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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Interpenetrated Structures for Enhancing Ion Diffusion Kinetics in Electrochemical Energy Storage Devices

The architectural design of electrodes offers new opportunities for next-generation electrochemical energy storage devices (EESDs) by increasing surface area, thickness, and active materials mass loading while maintaining good ion diffusion through optimized electrode tortuosity. However, conventional thick electrodes increase ion diffusion length and cause larger ion concentration gradients, limiting reaction kinetics. We demonstrate a strategy for building interpenetrated structures that shortens ion diffusion length and reduces ion concentration inhomogeneity. This free-standing device structure also avoids short-circuiting without needing a separator. The feature size and number of interpenetrated units can be adjusted during printing to balance surface area and ion diffusion. Starting with a 3D-printed interpenetrated polymer substrate, we metallize it to make it conductive. This substrate has two individually addressable electrodes, allowing selective electrodeposition of energy storage materials. Using a Zn//MnO 2 battery as a model system, the interpenetrated device outperforms conventional separate electrode configurations, improving volumetric energy density by 221% and exhibiting a higher capacity retention rate of 49% compared to 35% at temperatures from 20 to 0 °C. Our study introduces a new EESD architecture applicable to Li-ion, Na-ion batteries, supercapacitors, etc.

25 ENERGY STORAGE↗
DOE OSTI2019

Fast, Dynamic, and Scalable Algorithms for Large-Scale Constrained Optimization

Scientists and engineers constantly aim to optimize an objective subject to physical, environmental, and/or resource constraints. The technique of using mathematical models to formulate and find real solutions of such problems is known as mathematical optimization, a process that has become invaluable for design and discovery in numerous scientific fields. This project has focused on the design, analysis, and implementation of high-performance computing algorithms for solving cutting-edge optimization problems. These include problems that involve (1) data uncertainties, such as those in the future supply, demand, and capacity of a given power system, (2) extreme numbers of alternatives, such as in the design of electrical power grids to avoid network vulnerabilities, and (3) real-time decisions, such as in the control of chemical reactors. The key features of the new algorithms are that they are fast, dynamic, and scalable to meet the computational requirements of scientists and researchers working to optimize large-scale, complex systems. The algorithms that have been designed, analyzed, and tested as part of the project can be characterized based on the types of optimization problems they have been designed to solve. Much of the work has focused on algorithms for solving large-scale constrained optimization problems. Contributions have also been made in the design of algorithms for unconstrained optimization, with some specialized methods for solving problems that have inherent nonsmoothness. Contributions have also been made in areas that have grown to prominence in the field over the five-year award period. These include the design of algorithms for solving large-scale stochastic optimization problems, such as those that arise in large-scale machine learning, and in complexity analyses for solving nonconvex problems, which has been a focal point of much recent work in continuous optimization. Overall, the project has supported work that has led to almost 30 articles that have been published or accepted to top journals in the field of mathematical optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Pyomo.DOE: An open-source package for model-based design of experiments in Python

Predictive mathematical models are a cornerstone of science and engineering. Yet selecting, calibrating, and validating said science-based models often remains an art in practice. Model-based design of experiments (MBDoE) provides a systematic framework to maximize information gain from experiments while minimizing time and resource costs. But MBDoE remains limited to niche application areas, in part because practitioners must integrate expertise in statistics, computational optimization, and modeling. To help reduce this barrier, we introduce Pyomo.DOE, an open-source package for MBDoE. Pyomo.DOE uses a nonlinear sensitivity analysis code k_aug to quickly approximate the Fisher information matrix and leverages a new stochastic programming abstraction. We demonstrate Pyomo.DOE with the first application of MBDoE to fixed-bed breakthrough experiments, which highlights the power of Pyomo.DOE to quantify the value of experimental modifications a priori for large-scale partial differential-algebraic equation (PDAE) models. Here we also provide a mathematical primer on MBDoE targeted at general chemical engineers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Environmental Tradeoffs of Stover Removal and Erosion in Indiana

When considering the market for biomass from corn stover resources erosion and soil quality issues are important to consider. Removal of stover can be beneficial in some areas, especially when coordinated with other conservation practices, such as vegetative barrier strips and cover crops. However, benefits are highly dependent on several factors, namely if farmers see costs and benefits associated with erosion and the tradeoffs with the removal of biomass. Although typically considered an internal cost, the implication is important to policy and contracting for biomass. This paper uses results from an integrated RUSLE2/WEPS model to incorporate six different regime choices, covering management, harvest and conservation, into a simple profit maximization model to show these tradeoffs explicitly. The results of this work show how different costs for erosion, biomass and conservation managements will affect behavior. If erosion prices are low and no conservation requirement exists, biomass removal will significantly increase erosion, but only in some areas. Alternatively, when erosion prices are high, farmers will parallel socially optimal levels of erosion and conservation management practices can be incentivized through access to a market for stover.

09 BIOMASS FUELS↗
DOE OSTI2012

Serum Gamma-Glutamyl-Transferase Independently Predicts Outcome After Transarterial Chemoembolization of Hepatocellular Carcinoma: External Validation

Purpose: An Asian study showed that gamma glutamyl transpeptidase (GGT) can predict survival after transarterial chemoembolization (TACE) of hepatocellular carcinoma (HCC). This study was designed to validate in a European population this biomarker as an independent predictor of outcome after TACE of HCC and to determine a threshold value for clinical use. Methods: In 88 consecutive patients treated by TACE for HCC, the optimal threshold for GGT serum level was determined by a ROC analysis. Endpoints were time-to-treatment failure (TTTF) and overall survival (OS). All multivariate models were internally validated using bootstrapping (90 replications). Results: Median follow-up lasted 373 days, and median overall survival was 748 days. The optimal threshold for GGT was 165 U/L (sensitivity: 89.3%; specificity: 56.7%; area under the ROC curve: 0.7515). Median TTTF was shorter when GGT was {>=}165 U/L (281 days vs. 850 days; P < 0.001). GGT {>=}165 U/L (hazard ratio (HR) = 2.06; P = 0.02), WHO PS of 2 (HR = 5.4; P = 0.002), and tumor size (HR = 1.12; P = 0.014) were independently associated with shorter TTTF. Median OS was shorter when GGT was {>=}165 U/L (508 days vs. not reached; P < 0.001). GGT {>=} 165 U/L (HR = 3.05; P = 0.029), WHO PS of 2 (HR = 12.95; P < 0.001), alfa-fetoprotein (HR = 2.9; P = 0.01), and tumor size (HR = 1.096; P = 0.013) were independently associated with shorter OS. The results were confirmed by bootstrapping. Conclusions: Our results provide in a European population the external validation of GGT as an independent predictor of outcome after TACE of HCC. A serum level of GGT {>=} 165 U/L is independently associated with both shorter TTTF and OS.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Early season prediction of within-field crop yield variability by assimilating CubeSat data into a crop model

Accurate early season predictions of crop yield at the within-field scale can be used to address a range of crop production, management, and precision agricultural challenges. While the remote sensing of within-field insights has been a research goal for many years, it is only recently that observations with the required spatio-temporal resolutions, together with efficient assimilation methods to integrate these into modeling frameworks, have become available to advance yield prediction efforts. Here we explore a yield prediction approach that combines daily high-resolution CubeSat imagery with the APSIM crop model. The approach employs APSIM to train a linear regression that relates simulated yield to simulated leaf area index (LAI). That relationship is then used to identify the optimal regression date at which the LAI provides the best prediction of yield: in this case, approximately 14 weeks prior to harvest. Instead of applying the regression on satellite imagery that is coincident, or closest to, the regression date, our method implements a particle filter that integrates CubeSat-based LAI into APSIM to provide end-of-season high-resolution (3 m) yield maps weeks before the optimal regression date. The approach is demonstrated on a rainfed maize field located in Nebraska, USA, where suitable collections of both imagery and in-situ data were available for assessment. The procedure does not require in-field data to calibrate the regression model, with results showing that even with a single assimilation step, it is possible to provide yield estimates with good accuracy up to 21 days before the optimal regression date. Yield spatial variability was reproduced reasonably well, with a strong correlation to independently collected measurements (R 2 = 0.73 and rRMSE = 12%). When the field averaged yield was compared, our approach reduced yield prediction error from 1 Mg/ha (control case based on a calibrated APSIM model), to 0.5 Mg/ha (using satellite imagery alone), and then to 0.2 Mg/ha (results with assimilation up to three weeks prior to the optimal regression date). Such a capacity to provide spatially explicit yield predictions early in the season has considerable potential to enhance digital agricultural goals and improve end-of-season yield predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

LaSDI: Parametric Latent Space Dynamics Identification

Enabling fast and accurate physical simulations with data has become an important area of computational physics to aid in inverse problems, design-optimization, uncertainty quantification, and other various decision-making applications. This paper presents a data-driven framework for parametric latent space dynamics identification procedure that enables fast and accurate simulations. The parametric model is achieved by building a set of local latent space model and designing an interaction among them. An individual local latent space dynamics model achieves accurate solution in a trust region. By letting the set of trust region to cover the whole parameter space, our model shows an increase in accuracy with an increase in training data. Herein we introduce two different types of interaction mechanisms, i.e., point-wise and region-based approach. Both linear and nonlinear data compression techniques are used. We illustrate the framework of Latent Space Dynamics Identification (LaSDI) enable a fast and accurate solution process on various partial differential equations, i.e., Burgers’ equations, radial advection problem, and nonlinear heat conduction problem, achieving 0 (100)x speed-up and 0 (1)% relative error with respect to the corresponding full order models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Optimization-based modeling and analysis of brine reflux osmotically assisted reverse osmosis for application toward zero liquid discharge systems

Significant amounts of high-salinity wastewater generated by water-intensive industrial activities such as shale oil and gas production have raised serious environmental concerns in recent years. Existing and emerging desalination technologies offer promise to manage these high salinity wastewater streams while simultaneously producing fresh water that could be diverted for beneficial uses. Osmotically assisted reverse osmosis (OARO) is one such emerging desalination technology capable of handling hypersaline brines and achieving high recoveries. However, rigorous modeling and analysis is needed to evaluate the process performance, energy consumption, and treatment cost of various OARO configurations. Here, this work presents detailed modeling and analysis of brine-reflux OARO (BR-OARO) system and compares it with other commonly discussed configurations, including cascading osmotically mediated reverse osmosis (COMRO), consecutive loop OARO, and split feed counterflow RO, through a cost optimization-based framework. We analyze and compare the treatment costs, membrane area, specific energy consumption, and design parameters of the aforementioned configurations with the ultimate goal of achieving zero liquid discharge (ZLD). The results indicate that the BR-OARO system with treatment cost of 5.1 US $/m 3 of produced water with 10% salinity outperforms other configurations in terms of number of stages needed, treatment cost, membrane area, and energy consumption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Separating Miscible Liquid–Liquid Mixtures Using Supported Ionic Liquid Membranes

Supported liquid membranes (SLMs) are promising in separating miscible liquid–liquid mixtures, which has been a key challenge in wastewater treatment and other applications. However, SLMs suffer from poor durability due to the loss of the liquid phase. In current work, ionic liquids (ILs) with high stability have been impregnated into polyvinylidene fluoride membranes to separate miscible benzene–heptane mixtures. The two imidazolium-based ILs, that is, 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIM][PF 6 ]) and 1-butyl-3-methylimidazolium tris(pentafluoroethyl) trifluorophosphate ([BMIM][FAP]), were tested in supported ionic liquid membranes (SILMs) for the benzene–heptane separation. Both ILs show successful separation within 48 h as indicated by nuclear magnetic resonance results. Compared to the SILM with [BMIM][FAP], the SILM with [BMIM][PF 6 ] has lower throughput and higher selectivity. The higher selectivity can be attributed to the higher hydrophilicity of [BMIM][PF 6 ], which results in strong repulsion against heptane. The lower throughput can be attributed to the higher hydrophilicity as well since it lowers the solubility of benzene in [BMIM][PF 6 ]. The stability of IL in SILMs has also been investigated via multiple separation cycles. The scanning electron microscopy, weight change of SILMs, and separation results indicate that the separation efficiency of the [BMIM][PF 6 ] SILM does not degrade for up to 144 h. The SILM has been further optimized with curvature design (i.e., curved SILM) to increase the interfacial area and thus increase the separation throughput, where the curved SILM separation device was 3D-printed. Here, the findings here have important implications on design and application of SILMs in separating miscible liquid–liquid mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Capturing chemical intuition in synthesis of metal-organic frameworks

We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal-organic framework. We define chemical intuition as the collection of unwritten guidelines used by synthetic chemists to find the right synthesis conditions. As (partially) failed experiments usually remain unreported, we have reconstructed a typical track of failed experiments in a successful search for finding the optimal synthesis conditions that yields HKUST-1 with the highest surface area reported to date. We illustrate the importance of quantifying this chemical intuition for the synthesis of novel materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Pure edge-dislocation half-loops in low-temperature Ga⁢N for V-defect formation

Lateral injection of carriers through semipolar crystallographic planes into c-plane QWs is one of the new frontiers in III-N light-emitting diodes (LEDs), especially for long wavelengths. Strategic use of V-defects has proven to be the most promising method for lateral injection, and creating optimal V-defect structure and density is an important research area for reducing forward voltage and increasing wall plug efficiency. Here, in this article, we present a novel method for forming V-defects in nominally unstressed low-temperature Ga⁢N through the generation of pure edge-dislocation half-loops. We present a detailed material science analysis of the loops via scattering-contrast electron microscopy. The loops have pure-edge character with Burgers vector 1/3 ⁢⟨$11\bar{2}0$⟩, and form in a sessile orientation on {$11\bar{2}0$} a-planes. The two arms of the loops are inclined such that the extra half-planes face down toward the growth substrate. The dislocation loops can be used to intentionally form V-defects through conditions of kinetically limited growth: these conditions also favor nucleation of V-defects at ∼100% of other threading dislocations in the Ga⁢N templates. Patterned sapphire substrates (PSS) are one of the most important substrates for III-N LED growth because of their superior light extraction. However, due to its low threading dislocation density, PSS have not been used extensively for V-defect LEDs. This work provides a pathway for improved control of V-defect formation and density on LEDs grown on sapphire with the goal of enabling uniform lateral injection in these V-defect engineered LEDs with low forward voltage, including PSS for high light extraction.

LEDs↗
DOE OSTI2016

MtSWEET11, a Nodule-Specific Sucrose Transporter of Medicago truncatula

Optimization of nitrogen fixation by rhizobia in legumes is a key area of research for sustainable agriculture. Symbiotic nitrogen fixation (SNF) occurs in specialized organs called nodules and depends on a steady supply of carbon to both plant and bacterial cells. Here we report the functional characterization of a nodule-specific Suc transporter, MtSWEET11 from Medicago truncatula . MtSWEET11 belongs to a clade of plant SWEET proteins that are capable of transporting Suc and play critical roles in pathogen susceptibility. When expressed in mammalian cells, MtSWEET11 transported sucrose (Suc) but not glucose (Glc). The MtSWEET11 gene was found to be expressed in infected root hair cells, and in the meristem, invasion zone, and vasculature of nodules. Expression of an MtSWEET11-GFP fusion protein in nodules resulted in green fluorescence associated with the plasma membrane of uninfected cells and infection thread and symbiosome membranes of infected cells. Two independent Tnt1 -insertion sweet11 mutants were uncompromised in SNF. Furthermore, although MtSWEET11 appears to be involved in Suc distribution within nodules, it is not crucial for SNF, probably because other Suc transporters can fulfill its role(s).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Volumetric nondestructive evaluation for damage in carbon fiber reinforced polymer panels subjected to artificial lightning strikes

Aircrafts and wind turbine blades often get hit by lightning strikes due to their operating locations. With increasing incidents of lightning flashes every year due to global warming, damage assessment of CFRP structures after lightning strike to aircrafts and wind turbine blades is getting increasingly important. Many researchers are involved in designing better and more resilient lighting strike protection materials and often utilize non-destructuve evaluation (NDE) methods such as ultrasonic testing (UT), high-speed digital videograpgy, and high-speed IR thermography. In particular, UT is widely used due to its cost-effectiveness compared to other methods. Using UT imaging can obtain any potential damaged locations caused by lightning strike through the thickness of the composite specimens. Traditional UT and visual inspections only display the damage in units area, when in fact the UT data is volumetric. This study optimized the UT data to measure and display the volumetric damage after artificial lightning strike and is compared to the standardized visual inspection.

Spencer, Ryan↗
DOE OSTI2014

TH-E-BRF-10: Interim Esophageal Cancer Response Assessment Via 18FDG-PET Scanning During Radiation Therapy

Purpose: Local failure occurs in a large proportion of esophageal cancer patients treated with chemoradiation. The treatment strategy for non-responders could potentially be modified if they are identified during therapy. This work investigates the utility of an interim 18FDG-PET scan acquired during the course of therapy as a predictor of pathological response post-therapy. Methods: Fifteen patients underwent 18FDG-PET scanning prior to radiation therapy (RT) and once during RT, after delivery of ∼32 Gy. The physician-contoured GTV on the planning CT scan was used to automatically segment a PET-based GTV on the pre-RT PET (GTV-pre-PET) as the volume with >40% of the maximum GTV PET SUV value. The pre- and intra-RT CTs were deformably registered to each other to transfer the GTV-pre-PET to the intra-RT PET (GTV-intra-PET). The fractional decrease in the maximum SUV, mean SUV and the SUV to the highest intensity 10% – 90% volumes from GTV-pre-PET to GTV-intra-PET were compared to pathological response assessed at the time of post-RT surgery. Results: Based on post-treatment pathology of 15 patients, 7 were classified as achieving favorable response (treatment effect grade ≤ 1) and 8 as unfavorable response (treatment effect grade > 1). Neither fractional decrease in maximum SUV nor mean SUV were significant between the favorable and unfavorable groups. However, the fractional decrease in SUV20% (SUV to the highest 20% volume) was significant (p = 0.02), with an area under the Receiver Operating Characteristics (ROC) curve of 0.84. An optimal cutoff value of 0.46 for this metric was able to distinguish between the two groups with 71% sensitivity (favorable) and 88% specificity (unfavorable). Conclusion: The fractional decrease in SUV to the volume with highest 20% intensity from pre- to intra-RT 18FDG-PET imaging may be used to distinguish between favorable and unfavorable responders with high sensitivity and specificity.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Web-based, GPU-accelerated, Monte Carlo simulation and visualization of indirect radiation imaging detector performance

Purpose: Monte Carlo simulations play a vital role in the understanding of the fundamental limitations, design, and optimization of existing and emerging medical imaging systems. Efforts in this area have resulted in the development of a wide variety of open-source software packages. One such package, hybridMANTIS, uses a novel hybrid concept to model indirect scintillator detectors by balancing the computational load using dual CPU and graphics processing unit (GPU) processors, obtaining computational efficiency with reasonable accuracy. In this work, the authors describe two open-source visualization interfaces, webMANTIS and visualMANTIS to facilitate the setup of computational experiments via hybridMANTIS. Methods: The visualization tools visualMANTIS and webMANTIS enable the user to control simulation properties through a user interface. In the case of webMANTIS, control via a web browser allows access through mobile devices such as smartphones or tablets. webMANTIS acts as a server back-end and communicates with an NVIDIA GPU computing cluster that can support multiuser environments where users can execute different experiments in parallel. Results: The output consists of point response and pulse-height spectrum, and optical transport statistics generated by hybridMANTIS. The users can download the output images and statistics through a zip file for future reference. In addition, webMANTIS provides a visualization window that displays a few selected optical photon path as they get transported through the detector columns and allows the user to trace the history of the optical photons. Conclusions: The visualization tools visualMANTIS and webMANTIS provide features such as on the fly generation of pulse-height spectra and response functions for microcolumnar x-ray imagers while allowing users to save simulation parameters and results from prior experiments. The graphical interfaces simplify the simulation setup and allow the user to go directly from specifying input parameters to receiving visual feedback for the model predictions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Quantitative analysis of treatment process time and throughput capacity for spot scanning proton therapy

Purpose: To determine the patient throughput and the overall efficiency of the spot scanning system by analyzing treatment time, equipment availability, and maximum daily capacity for the current spot scanning port at Proton Therapy Center Houston and to assess the daily throughput capacity for a hypothetical spot scanning proton therapy center. Methods: At their proton therapy center, the authors have been recording in an electronic medical record system all treatment data, including disease site, number of fields, number of fractions, delivered dose, energy, range, number of spots, and number of layers for every treatment field. The authors analyzed delivery system downtimes that had been recorded for every equipment failure and associated incidents. These data were used to evaluate the patient census, patient distribution as a function of the number of fields and total target volume, and equipment clinical availability. The duration of each treatment session from patient walk-in to patient walk-out of the spot scanning treatment room was measured for 64 patients with head and neck, central nervous system, thoracic, and genitourinary cancers. The authors retrieved data for total target volume and the numbers of layers and spots for all fields from treatment plans for a total of 271 patients (including the above 64 patients). A sensitivity analysis of daily throughput capacity was performed by varying seven parameters in a throughput capacity model. Results: The mean monthly equipment clinical availability for the spot scanning port in April 2012–March 2015 was 98.5%. Approximately 1500 patients had received spot scanning proton therapy as of March 2015. The major disease sites treated in September 2012–August 2014 were the genitourinary system (34%), head and neck (30%), central nervous system (21%), and thorax (14%), with other sites accounting for the remaining 1%. Spot scanning beam delivery time increased with total target volume and accounted for approximately 30%–40% of total treatment time for the total target volumes exceeding 200 cm{sup 3}, which was the case for more than 80% of the patients in this study. When total treatment time was modeled as a function of the number of fields and total target volume, the model overestimated total treatment time by 12% on average, with a standard deviation of 32%. A sensitivity analysis of throughput capacity for a hypothetical four-room spot scanning proton therapy center identified several priority items for improvements in throughput capacity, including operation time, beam delivery time, and patient immobilization and setup time. Conclusions: The spot scanning port at our proton therapy center has operated at a high performance level and has been used to treat a large number of complex cases. Further improvements in efficiency may be feasible in the areas of facility operation, beam delivery, patient immobilization and setup, and optimization of treatment scheduling.

60 APPLIED LIFE SCIENCES↗