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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A light-induced phononic symmetry switch and giant dissipationless topological photocurrent in ZrTe 5

Dissipationless currents from topologically protected states are promising for disorder-tolerant electronics and quantum computation. In this work, we photogenerate giant anisotropic terahertz nonlinear currents with vanishing scattering, driven by laser-induced coherent phonons of broken inversion symmetry in a centrosymmetric Dirac material ZrTe 5 . Our work suggests that this phononic terahertz symmetry switching leads to formation of Weyl points, whose chirality manifests in a transverse, helicity-dependent current, orthogonal to the dynamical inversion symmetry breaking axis, via circular photogalvanic effect. The temperature-dependent topological photocurrent exhibits several distinct features: Berry curvature dominance, particle–hole reversal near conical points and chirality protection that is responsible for an exceptional ballistic transport length of ~10 μm. These results, together with first-principles modelling, indicate two pairs of Weyl points dynamically created by B 1u phonons of broken inversion symmetry. Such phononic terahertz control breaks ground for coherent manipulation of Weyl nodes and robust quantum transport without application of static electric or magnetic fields.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Validating the galaxy and quasar catalog-level blinding scheme for the DESI 2024 analysis

In the era of precision cosmology, ensuring the integrity of data analysis through blinding techniques is paramount — a challenge particularly relevant for the Dark Energy Spectroscopic Instrument (DESI). DESI represents a monumental effort to map the cosmic web, with the goal to measure the redshifts of tens of millions of galaxies and quasars. Given the data volume and the impact of the findings, the potential for confirmation bias poses a significant challenge. To address this, we implement and validate a comprehensive blind analysis strategy for DESI Data Release 1 (DR1), tailored to the specific observables DESI is most sensitive to: Baryonic Acoustic Oscillations (BAO), Redshift-Space Distortion (RSD) and primordial non-Gaussianities (PNG). We carry out the blinding at the catalog level, implementing shifts in the redshifts of the observed galaxies to blind for BAO and RSD signals and weights to blind for PNG through a scale-dependent bias. We validate the blinding technique on mocks as well as on data by applying a second blinding layer to perform a series of sanity checks; the latter allows probing complexities in real data not captured in mocks. We find that the blinding strategy alters the data vector in a controlled way, and the BAO and RSD analysis choices are robust to blinding. The successful validation of the blinding strategy paves the way for the unblinded DESI DR1 analysis, alongside future blind analyses with DESI and other surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

High-Precision Zinc Isotopic Measurement of Certified Reference Materials Relevant to the Environmental, Earth, Planetary and Biomedical Sciences

The zinc (Zn) stable isotope system has emerged as a powerful tool for investigating natural and anthropogenic processes of interest to disciplines extending from the Earth and planetary sciences to biomedical research. In nature, Zn isotopes typically fractionate ( 66 Zn/ 64 Zn) within the range of –1 and +1 permil (‰), and however, analytical limitations restrict the application of the Zn isotope system. Specifically, there is a lack of well-characterised matrix-matched reference materials covering most Zn isotope applications that are essential for validating laboratory performance, particularly given the contamination prone nature of Zn. Furthermore, the increasing demand for analysis of size-limited materials and sample types displaying small, sub-permil level Zn isotope variations requires improvements in measurement procedures. To address these limitations, the δ 66 Zn values of two pure Zn solutions and eighteen reference materials including the previously uncharacterised RGM-2, BCR-279, DOLT-4, DOLT-5, NASS-7, SBC-1, SGR-1b, MESS-3 and HISS-1, and the understudied QLO-1, SDC-1, BCR-414, NASS-6 and COQ-1 materials are reported. Furthermore, a 70 Zn- 67 Zn double-spike design has been implemented that routinely achieves intermediate measurement precision better than ± 0.02‰. This represents at least a two-fold improvement when compared with other double-spike designs, providing a robust platform of δ 66 Zn values required for quality control procedures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

kynema-fmb [SWR-23-07]

Kynema-FMB (FKA: Kynema) is an open-source performance portable flexible multibody (FMB) dynamics solver designed for time-domain simulations. While originally tailored for wind turbine structural dynamics, the formulation and implementation are those of a general flexible-multidbody dynamics solver that can readily be applied to a wide range of systems. Kynema was designed with a narrow focus, namely to provide a lightweight, fast, accurate FMD solver for coupling to computational-fluid-dynamics (CFD) codes, especially the CFD codes in the Kynema suite, for fluid-structure-interaction (FSI) simulations. Kynema-FMB is equipped to model systems that can be represented as a collection of beams and rigid bodies that are connected through constraints. Degrees of freedom are defined in the inertial/global frame of reference and include displacements and rotations (formally as rotation matrices, but stored as quaternions). The underlying formulation is built on a Lie-group time integrator designed for index-3 differential-algebraic equations, which is second-order accurate in time (Bruls et al., 2012). Beam models are based on geometrically exact beam theory and are discretized as high-order spectral finite elements similar to those in BeamDyn (Wang et al., 2017). The governing equations for a FMD system like a wind turbine constitute a highly nonlinear system of constrained partial-differential equations. Kynema-FMB uses analytical Jacobians in the nonlinear-system solves in each time step. Linear systems use sparse storage and several third-party sparse-linear-system solvers are enabled. Ill conditioning of linear systems is mitigated with preconditioning described in Bottasso et al, 2008. Kynema-FMB is integrated with a simple open-source controller (ROSCO). There is an application programming interface (API) for coupling to geometry-resolved CFD (like that in Sharma et al., 2023) and actuator-force CFD (like that in Kuhn et al., 2025). In the latter, for actuator-line models, Kynema-FMB includes an internal blade-element solver that depends on user-provided lookup tables for coefficients of lift and drag, i.e., aerodynamic polars. Kynema-FMB is written in C++ and leverages Kokkos and Kokkos-Kernels (KokkosEcosystem) as its performance portability layer enabling simulations on both CPU and GPU systems. The repository is equipped with extensive automated testing at the unit and regression/system levels. The following describes the high-level development objectives conceived for Kynema: *Kynema will follow modern software development best practices, including test-driven development (TDD), version control, hierarchical automated testing, and continuous integration (CI) for a robust development environment. *The core data structures are memory efficient and enable vectorization and parallelization at multiple levels. *Data structures are data-oriented to exploit methods for accelerated computing including high utilization of chip resources (e.g., single instruction multiple data (SIMD) instruction sets) and parallelization using GP-GPUs. *The computational algorithms incorporate robust open-source libraries for mathematical operations, resource allocation, and data management. *The API design considers multiple stakeholder needs and ensure integration with existing and future ecosystems for data science, machine learning, and AI. *Kynema-FMB is written in modern C++ and leverages Kokkos as its performance-portability library with inspiration from the kynema stack.

Sprague, MichaelA.↗
DOE OSTI2019

De novo Nanopore read quality improvement using deep learning

BACKGROUND: Long read sequencing technologies such as Oxford Nanopore can greatly decrease the complexity of de novo genome assembly and large structural variation identification. Currently Nanopore reads have high error rates, and the errors often cluster into low-quality segments within the reads. The limited sensitivity of existing read-based error correction methods can cause large-scale mis-assemblies in the assembled genomes, motivating further innovation in this area. RESULTS: Here we developed a Convolutional Neural Network (CNN) based method, called MiniScrub, for identification and subsequent "scrubbing" (removal) of low-quality Nanopore read segments to minimize their interference in downstream assembly process. MiniScrub first generates read-to-read overlaps via MiniMap2, then encodes the overlaps into images, and finally builds CNN models to predict low-quality segments. Applying MiniScrub to real world control datasets under several different parameters, we show that it robustly improves read quality, and improves read error correction in the metagenome setting. Compared to raw reads, de novo genome assembly with scrubbed reads produces many fewer mis-assemblies and large indel errors. CONCLUSIONS: MiniScrub is able to robustly improve read quality of Oxford Nanopore reads, especially in the metagenome setting, making it useful for downstream applications such as de novo assembly. We propose MiniScrub as a tool for preprocessing Nanopore reads for downstream analyses. MiniScrub is open-source software and is available at https://bitbucket.org/berkeleylab/jgi-miniscrub .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Estimating the Effects of Soil Remediation on Children’s Blood Lead near a Former Lead Smelter in Omaha, Nebraska, USA

Lead exposures from legacy sources threaten children’s health. Soil in Omaha, Nebraska, was contaminated by emissions from a lead smelter and refinery. The U.S. Environmental Protection Agency excavated and replaced contaminated soil at the Omaha Lead Superfund Site between 1999 and 2016. The goal of this study was to assess the association of soil lead level (SLL) and soil remediation status with blood lead levels (BLLs) in children living near or on the site. We linked information on SLL at residential properties with children’s BLLs and assigned remediation status to children’s BLL measurements based on whether their measurements occurred during residence at remediated or unremediated properties. We examined the association of SLL and remediation status with elevated BLL (EBLL). We distinguished the roles of temporal trend and the intervention with time-by-intervention-status interaction contrasts. All analyses estimated odds ratios (ORs) with a generalized estimating equations approach to ensure robustness under the complex correlations among BLL measurements. All analyses controlled for relevant covariates including children’s characteristics. EBLL (> 5 μg/dL ) was associated with both residential SLL [e.g., OR=2.00; 95% confidence interval (CI): 1.83, 2.19; > 400–800 vs. ≤ 200 ppm] and neighborhood SLL [e.g., OR=1.85 (95% CI: 1.62, 2.11; > 400–800 vs. ≤ 200 ppm)] before remediation but only with neighborhood SLL after remediation. The odds of EBLL were higher before remediation [OR 1.52 (95% CI: 1.34, 1.72)]. Similarly, EBLL was positively associated with preremediation status in our interaction analysis [interaction OR=1.18 (95%CI: 1.02, 1.37)]. Residential and neighborhood SLLs were important predictors of EBLLs in children residing near or on this Superfund site. Neighborhood SLL remained a strong predictor following remediation. Our data analyses showed the benefit of soil remediation. Results from the interaction analyses should be interpreted cautiously due to imperfect correspondence of remediation times between remediation and comparison groups. https://doi.org/10.1289/EHP8657

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Intermetallic PtCo Catalysts with Enhanced Performance and Stability [Slides]

Pt-based catalysts need systematic modifications to be adapted to different applications (LDV or HDV). L1 0 -CoPt particles have been demonstrated as highly active and durable cathode materials for fuel cells. Colloidal synthesis can generate catalysts with highly uniform particles size but the removal of surfactants is challenging. Acid leaching warrants a Pt shell with certain thickness, which mitigates the Co leaching. Controlling the size of L1 0 -CoPt particles is a robust method to alter their catalytic behaviours and tailor the function of catalysts. Modifying the carbon features (e.g. porosity and graphitization) is an effective method to regulate the performance and stability of catalysts to adapt the catalysts to different applications.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

Technical Report for Bayesian Optimization and Reinforcement Learning for Beam Polarization Increase in the BNL Hadron Injectors

This project developed and evaluated physics-informed Bayesian learning and machine learning (ML)-based optimization methods for improving beam polarization preservation in the BNL hadron injector chain. The work focused on uncertainty-aware digital twin modeling, Bayesian calibration of accelerator simulations using beam measurements, and data-efficient optimization strategies including Bayesian optimization and reinforcement learning. These methods were applied to injector tuning and RF control problems in realistic accelerator settings to support improved operational robustness and readiness for RHIC operations and future Electron–Ion Collider facilities. No subject inventions were disclosed under this award.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Effect of Polymer Removal on the Morphology and Phase of the Nanoparticles in All-Inorganic Heterostructures Synthesized via Two-Step Polymer Infiltration

Polymer templates play an essential role in the robust infiltration-based synthesis of functional multicomponent heterostructures with controlled structure, porosity, and composition. Such heterostructures are be used as hybrid organic–inorganic composites or as all-inorganic systems once the polymer templates are removed. Using iron oxide/alumina heterostructures formed by two-step infiltration of polystyrene-block-polyvinyl pyridine block copolymer with iron and aluminum precursors from the solution and vapor-phases, respectively, we show that the phase and morphology of iron oxide nanoparticles dramatically depend on the approach used to remove the polymer. We demonstrate that thermal and plasma oxidative treatments result in iron oxide nanoparticles with either solid or hollow morphologies, respectively, that lead to different magnetic properties of the resulting materials. Our study extends the boundaries of structure manipulations in multicomponent heterostructures synthesized using polymer infiltration synthesis, and hence their properties.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Self-Cleaning Highly Porous TiO 2 Coating Designed by Swelling-Assisted Sequential Infiltration Synthesis (SIS) of a Block Copolymer Template

Photocatalytic self-cleaning coatings with a high surface area are important for a wide range of applications, including optical coatings, solar panels, mirrors, etc. Here, we designed a highly porous TiO 2 coating with photoinduced self-cleaning characteristics and very high hydrophilicity. This was achieved using the swelling-assisted sequential infiltration synthesis (SIS) of a block copolymer (BCP) template, which was followed by polymer removal via oxidative thermal annealing. The quartz crystal microbalance (QCM) was employed to optimize the infiltration process by estimating the mass of material infiltrated into the polymer template as a function of the number of SIS cycles. This adopted swelling-assisted SIS approach resulted in a smooth uniform TiO 2 film with an interconnected network of pores. The synthesized film exhibited good crystallinity in the anatase phase. The resulting nanoporous TiO 2 coatings were tested for their functional characteristics. Exposure to UV irradiation for 1 h induced an improvement in the hydrophilicity of coatings with wetting angle reducing to unmeasurable values upon contact with water droplets. Furthermore, their self-cleaning characteristics were tested by measuring the photocatalytic degradation of methylene blue (MB). The synthesized porous TiO 2 nanostructures displayed promising photocatalytic activity, demonstrating the degradation of approximately 92% of MB after 180 min under ultraviolet (UV) light irradiation. Thus, the level of performance was comparable to the photoactivity of commercial anatase TiO 2 nanoparticles of the same quantity. Our results highlight a new robust approach for designing hydrophilic self-cleaning coatings with controlled porosity and composition.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗
DOE OSTI2023

Optimal mitigation and control over power system dynamics for stochastic grid resilience

Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the western system coordinating council 9-bus test system using synthetic multi-device outage scenarios.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Tailoring electrocatalytic activity of in situ crafted perovskite oxide nanocrystals via size and dopant control

Significance The ability to scrutinize the correlation of dimension, composition, and dopant to electrocatalytic performance renders the development of highly active electrocatalysts. This work reports a general and robust strategy for crafting uniform perovskite oxide nanoparticles (i.e., BaTiO 3 and La- and Co-doped BaTiO 3 ) with controlled sizes and dopant compositions by employing amphiphilic star-like diblock copolymers as nanoreactors. Their size- and dopant-dependent oxygen reduction reaction (ORR) performances are unveiled. Particularly, La- and Co-doped BaTiO 3 nanoparticles exhibit markedly improved ORR activities over the pristine counterparts due to reduced free energy barrier of ORR and increased conductivity as substantiated by density functional theory. The nanoreactor strategy could be conveniently extended to yield various functional nanomaterials of interest with tailored sizes and compositions for electrocatalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Unified Universal Control and Coordination of Inverter-Based Resources, and Validation for a PV + Battery Hybrid Plant

As renewable energy deployment grows, hybrid power plants (HPPs) combining photovoltaic (PV) and battery systems must evolve to offer both energy and grid stability services. These systems typically include a mix of grid-following (GFL) and grid-forming (GFM) inverters, presenting unique coordination and control challenges. This Department of Energy–funded project developed and validated a Unified Universal Control and Coordination (UUCC) framework for such PV + battery hybrid plants, enabling seamless and stable operation, including ultrafast black start, autonomous synchronization, and robust frequency and voltage regulation, under different grid conditions. The project significantly advanced the understanding of inverter-based resource (IBR) control by developing and validating three complementary system-level approaches for hybrid GFL/GFM operation: 1. A combined Virtual Resistance (VR)-based GFL and Virtual Oscillator Control (VOC)-based GFM method, where each inverter type is governed by a specialized control strategy. Together, these achieve stable, fast-response coordination, eliminating inrush current and enabling smooth black start and grid synchronization across a wide range of grid strengths. 2. A Deadbeat-based UUCC strategy, which uses discrete-time, switching-cycle-level control for both GFL and GFM inverters. This approach replaces traditional PI/PLL control with a control parameter-free, high-bandwidth framework that supports stable LVRT and instantaneous synchronization under all conditions. 3. A benchmark comparison with Siemens’ commercial GFM microgrid controller, which provided a fast baseline platform. The commercial approach decoupled v & f control was implemented on a commercial microgrid controller.The baseline commercial benchmark helped highlight superior transient response and black start performance offered by the deadbeat and VOC approaches. These technical contributions offer substantial improvements over conventional inverter control schemes, which often rely on slow phase-locked loop (PLL)-based synchronization, require careful control parameters tuning, and prone to unstable in weak grids with GFL inverters and in stiff grid with GFM inverters therefore challenging for hybrid GFL+GFM under all grid conditions. The deadbeat-based UUCC framework enables simpler, faster, and more robust operation of hybrid IBR systems using wide-bandgap (WBG) devices such as SiC power semiconductors. The rapid expansion of hybrid distributed energy resources (DERs), including residential and commercial PV-BESS installations such as Tesla Powerwall, PV with vehicle-to-grid (V2G) capability, and other integrated configurations, presents complex operational challenges for medium-voltage radial distribution feeders. These networks are subject to frequent disturbances such as faults, switching operations, rapid reclosing sequences, and feeder reconfigurations, all of which introduce dynamic stress on IBRs. In addition, planned feeder segmentation and deliberate islanding for resilience will require DERs that can autonomously perform blackstart, establish voltage and frequency references, and resynchronize with the main grid. The advanced deadbeat-based UUCC control and blackstart functionalities developed in this project directly address these requirements, enabling decentralized and autonomous operation of inverter-dominated DERs in distribution systems under a wide range of fault and reconfiguration scenarios. From a public benefit perspective, these innovations enable more reliable and cost-effective integration of renewable energy into distribution networks. The ability to autonomously black start and stabilize grids under varying grid conditions support accelerates recovery from outages and support decentralized resilient energy systems. By reducing system complexity and improving performance, this project lays critical groundwork for future inverter-dominated power grids that are clean, reliable, and accessible to all.

14 SOLAR ENERGY↗
DOE OSTI2022

The LIBRA Experiment: Investigating Robust Tritium Accountancy in Molten FLiBe Exposed to a D-T Fusion Neutron Spectrum

The Liquid Immersion Blanket: Robust Accountancy (LIBRA) experiment will be a first-of-a-kind experiment to explore and develop the liquid immersion blanket (LIB) concept. The LIB is a radically simple molten–LiF-BeF2 (FLiBe)–salt tritium breeding blanket for deuterium-tritium (D-T)–fueled fusion power plants (FPPs) achieving a high tritium breeding ratio (TBR) in neutronics models. However, tritium breeding in FLiBe is inherently difficult to study experimentally. As a result, the coupled issues of FLiBe radiochemistry and tritium (T) transport are poorly understood. LIBRA approaches this challenge by simulating an FPP blanket environment using a D-T neutron generator and ≈ 1000 kg of FLiBe. LIBRA will investigate T breeding, containment, and extraction, coupled with FLiBe redox control and radiochemistry. The primary goal of LIBRA is to demonstrate robust T accountancy in blanket prototypical conditions. Here, T accountancy encompasses accurate predictions of T breeding in the FLiBe; detection and measurement of all T bred in LIBRA; and speciation of the T extracted from the FLiBe. Initial neutronics simulations of LIBRA indicate that a global TBR of ~ 1 is possible, where the TBR is defined as the number of tritons bred and extracted from FLiBe relative to the number of neutrons produced by D-T fusion reactions in the neutron generator. In this paper, we present the LIBRA concept and its scientific goals in the context of T breeding experiments. We also consider the potential impact of the LIB on the future fusion power industry, motivating further development of FLiBe-based T breeding research activities such as LIBRA.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Salt Vessel-Sample Generator Interface

The goal of the salt sampling program at Argonne is to develop and deploy automated molten salt sampling approaches for interfacing relevant unit operations with salt analysis to improve the timeliness and accuracy of sampling-based accountancy measurements. One technology under development is a vacuum sampler loop module. In this system, molten salt is drawn from a process vessel through a heated sampling line and into a charge vessel. Next, one or more samples are split from the volume in the charge vessel and the remaining salt is returned to the process. The vacuum sampler loop module is being developed to interface with other sample processing and analysis modules to enable rapid at-line sample characterization. The main purpose of the vacuum sampling loop module is to enable the collection of samples that are more representative of the bulk salt by replacing traditional point samplers (i.e., dip probes) with a sampling approach that captures a larger cross section of salt. Additionally, the vacuum sampling approach eliminates the risk of dross contamination of samples and avoids the use of moving parts in the salt. Two methods of interfacing the vacuum sampling loop with a precision pneumatic sample generator were investigated in FY21. This report covers the testing of fluidic coupling between the two modules. Two iterations of the fluidically coupled modules were tested. The first iteration system coupled the two modules using a freeze valve to seal the vacuum sampler during filling and to control flow into the pneumatic sample generator. While this integrated system functioned as intended, some changes were implemented to make the system more robust and better suited to remote deployment. Specifically, the system was made to be more modular and active control of the vacuum filling operation was replaced with a passive control mechanism. For passive filling, the salt charge vessel was vented to a small gas tank that was at negative pressure, causing salt to be drawn into the vessel until the force of the fluid head was in equilibrium with the gas pressure. The passive control system performed well and will be used in future iterations. Another change in the second system was a newly configured pneumatic sample generator in which sample ejection occurred through a hole in the reservoir’s stainless-steel side wall instead of through a non-wetted sapphire orifice on the bottom. This alternate configuration may be better suited for near-process deployment because it enables on-line orifice maintenance and an orifice bypass drain back to the process. A third change in the second iteration system was the transition to a two-chamber charge vessel which split off a fraction of the sampled salt as a liquid aliquot. The goal was to create a buffer mechanism that would allow reproducible aliquoting of samples, independently of variability in the charge vessel fill height. While the two-chamber design was functional, the sample size reproducibility was below target values. To improve reproducibility and overcome many of the impediments to remote deployment of the vacuum sampling loop module, separate work was conducted to replace the two-chamber liquid aliquoting mechanism with aliquoting into single-use sample tubes. Solid salt transfer in the sample tubes will replace fluidic coupling for integrating the vacuum sampler with downstream modules. Because the proposed operations can all be executed with simple overhead actuation mechanisms or other existing hot-cell technology, there will be no need for large investments in novel hot cell sample handling technologies using this alternate approach. As such, near-term deployment of the vacuum sampling technology will be achievable. This new approach for automated coupling of sample tubes with down-stream modules is covered in a separate FY21 report, and a remotely operated version of the vacuum sampler loop module with the tube aliquoting feature is planned for FY22.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Atomically Precise Membranes for the Separation of Gases

Industrial separations require enormous amounts of energy, accounting for approximately half the industrial energy use and 10–15% of the total energy consumption. Distillation alone accounts for about half the energy demand for industrial separations. If these processes could be replaced by an energy-efficient membrane separation process, this energy demand could be reduced by 90%. However, although some membrane processes have made inroads into thermal distillation, for membrane-based separations to replace the distillation process to a far more significant and practical level, new membranes with higher robustness, selectivity, and flux still need be developed. In this membrane development program, we leveraged Temple University’s prior work in spiroligomers to develop robust membrane structures. These structures can be formed into atomically precise pores by controlling the chemical synthesis and the oligomer building blocks to first build precisely controlled macrocycles and then subsequently crosslinking these macrocycles to produce a membrane. Furthermore, through the highly controllable chemistry of our molecular building blocks, not only can we integrate pores with highly controllable and reproducible size and morphology, but we can also target internal functionalization. By using a range of scalable membrane synthesis approaches, combined with control of each and every pores internal chemistry and molecular conformation we can achieve membrane structures that can display the ultimate in high selectivity and permeance. The Mainstream-Temple University membranes can be designed to achieve ultra-selective separations based on the key factors of molecular size, shape, and functionality. In our approach to fabricate scalable atomically precise membranes, we used our molecular Lego nanostructures. We demonstrated an approach to create atomically precise pores within the membrane with pores that are the dimensions of the molecule we are trying to separate. Moreover, in addition to controlling the morphology of the membrane structure by controlling the size of every pore, we can also decorate every pore with precisely targeted and placed functional groups. These accurately placed functional groups can provide selective binding to molecules and provide enhanced selectivity via a facilitated transport mechanism. In Phase II, the Mainstream-Temple University team demonstrated the scalable synthesis of oligomers and the ability to control the pore internal and external functionality, or chemistry, to allow the fabrication of a thin-film membrane. The initial steps of the spiroligomer synthesis to produce the two key bis-amino enantiomer building blocks were scaled from the gram scale to the kilogram scale, obtaining 25 kg of the materials by transferring the procedure to a toll manufacturer. Finally, we successfully optimized the fabrication of these macrocycles into robust membranes. We successfully transitioned from a laboratory based, hard-to-scale Langmuir trough synthesis to a highly scalable, roll-to-roll applicable, interfacial polymerization process. During this Phase II program, we established a platform of atomically precise membranes where our highly controllable, atomically precise macrocycles served as a scaffold with precisely and uniformly controlled pores. Furthermore, this layer can be tailored to accommodate a diverse range of functional groups, which both further controlled the pore size to enhance the sieving effect as well as imparting precisely controlled targeted selectivity through biomimetic molecular interactions. In this Phase II, we established and scaled up a platform approach to both tune the pore size and chemistry as well as scale it to produce membranes that can be applied to a wide range of industries. In future development, the project team expects to scale up both the macrocycle building block production and interfacial polymerization process to produce the atomically precise membrane with targeted pore sizes and pore chemistries.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Data-Driven Forgetting and Discount Factors for Vehicle Speed Forecasting in Ecological Adaptive Cruise Control

Abstract This paper investigates temporal correlations in human driving behavior using real-world driving to improve speed forecasting accuracy. These correlations can point to a measurement weighting function with two parameters: a forgetting factor for past speed measurements that the vehicle itself drove with, and a discount factor for the speeds of vehicles ahead based on information from vehicle-to-vehicle communication. The developed weighting approach is applied to a vehicle speed predictor using polynomial regression, a prediction method well-known in the literature. The performance of the developed approach is then assessed in both real-world and simulated traffic scenarios for accuracy and robustness. The new weighting method is applied to an ecological adaptive cruise control system, and its influence is analyzed on the prediction accuracy and the performance of the ecological adaptive cruise control in an electric vehicle powertrain model. The results show that the new prediction method improves energy saving from the eco-driving by up to 4.7% compared to a baseline least-square-based polynomial regression. This is a 10% improvement over the constant speed/acceleration model, a conventional speed predictor.

Automation & Control Systems↗