect the possibility of microgrid/DER failure under extreme events and assume their survival while primarily focussing on reducing impact duration or magnitude, the proposed PSI‐based framework explicitly addresses microgrid and DER survival during the islanding transition. The formulated nonlinear chance constraints are approximated using a multiinterval approach and equivalently represented as a mixed‐integer linear programming (MILP) formulation. Case study results validate the proposed method, showing that the PSI estimation error is reduced to less than 8%, compared to approximately 28% with existing methods. Various sensitivity analyses on the DER tripping rate and PSI settings were performed to validate the robustness of the proposed method. In particular, the necessity of accounting for DER tripping in the PSI calculation was demonstrated.

chance constrained optimization↗

DOE OSTI2017

Characterization of Wrapped Coil Tank Water Heater during Charging/Discharging

Heat pump water heaters (HPWH) are an energy efficient method for water heating compared to conventional electric water heaters. A wrapped coil around the water tank is often used as the condenser for the heat pump for such applications. Thermal stratification, caused by varying heat transfer rate from the condenser to the water depending on the phase of the refrigerant and the wrap configuration, is often observed inside the tank, especially for HPWHs using CO2 as the refrigerant. The current study investigates the impact of the charging/discharging process on thermal stratification. A series of simulations were conducted based on the draw patterns recommended by the DOE method of test for rating water heater performance. We also analyzed the water circulation patterns during charging/discharging process. The thermal stratification was adversely affected because of the circulation even when the Heat Pump (HP) was operational. It was observed that a relatively higher charge/discharge flow rate disrupts the thermal stratification quickly and thus lowers the supply water temperature. Furthermore, the duration of charging/discharging also plays an important role. It was noticed that the back flow has insignificant effect on the supply water temperature if charging/discharging time is relatively small. However, the effect was obvious for larger water draw flow rates that last for longer time.

Elatar, Ahmed↗

DOE OSTI2018

Global variance reduction method applied to HBR-2 benchmark - 25144

It is a great challenge to obtain reliable results in reasonable time by the Monte Carlo (MC) method in solving deep-penetration shielding problems. Global variance reduction (GVR) method uses biased source and weight window to decrease MC calculation tally error for deep-penetration problems. However, excessive splitting of large weight particles out of the source region is time-consuming for problems with significant fluence rate variation. A new GVR method, which performs space and energy splitting/roulette based on the importance of the phase space, is proposed in this paper to avoid excessive splitting of large weight particles. The improved GVR method is applied to HBR-2 benchmark. Numerical results show that the new GVR method achieves good corresponding results to those of references. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Wavefront shaping with a Hadamard basis for scattering soil imaging

Here, soil is a scattering medium that inhibits imaging of plant-microbial-mineral interactions that are essential to plant health and soil carbon sequestration. However, optical imaging in the complex medium of soil has been stymied by the seemingly intractable problems of scattering and contrast. Here, we develop a wavefront shaping method based on adaptive stochastic parallel gradient descent optimization with a Hadamard basis to focus light through soil mineral samples. Our approach allows a sparse representation of the wavefront with reduced dimensionality for the optimization. We further divide the used Hadamard basis set into subsets and optimize a certain subset at once. Simulation and experimental optimization results demonstrate our method has an approximately seven times higher convergence rate and overall better performance compared to that with optimizing all pixels at once. The proposed method can benefit other high-dimensional optimization problems in adaptive optics and wavefront shaping.

47 OTHER INSTRUMENTATION↗

DOE OSTI2018

An Efficient Pipeline for Abdomen Segmentation in CT Images

Computed tomography (CT) scans usually include some disadvantages due to the nature of the imaging procedure, and these handicaps prevent accurate abdomen segmentation. Discontinuous abdomen edges, bed section of CT, patient information, closeness between the edges of the abdomen and CT, poor contrast, and a narrow histogram can be regarded as the most important handicaps that occur in abdominal CT scans. Currently, one or more handicaps can arise and prevent technicians obtaining abdomen images through simple segmentation techniques. In other words, CT scans can include the bed section of CT, a patient’s diagnostic information, low-quality abdomen edges, low-level contrast, and narrow histogram, all in one scan. These phenomena constitute a challenge, and an efficient pipeline that is unaffected by handicaps is required. In addition, analysis such as segmentation, feature selection, and classification has meaning for a real-time diagnosis system in cases where the abdomen section is directly used with a specific size. A statistical pipeline is designed in this study that is unaffected by the handicaps mentioned above. Intensity-based approaches, morphological processes, and histogram-based procedures are utilized to design an efficient structure. Performance evaluation is realized in experiments on 58 CT images (16 training, 16 test, and 26 validation) that include the abdomen and one or more disadvantage(s). The first part of the data (16 training images) is used to detect the pipeline’s optimum parameters, while the second and third parts are utilized to evaluate and to confirm the segmentation performance. The segmentation results are presented as the means of six performance metrics. Thus, the proposed method achieves remarkable average rates for training/test/validation of 98.95/99.36/99.57% (jaccard), 99.47/99.67/99.79% (dice), 100/99.91/99.91% (sensitivity), 98.47/99.23/99.85% (specificity), 99.38/99.63/99.87% (classification accuracy), and 98.98/99.45/99.66% (precision). In summary, a statistical pipeline performing the task of abdomen segmentation is achieved that is not affected by the disadvantages, and the most detailed abdomen segmentation study is performed for the use before organ and tumor segmentation, feature extraction, and classification.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2017

Transmission Line Ampacity Improvements of AltaLink Wind Plant Overhead Tie-Lines Using Weather-Based Dynamic Line Rating

Abstract—Overhead transmission lines (TLs) are conventionally given seasonal ratings based on conservative environmental assumptions. Such an approach often results in underutilization of the line ampacity as the worst conditions prevail only for a short period over a year/season. We presents dynamic line rating (DLR) as an enabling smart grid technology that adaptively computes ratings of TLs based on local weather conditions to utilize additional headroom of existing lines. In particular, general line ampacity state solver utilizes measured weather data for computing the real-time thermal rating of the TLs. The performance of the presented method is demonstrated from a field study of DLR technology implementation on four TL segments at AltaLink, Canada. The performance is evaluated and quantified by comparing the existing static and proposed dynamic line ratings, and the potential benefits of DLR for enhanced transmission assets utilization. For the given line segments, the proposed DLR results in real-time ratings above the seasonal static ratings for most of the time; up to 95.1% of the time, with a mean increase of 72% over static rating.

17 WIND ENERGY↗

DOE OSTI2025

The development and application of the stirred‐reactor coupon analysis (SRCA) test method

A new technique, termed the stirred‐reactor coupon analysis (SRCA) method, has been developed to measure the rate of glass dissolution in forward‐rate conditions. Monolithic glass coupons are partially masked with an inert material before placement in a large volume of well‐mixed solution with known chemistry and temperature for a predetermined duration. After the test, the mask is removed, and the difference in step height between the protected area and the exposed corroded portions of the sample coupon is measured to determine the extent of glass dissolution. The step height is converted to a rate measurement using the test duration and glass density. Test parameters such as sample surface preparation and test duration were evaluated to determine their effects on the measured rates. Additionally, results from an interlaboratory study (ILS) consisting of 12 laboratories from 11 different institutions are presented, where each laboratory performed 12 independent tests. When removing experimental outlier data, the 95% reproducibility limits for the SRCA method has no statistical difference with previously published standardized test methods used to determine the forward rate of glass dissolution. Overall, this paper describes steps necessary to perform the test method and provides the statistical calculations to evaluate test accuracy.

chemical durability↗

DOE OSTI2023

Results of FY 2023 Alloy 617 and Alloy 709 High-Temperature Crack-Growth Testing

This report summarizes the work performed at Idaho National Laboratory under the “Creep, fatigue and creep-fatigue crack growth tests” task of the “Long-Term VHTR Material Qualification – INL” work package. Work was performed this year to validate the crack growth monitoring setup used with the test frames against both continuous crack length monitoring using an optical camera, as well as post-mortem analysis of marker bands on the fracture surface. Delays prevented the use of a gauge to measure load-line displacement for early tests, and so the creep-fatigue crack growth setup was evaluated using the actuator displacement for a load-line displacement setup. While not ideal, this allowed examination of the shortcomings with the current software setup that was originally designed for performing stress corrosion crack growth rate studies. The method for data collection was modified to link the crack growth monitoring software with Instron’s Wave Matrix software. Once the load-line displacement gauge arrived, the crack growth equipment was successfully modified to permit continuous monitoring of both load-line displacement and crack length. This is critical for creep-fatigue and creep crack growth rate studies for ductile material, as it permits the C* and Ct analyses. Test results are shown for Alloy 617 fatigue and creep-fatigue (without the gauge for load-line displacement measurements), as well as creep-fatigue of Alloy 709, which was performed with the completed test setup, allowing for crack length and load-line displacement monitoring.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Magnetite (Fe 3 O 4 )—multiwalled carbon nanotube composite structures with performance as high rate electrode materials for Li-ion batteries

A method of synthesizing an electrode material for lithium ion batteries from Fe 3 O 4 nanoparticles and multiwalled carbon nanotubes (MWNTs) to yield (Fe 3 O 4 -NWNTs) composite heterostructures. The method includes linking the Fe 3 O 4 nanoparticles and multiwalled carbon nanotubes using a π-π interaction synthesis process to yield the composite heterostructure electrode material. Since Fe 3 O 4 has an intermediate voltage, it can be considered an anode (when paired with a higher voltage material) or a cathode (when paired with a lower voltage material).

Wong, Stanislaus↗

DOE OSTI2018

Compact 3D Copper with Uniform Porous Structure Derived by Electrochemical Dealloying as Dendrite-Free Lithium Metal Anode Current Collector

Here, the development of lithium (Li) metal anodes Li metal batteries faces huge challenges such as uncontrolled Li dendrite growth and large volume change during Li plating/stripping, resulting in severe capacity decay and high safety hazards. A 3D porous copper (Cu) current collector as a host for Li deposition can effectively settle these problems. However, constructing a uniform and compact 3D porous Cu structure is still an enormous challenge. Herein, an electrochemical etching method for Cu–Zinc (Zn) alloy is reported to precisely engrave a 3D Cu structure with uniform, smooth, and compact porous network. Such a continuous structure endows 3D Cu excellent mechanical properties and high electrical conductivity. The uniform and smooth pores with a large internal surface area ensures well dispersed current density for homogeneous Li metal deposition and accommodation. A smooth and stable solid electrolyte interphase is formed and meanwhile Li dendrites and dead Li are effectively suppressed. The Li metal anode conceived 3D Cu current collector can stably cycle for 400 h under an Li plating/stripping capacity of 1 mA h cm –2 and a current density of 1 mA cm –2 . The Li@3D Cu||LiFePO 4 full cells present excellent cycling and rate performances. The electrochemical dealloying is a robust method to construct 3D Cu current collectors for dendrite–free Li metal anodes.

25 ENERGY STORAGE↗

DOE OSTI2023

Insights into Chemical Prelithiation of SiO x /Graphite Composite Anodes through Scanning Electron Microscope Imaging

Initial Coulombic efficiency (ICE) is critical for determining the energy density of lithium-ion batteries (LIBs) used for practical applications; however, it is typically disregarded in anode research. We used SiO x and graphite composite anodes for commercial lithium-ion batteries in our preliminary research to achieve a balance between ICE, capacity, and cycling life. ICE reached 88%; however, it needs further improvement for commercial applications. Prelithiation is a process that involves the introduction of extra lithium ions into LIBs during their manufacturing to enhance the overall performance of the LIBs. We applied a chemical prelithiation method on our SiO x /graphite composite anodes, which comprised 95 wt % of the active material mass loading on the electrode. The ICE increased from 88% to 98% using an aryllithium reagent impregnation method within 2 min of prelithiation. The anode’s specific capacity density, rate, and cycle performance also significantly improved. Scanning electron microscopy (SEM) imaging enhanced by an osmium tetroxide staining method indicated that the P-anode contained a stable solid electrolyte interface (SEI) layer after the prelithiation process and cycling electrochemical test. The P-anode’s stable charge differential peak over 500 cycles also showcases a robust artificial SEI layer that was generated by the prelithiation procedure. Here, this prelithiation process has significant potential for adoption in the LIB industry’s current electrode manufacturing process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Evaluating county-level lung cancer incidence from environmental radiation exposure, PM 2.5 , and other exposures with regression and machine learning models

Characterizing the interplay between exposures shaping the human exposome is vital for uncovering the etiology of complex diseases. For example, cancer risk is modified by a range of multifactorial external environmental exposures. Environmental, socioeconomic, and lifestyle factors all shape lung cancer risk. However, epidemiological studies of radon aimed at identifying populations at high risk for lung cancer often fail to consider multiple exposures simultaneously. For example, moderating factors, such as PM 2.5 , may affect the transport of radon progeny to lung tissue. This ecological analysis leveraged a population-level dataset from the National Cancer Institute’s Surveillance, Epidemiology, and End-Results data (2013–17) to simultaneously investigate the effect of multiple sources of low-dose radiation (gross γ activity and indoor radon) and PM 2.5 on lung cancer incidence rates in the USA. County-level factors (environmental, sociodemographic, lifestyle) were controlled for, and Poisson regression and random forest models were used to assess the association between radon exposure and lung and bronchus cancer incidence rates. Tree-based machine learning (ML) method perform better than traditional regression: Poisson regression: 6.29/7.13 (mean absolute percentage error, MAPE), 12.70/12.77 (root mean square error, RMSE); Poisson random forest regression: 1.22/1.16 (MAPE), 8.01/8.15 (RMSE). The effect of PM 2.5 increased with the concentration of environmental radon, thereby confirming findings from previous studies that investigated the possible synergistic effect of radon and PM 2.5 on health outcomes. In summary, the results demonstrated (1) a need to consider multiple environmental exposures when assessing radon exposure’s association with lung cancer risk, thereby highlighting (1) the importance of an exposomics framework and (2) that employing ML models may capture the complex interplay between environmental exposures and health, as in the case of indoor radon exposure and lung cancer incidence.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2023

Realistic fuel spray modeling for gasoline direct injection engine applications

Fuel spray modeling plays a critical role during modern gasoline direct injection (GDI) engine development due to fuel injection’s dominant impact on engine performance and emissions as well as the complex physical processes involved. In engineering three-dimensional (3D) computational fluid dynamics (CFD) simulations, the liquid-phase fuel atomization, evaporation, and mixing are usually modeled with the discrete droplet model (DDM) adopting a Lagrangian approach for multiphase CFD simulations. To this end, general practices heavily depend on the reduced order characterization of the injector nozzle flow. However, such simplified injector modeling may lead to insufficient representations of the complex spray dynamics. To tackle this problem, this study proposes a novel workflow to numerically evaluate GDI sub-cooled and flash-boiling sprays under engine-relevant conditions using a side-mounted GDI injector together with real gasoline fuel properties. The workflow introduces a one-way coupling (OWC) method leveraging high-fidelity nozzle flow simulations to provide realistic boundary conditions to the Lagrangian injector model. The proposed workflow was first verified in a constant volume chamber (CVC) environment and then implemented in a practical GDI engine setup to study spray morphology, fuel-air mixing, and wall-wetting propensity. In addition, detailed comparison was performed between the OWC method and the conventional rate of injection (ROI) routine. In conclusion, quantitative analysis of spray characteristics was conducted to highlight possible source of discrepancies of the conventional ROI method.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Modification of a Silicon Photomultiplier for Reduced High Temperature Dark Count Rate

In this work we present a novel method for improving the high-temperature performance of silicon photomultipliers (SiPMs) via focused ion beam (FIB) modification of individual microcells. The literature suggests that most of the dark count rate (DCR) in a SiPM is contributed by a small percentage (<5%) of microcells. By using a FIB to electrically deactivate this relatively small number of microcells, we believe we can greatly reduce the overall DCR of the SiPM at the expense of a small reduction in overall photodetection efficiency, thereby improving its high temperature performance. In this report we describe our methods for characterizing the SiPM to determine which individual microcells contribute the most to the DCR, preparing the SiPM for FIB, and modifying the SiPM using the FIB to deactivate the identified microcells.

42 ENGINEERING↗