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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 901 records · Page 50

2D High‐Entropy Transition Metal Dichalcogenides for Carbon Dioxide Electrocatalysis

Abstract High‐entropy alloys combine multiple principal elements at a near equal fraction to form vast compositional spaces to achieve outstanding functionalities that are absent in alloys with one or two principal elements. Here, the prediction, synthesis, and multiscale characterization of 2D high‐entropy transition metal dichalcogenide (TMDC) alloys with four/five transition metals is reported. Of these, the electrochemical performance of a five‐component alloy with the highest configurational entropy, (MoWVNbTa)S 2 , is investigated for CO 2 conversion to CO, revealing an excellent current density of 0.51 A cm −2 and a turnover frequency of 58.3 s −1 at ≈ −0.8 V versus reversible hydrogen electrode. First‐principles calculations show that the superior CO 2 electroreduction is due to a multi‐site catalysis wherein the atomic‐scale disorder optimizes the rate‐limiting step of CO desorption by facilitating isolated transition metal edge sites with weak CO binding. 2D high‐entropy TMDC alloys provide a materials platform to design superior catalysts for many electrochemical systems.

Cavin, John↗

Sonication-based isolation and enrichment of Chlorella protothecoides chloroplasts for illumina genome sequencing

With the increasing world demand for biofuel, a number of oleaginous algal species are being considered as renewable sources of oil. Chlorella protothecoides Krüger synthesizes triacylglycerols (TAGs) as storage compounds that can be converted into renewable fuel utilizing an anabolic pathway that is poorly understood. The paucity of algal chloroplast genome sequences has been an important constraint to chloroplast transformation and for studying gene expression in TAGs pathways. In this study, the intact chloroplasts were released from algal cells using sonication followed by sucrose gradient centrifugation, resulting in a 2.36-fold enrichment of chloroplasts from C. protothecoides, based on qPCR analysis. The C. protothecoides chloroplast genome (cpDNA) was determined using the Illumina HiSeq 2000 sequencing platform and found to be 84,576 Kb in size (8.57 Kb) in size, with a GC content of 30.8 %. This is the first report of an optimized protocol that uses a sonication step, followed by sucrose gradient centrifugation, to release and enrich intact chloroplasts from a microalga (C. prototheocoides) of sufficient quality to permit chloroplast genome sequencing with high coverage, while minimizing nuclear genome contamination. The approach is expected to guide chloroplast isolation from other oleaginous algal species for a variety of uses that benefit from enrichment of chloroplasts, ranging from biochemical analysis to genomics studies.

09 BIOMASS FUELS↗

Creation of a High-Yield AAV Vector Production Platform in Suspension Cells Using a Design-of-Experiment Approach

Recombinant adeno-associated virus (rAAV) vectors are a leading gene delivery platform, but vector manufacturing remains a challenge. New methods are needed to increase rAAV yields and reduce costs. Past efforts to improve rAAV production have focused on optimizing a single variable at a time, but this approach does not account for the interactions of multiple factors that contribute to vector generation. Here, we utilized a design-of-experiment (DOE) methodology to optimize rAAV production in a HEK293T suspension cell system. We simultaneously varied the transgene, packaging, and helper plasmid ratios, the total DNA concentration, and the cell density to systematically evaluate the impact of each variable across 52 conditions. The results revealed a unique set of parameters with a lower concentration of transgene plasmid, a higher concentration of packaging plasmid, and a higher cell density than previously described protocols. Using this DOE-optimized protocol, we achieved unpurified yields approaching 3 × 10 14 viral genomes (VGs)/L of cell culture. Additionally, we incorporated polyethylene glycol (PEG)-based virus precipitation, pH-mediated protein removal, and affinity chromatography to our downstream processing, enabling average purified yields of >1 × 10 14 VGs/L for rAAV-EGFPs across 13 serotypes and capsid variants.

59 BASIC BIOLOGICAL SCIENCES↗

Graph Algorithms in PGAS: Chapel and UPC++

The Partitioned Global Address Space (PGAS) programming model can be implemented «««< HEAD either with programming language features or with runtime library APIs, each implementation favoring different aspects (e.g., productivity, abstraction, flexibility, or performance). Certain language and runtime features, such as collectives, explicit and asynchronous communication primitives, and constructs facilitating overlap of communication and computation (such as futures and conjoined futures) can enable better performance and scaling for irregular applications, in particular for distributed graph analytics. We compare graph algorithms in one of each of these environments: the Chapel PGAS programming language and the UPC++ PGAS runtime library. We implement algorithms for breadth-first search and triangle counting graph kernels in both environments. We discuss the code in each of the environments, and compile performance data on a Cray Aries and an Infiniband platform. Our results show that the library-based approach of UPC++ currently provides strong performance while Chapel provides a high-level abstraction that, harder to optimize, still provides comparable performance. We argue that various language primitives and runtime library features should be considered in conjunction with each other to design future graph analytics libraries so as to incorporate the best of both worlds.

Distributed Algorithms, Graph algorithms, HPC↗

NOODLES Grid [SWR-25-93]

NOODLES Grid is a real-time visualization server for power system simulation data. It loads precomputed datasets, builds optimized instance renderings, and streams live interactive scenes to connected clients. It is built for high scalability, flexible visualization, and fast interaction. NOODLES is a cross-platform/device/tool protocol for collaborative visualization. NOODLES was Developed at the National Renewable Energy Laboratory (NREL) as a capability of the Insight Center https://www.nrel.gov/computational-science/insight-center.html

Brunhart-Lupo, Nicholas [National Renewable Energy↗

Robust multiresonant nonlocal metasurfaces by rational design

Abstract Dielectric metasurfaces supporting optical resonances have become a promising platform for quantum and nonlinear optics. However, resonant metasurfaces remain limited in their capacity to independently control the behavior of many distinct resonances despite efforts in computational optimization and inverse design. In this work, we overcome longstanding limitations by introducing a generalized rational design paradigm based on symmetry. Specifically, we use symmetry-broken metasurfaces with periodic “quadromer” lattices comprised of four nanostructures per unit cell to enable extensive control of multiple optical resonances. The rationally designed metasurfaces are readily fabricable, and we experimentally demonstrate metasurfaces that support up to four high Q-factor resonances with deliberately chosen free-space polarizations, spectral separations, and mode profiles. Our design paradigm may unlock new applications for multiresonant metasurfaces in quantum and nonlinear optics, optical sensing, and augmented reality displays.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

An Analytical Technology Platform to Identify Symbiotic Interactions Between PGPR and Root Microbiome Members from Biofuel Feedstocks

The goal of this STTR project was to establish a commericially-viable technology platform that can be used to develop formulations of plant growth promoting rhizobacteria (PGPR) that can be used as biofertilizers for improved production of woody biomass. The platform has been designed to screen thousands of different formulations of microorganisms in search for those formulations that best support the growth and survival of PGPR species. The focus of the Phase I project was to provide the existing technology with new capabilities that define its commerical pathway. These goals were to (1) adapt the existing platform for use with Populus isolates and (2) developing a highly-automated image analysis software tool that can rapidly screen large data sets to statistically identify optimized biofertilizer formulations. The project has produced a software routine for this screening and identification need, and has generated preliminary data for use of this approach to identify symbiotic PGPR communities that may be useful for promoting Populus growth.

09 BIOMASS FUELS↗

A Zoom-in Analysis of I/O Logs to Detect Root Causes of I/O Performance Bottlenecks

Scientific applications frequently spend a large fraction of their execution time in reading and writing data on parallel file systems. Identifying these I/O performance bottlenecks and attributing root causes are critical steps toward devising optimization strategies. Several existing studies analyze I/O logs of a set of benchmarks or applications that were run with controlled behaviors. However, there is still a lack of general approach that systematically identifies I/O performance bottlenecks for applications running "in the wild" on production systems. In this study, we have developed an analysis approach of "zooming in" from platform-wide to application-wide to job-level I/O logs for identifying I/O bottlenecks in arbitrary scientific applications. We analyze the logs collected on a Cray XC40 system in production over a two-month period. This study results in several insights for application developers to use in optimizing I/O behavior.

Wang, Teng↗

Automatic translation of MPI source into a latency-tolerant, data-driven form

Hiding communication behind useful computation is an important performance programming technique but remains an inscrutable programming exercise even for the expert. We present Bamboo, a code transformation framework that can realize communication overlap in applications written in MPI without the need to intrusively modify the source code. Bamboo reformulates MPI source into the form of a task dependency graph that expresses a partial ordering among tasks, enabling the program to execute in a data-driven fashion under the control of an external runtime system. Experimental results demonstrate that Bamboo significantly reduces communication delays while requiring only modest amounts of programmer annotation for a variety of applications and platforms, including those employing co-processors and accelerators. Moreover, Bamboo's performance meets or exceeds that of labor-intensive hand coding. The translator is more than a means of hiding communication costs automatically; it demonstrates the utility of semantic level optimization against a wellknown library.

Communication-computation↗

Distributed Grid Control of Flexible Loads and DERs for Optimized Provision of Synthetic Regulating Reserves

Over the course of this project, we have successfully de-risked our distributed microgrid control architecture by tightly integrating its associated control algorithms into a unified software library, installing the software library on several industrial-grade target hardware platforms, and validating the performance of the resulting microgrid controller in a real-life microgrid. Upon completion of the project, we demonstrated that our distributed control architecture is resilient against (i) failures in control devices, (ii) unreliable communication links, (iii) delays in transmitted data, and (iv) imperfect knowledge of the number of (and state of) generation and load assets in the microgrid. In this final report, we present results from all the milestones that were accomplished over the course of this project.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Wearable Sweat Band for Noninvasive Levodopa Monitoring

Levodopa is the standard medication clinically prescribed to patients afflicted with Parkinson's disease. In particular, the monitoring and optimization of levodopa dosage are critical to mitigate the onset of undesired fluctuations in the patients' physical and emotional conditions such as speech function, motor behavior, and mood stability. The traditional approach to optimize levodopa dosage involves evaluating the subjects' motor function, which has many shortcomings due to its subjective and limited quantifiable nature. In this paper, we present a wearable sweat band on a nanodendritic platform that quantitatively monitors levodopa dynamics in the body. Both stationary iontophoretic induction and physical exercise are utilized as our methods of sweat extraction. The sweat band measures real-time pharmacokinetic profiles of levodopa to track the dynamic response of the drug metabolism. We demonstrated the sweat band's functionalities on multiple subjects with implications toward the systematic administering of levodopa and routine management of Parkinson's disease.

47 OTHER INSTRUMENTATION↗

Transient Efficiency, Flexibility, and Reliability Optimization of Coal-Fired Power Plants - Final Program Review

This program developed an advanced model-based monitoring and model-predictive control algorithms for a coal fired power plant (CFPP), and deployed these algorithms in a real-time platform to demonstrate performance benefits for transient flexibility and plant operation efficiency. More specifically, the objectives were successfully achieved through a combination of (i) developing a high-fidelity transient plant model in Apros, which was used as a high-fidelity plant simulation between $100-50\% TMCR$ where TMCR denotes the turbine maximum continuous rating, i.e., baseload, (ii) developing a very fast physics-based reduced-order model (ROM) of the plant, which ran more than $100\times$ faster than real-time, enabling its use as real-time embedded model for model-based estimation (MBE) and model predictive control (MPC) (iii) implementing a real-time MBE based on ROM using a robust unscented Kalman filter (UKF) to continuously tune the ROM to match the measurements from high-fidelity Apros plant model despite significant plant-model mismatch, and thus, obtain a Digital Twin of the plant (iv) designing and implementing a real-time MPC with dual objectives of transient plant load tracking with high ramp rates and minimizing coal consumption, i.e., improving plant efficiency in the baseload-partload operation range of $100-50\% TMCR$. Each key element above was developed and tested individually, and has been reported in corresponding Topical Reports. Finally, all the individual elements were integrated in an overall closed-loop system, that was successfully tested in desktop Simulink test harness simulations with ROM or high-fidelity model as the plant. Thereafter, the Simulink implementation was used to auto-generate C-code and deploy as real-time Docker microservice containers in Linux, and validate that they can run in real-time in the hardware-in-the loop (HIL) setup and produce the same results as in Simulink. The results of the integrated simulation tests in Simulink as well as the real-time HIL deployment are documented in this final report, showing good load tracking for load ramps at $3-4\%/min$ ramp rates, and achieving up to $5.5\%$ reduction in coal relative to baseline operation at $50\% TMCR$ load. The desktop and HIL simulations show successful performance of the overall model based estimation and control solution and achieve the key objectives of the program for flexible, efficient and reliable operation of sub-critical coal fired power plants.

20 FOSSIL-FUELED POWER PLANTS↗

Application and Removal of Strippable Coatings via Remote Platform - 13133

Florida International University's (FIU's) Applied Research Center is currently supporting the Department of Energy (DOE) Environmental Management Office of D and D and Facility Engineering program. FIU is supporting DOE's initiative to improve safety, reduce technical risks, and limit uncertainty within D and D operations by identifying technologies suitable to meet specific facility D and D requirements, assessing the readiness of those technologies for field deployment, and conducting feasibility studies and technology demonstrations of selected technologies and working with technology vendors to optimize the design of their current technologies to accomplish dangerous and demanding tasks during D and D operations. To meet one identified technology gap challenge for a technology to remotely apply strippable coatings, fixatives and decontamination gels, FIU identified and performed an initial demonstration of an innovative remote fixative sprayer platform from International Climbing Machines (ICM). The selected technology was demonstrated spraying fixative products at the hot cell mockup facility at the Applied Research Center at FIU in November 2008 under cold (non-radioactive) conditions. The remotely controlled platform was remotely operated and entered the facility and sprayed a fixative onto horizontal and vertical surfaces. Based on the initial FIU demonstration and the specific technical requirements identified at the DOE facilities, a follow-up demonstration was expanded to include strippable coatings and a decontamination gel, which was demonstrated in June 2010 at the ICM facility in Ithaca, NY. This second technology evaluation documented the ability of the remote system to spray the selected products on vertical stainless steel and concrete surfaces to a height of 3 meters (10 feet) and to achieve sufficient coverage and product thickness to promote the ability to peel/remove the strippable coatings and decontamination gel. The next challenge was to determine if a remote platform could be used to remove the strippable coatings and decontamination gels. In 2012, FIU worked with the technology provider, ICM, to conduct feasibility and trade studies to identify the requirements for the remote removal of strippable coatings or decontamination gels using the existing remote controlled platform. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

TU-CD-304-01: FEATURED PRESENTATION and BEST IN PHYSICS (THERAPY): Trajectory Modulated Arc Therapy: Development of Novel Arc Delivery Techniques Integrating Dynamic Table Motion for Extended Volume Treatments

Purpose: Integration of coordinated robotic table motion with inversely-planned arc delivery has the potential to resolve table-top delivery limitations of large-field treatments such as Total Body Irradiation (TBI), Total Lymphoid Irradiation (TLI), and Cranial-Spinal Irradiation (CSI). We formulate the foundation for Trajectory Modulated Arc Therapy (TMAT), and using Varian Developer Mode capabilities, experimentally investigate its practical implementation for such techniques. Methods: A MATLAB algorithm was developed for inverse planning optimization of the table motion, MLC positions, and gantry motion under extended-SSD geometry. To maximize the effective field size, delivery trajectories for TMAT TBI were formed with the table rotated at 270° IEC and dropped vertically to 152.5cm SSD. Preliminary testing of algorithm parameters was done through retrospective planning analysis. Robotic delivery was programmed using custom XML scripting on the TrueBeam Developer Mode platform. Final dose was calculated using the Eclipse AAA algorithm. Initial verification of delivery accuracy was measured using OSLDs on a solid water phantom of varying thickness. Results: A comparison of DVH curves demonstrated that dynamic couch motion irradiation was sufficiently approximated by static control points spaced in intervals of less than 2cm. Optimized MLC motion decreased the average lung dose to 68.5% of the prescription dose. The programmed irradiation integrating coordinated table motion was deliverable on a TrueBeam STx linac in 6.7 min. With the couch translating under an open 10cmx20cm field angled at 10°, OSLD measurements along the midline of a solid water phantom at depths of 3, 5, and 9cm were within 3% of the TPS AAA algorithm with an average deviation of 1.2%. Conclusion: A treatment planning and delivery system for Trajectory Modulated Arc Therapy of extended volumes has been established and experimentally demonstrated for TBI. Extension to other treatment techniques such as TLI and CSI is readily achievable through the developed platform. Grant Funding by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

A coarse-grained simulation model for colloidal self-assembly via explicit mobile binders

Colloidal particles with mobile binding molecules constitute a powerful platform for probing the physics of self-assembly. Binding molecules are free to diffuse and rearrange on the surface, giving rise to spontaneous control over the number of droplet–droplet bonds, i.e., valence, as a function of the concentration of binders. This type of valence control has been realized experimentally by tuning the interaction strength between DNA-coated emulsion droplets. Optimizing for valence two yields droplet polymer chains, termed ‘colloidomers’, which have recently been used to probe the physics of folding. To understand the underlying self-assembly mechanisms, here we present a coarse-grained molecular dynamics (CGMD) model to study the self-assembly of this class of systems using explicit representations of mobile binding sites. Further, we explore how valence of assembled structures can be tuned through kinetic control in the strong binding limit. More specifically, we optimize experimental control parameters to obtain the highest yield of long linear colloidomer chains. Subsequently tuning the dynamics of binding and unbinding via a temperature-dependent model allows us to observe a heptamer chain collapse into all possible rigid structures, in good agreement with recent folding experiments. Our CGMD platform and dynamic bonding model (implemented as an open-source custom plugin to HOOMD-Blue) reveal the molecular features governing the binding patch size and valence control, and opens the study of pathways in colloidomer folding. This model can therefore guide programmable design in experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SU-F-T-335: Piecewise Uniform Dose Prescription and Optimization Based On PET/CT Images

Purpose: In intensity modulated radiation therapy (IMRT), the tumor target volume is given a uniform dose prescription, which does not consider the heterogeneous characteristics of tumor such as hypoxia, clonogen density, radiosensitivity, tumor proliferation rate and so on. Our goal is to develop a nonuniform target dose prescription method which can spare organs at risk (OARs) better and does not decrease the tumor control probability (TCP). Methods: We propose a piecewise uniform dose prescription (PUDP) based on PET/CT images of tumor. First, we propose to delineate biological target volumes (BTV) and sub-biological target volumes (sub-BTVs) by our Hierarchical Mumford-Shah Vector Model based on PET/CT images of tumor. Then, in order to spare OARs better, we make the BTV mean dose minimized while restrict the TCP to a constant. So, we can get a general formula for determining an optimal dose prescription based on a linearquadratic model (LQ). However, this dose prescription is high heterogeneous, it is very difficult to deliver by IMRT. Therefore we propose to use the equivalent uniform dose (EUD) in each sub-BTV as its final dose prescription, which makes a PUDP for the BTV. Results: We have evaluated the IMRT planning of a patient with nasopharyngeal carcinoma respectively using PUDP and UDP. The results show that the highest and mean doses inside brain stem are 48.425Gy and 19.151Gy respectively when the PUDP is used for IMRT planning, while they are 52.975Gy and 20.0776Gy respectively when the UDP is used. Both of the resulting TCPs(0.9245, 0.9674) are higher than the theoretical TCP(0.8739), when 70Gy is delivered to the BTV. Conclusion: Comparing with the UDP, the PUDP can spare the OARs better while the resulting TCP by PUDP is not significantly lower than by UDP. This work was supported in part by National Natural Science Foundation of China undergrant no.61271382 and by the foundation for construction of scientific project platform forthe cancer hospital of Hunan province.

60 APPLIED LIFE SCIENCES↗

Simulating many-engine spacecraft: Exceeding 1 quadrillion degrees of freedom via information geometric regularization

We present an optimized implementation of the recently proposed information geometric regularization (IGR) for unprecedented scale simulation of compressible fluid flows applied to multi-engine spacecraft boosters. We improve upon state-of-the-art computational fluid dynamics (CFD) techniques in terms of computational cost, memory footprint, and energy-to-solution metrics. Unified memory on coupled CPU–GPU or APU platforms increases problem size with negligible overhead. Mixed half/single-precision storage and computation are used on well-conditioned numerics. We simulate flow at 200 trillion grid points and 1 quadrillion degrees of freedom, exceeding the current record by a factor of 20. A factor of 4 wall-time speedup is achieved over optimized baselines. Ideal weak scaling is observed on OLCF Frontier, LLNL El Capitan, and CSCS Alps using the full systems. Strong scaling is near ideal at extreme conditions, including 80% efficiency on CSCS Alps with an 8 node baseline and stretching to the full system.

Wilfong, Benjamin [Georgia Institute of Technology↗

Rapid discovery and evolution of nanosensors containing fluorogenic amino acids

Binding-activated optical sensors are powerful tools for imaging, diagnostics, and biomolecular sensing. However, biosensor discovery is slow and requires tedious steps in rational design, screening, and characterization. Here we report on a platform that streamlines biosensor discovery and unlocks directed nanosensor evolution through genetically encodable fluorogenic amino acids (FgAAs). Building on the classical knowledge-based semisynthetic approach, we engineer ~15 kDa nanosensors that recognize specific proteins, peptides, and small molecules with up to 100-fold fluorescence increases and subsecond kinetics, allowing real-time and wash-free target sensing and live-cell bioimaging. An optimized genetic code expansion chemistry with FgAAs further enables rapid (~3 h) ribosomal nanosensor discovery via the cell-free translation of hundreds of candidates in parallel and directed nanosensor evolution with improved variant-specific sensitivities (up to ~250-fold) for SARS-CoV-2 antigens. Altogether, this platform could accelerate the discovery of fluorogenic nanosensors and pave the way to modify proteins with other non-standard functionalities for diverse applications.

Biosensors↗