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DOE OSTI2024

Component pose reconstruction using a single robotic total station for panelized building envelopes

The construction industry can benefit greatly from increased automation in construction processes in terms of precision, time, and labor costs. This is especially true for prefabricated construction for either new buildings or envelope retrofits. Here, prefabricated components are manufactured offsite according to design specifications and installed onsite. Accurate information on the components position and orientation (pose) is needed to achieve this. A tool named Real-Time Evaluator (RTE), designed to autonomously track prefabricated components as they are being installed and provide real-time installation instructions, is currently under development using a single robotic total station. This is challenging since at least three points are needed to determine the pose of an object in space. To achieve this goal with a single robotic total station, two key algorithms were developed: the resection algorithm aligns the digital twin with the physical twin regardless of the location of the total station, and the transformation algorithm gives instructions of translations and rotations to installers to achieve the desired installation pose. The algorithms were evaluated experimentally on a lab-scale demonstration. Results show that the resection algorithm achieved an average error of < 3.1 mm, while the transformation algorithm predicted the rotation angle along a single axis with an error of < 0.5◦.

Tang, Mengjia↗

DOE OSTI2021

SMART-COM – Scalable Multi-Agent Adaptive Resolution Tools for Collaborative Outage Management

The purpose of this grant was to conduct scientific research and prototype applications to support NPP outage staff in their adaptive decision-making in efficient scheduling and resource allocation while preventing violation of safety technical specifications. The project contributed to scientific knowledge and engineering methods in (1) user interface design, (2) scheduling optimization and risk estimation, and (2) natural language processing that would benefit the nuclear power plants in minimizing schedule overruns and even unexpected shutdowns. The research team conducted site visits at a test reactor facility and an operating nuclear power plant to gather necessary information and inputs for research and development of a software application to support NPP staff in executing their outages. The final software application consisted of three modules. First, the natural language processing module supports interactive processing of technical documentation to build a database for outage staff to query non-permissible actions on system components. This module can alleviate outage staff from reviewing extensive documentation and minimize violation of technical specifications, especially in time-sensitive situations. Second, the schedule optimization module schedules outage activities and compute risk indices that outperform existing software and current practice. This module can reduce completion time of an outage that typically have too many activities for human to optimize based on current practice that does not apply the latest operations research. Finally, the visualization module presents progress and risk information of the overall outage and individual activities, as well as enabling access to the natural language processing and schedule optimization modules. This module can provide outage staff with situation awareness that are necessary to make risk-informed decisions in response to unexpected events during the execution of an outage.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Consistency of the pion form factor and unpolarized transverse momentum dependent parton distributions beyond leading twist in the light-front quark model

We investigate the interplay among the pion’s form factor, transverse momentum dependent distributions (TMDs), and parton distribution functions (PDFs) extending our light-front quark model (LFQM) computation based on the Bakamjian-Thomas construction for the two-point function [1,2] to the three-point and four-point functions. Ensuring the four-momentum conservation at the meson-quark vertex from the Bakamjian-Thomas construction, the meson mass is taken consistently as the corresponding invariant meson mass both in the matrix element and the Lorentz factor in our LFQM computation. We achieve the current-component independence in the physical observables such as the pion form factor and delve into the derivation of unpolarized TMDs and PDFs associated with the forward matrix element. We address the challenges posed by twist-4 TMDs and exhibit the fulfillment of the sum rule. Effectively, our LFQM successfully handles the light-front zero modes and offers insights for broader three-point and four-point functions and related observables.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Perspectives on the FESAC transformative enabling capabilities: Priorities, plans, and Status

In early 2017, the Fusion Energy Sciences Advisory Committee (FESAC), an advisory committee to the United States Department of Energy, was charged with identifying transformative enabling capabilities (TECs) “that could promote efficient advance toward fusion energy, building on burning plasma science and technology.” A subcommittee with broad expertise was formed and sought feedback from scientific experts, including experts from outside the fusion community. Three workshops were conducted, and a report was approved by FESAC in 2018 that identified four of the “most promising” TECs: advanced algorithms, high-critical-temperature superconductors, advanced materials and manufacturing, and novel technologies for tritium fuel cycle control. In addition, one “promising” TEC was identified: fast flowing liquid metal plasma-facing components. This paper will give details on the promising TECs and an overview on considerations of these TECs in the United States since the publication of the report.

Lumsdaine, Arnold↗

DOE OSTI2022

Solid-phase isotope harvesting of 88 Zr from a radioactive ion beam facility

During routine operation of the Facility for Rare Isotope Beams (FRIB), radionuclides will accumulate in both the aqueous beam dump and along the beamline in the process of beam purification. These byproduct radionuclides, many of which are far from stability, can be collected and purified for use in other scientific applications in a process called isotope harvesting. In this work, the viability of 88 Zr harvesting from solid components was investigated at the National Superconducting Cyclotron Laboratory. A secondary 88 Zr beam was stopped in a series of collectors comprised of Al, Cu, W, and Au foils. Here, this work details irradiation of the collector foils and the subsequent radiochemical processing to isolate the deposited 88 Zr (and its daughter 88 Y) from them. Total average recovery from the Al, Cu, and Au collector foils was (91.3 ± 8.9) % for 88 Zr and (95.0 ± 5.8) % for 88 Y, respectively, which is over three times higher recovery than in a previous aqueous-phase harvesting experiment. The utility of solid-phase isotope harvesting to access elements such as Zr that readily hydrolyze in near-neutral pH aqueous conditions has been demonstrated for application to harvesting from solid components at FRIB.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2020

Three-Dimensional Mapping of Resistivity and Microstructure of Composite Electrodes for Lithium-Ion Batteries

Nanoparticle silicon–graphite composite electrodes are a viable way to advance the cycle life and energy density of lithium-ion batteries. However, characterization of composite electrode architectures is complicated by the heterogeneous mixture of electrode components and nanoscale diameter of particles, which falls beneath the lateral and depth resolution of most laboratory-based instruments. In this work, we report an original laboratory-based scanning probe microscopy approach to investigate composite electrode microstructures with nanometer-scale resolution via contrast in the electronic properties of electrode components. Applying this technique to silicon-based composite anodes demonstrates that graphite, SiOx nanoparticles, carbon black, and LiPAA binder are all readily distinguished by their intrinsic electronic properties, with measured electronic resistivity closely matching their known material properties. Resolution is demonstrated by identification of individual nanoparticles as small as ~20 nm. Our technique presents future utility in multiscale characterization to better understand particle dispersion, localized lithiation, and degradation processes in composite electrodes for lithium-ion batteries.

25 ENERGY STORAGE↗

DOE OSTI2021

Advanced mass balance characterization and fractionation of algal biomass composition

Abstract Opportunities associated with biomass production and bioproduct isolation from algae-derived feedstocks are plentiful and promising; however, there are challenges associated with realizing these applications. One of the most important, and often overlooked, challenges is the lack of availability of a strong foundation of compositional analysis methods validated on microalgal biomass. Currently, compositional analysis in algae is dominated by the use of interference-prone methods, a lack of full mass balance accounting, and the use of top-down approaches that bin all unaccounted-for mass into a single category, such as carbohydrates. We present here an approach based on a bottom-up algal biomass characterization aimed at moving towards, and highlighting the importance of, full and accurate mass closure to achieve the maximum economic potential from a sustainable and renewable feedstock. Algal biomass representing three genera, Nannochloropsis , Scenedesmus , and Monoraphidium , was subjected to a cell rupture and fractionation process, followed by detailed characterization of each fraction to determine the partitioning of measured and unknown components. The goal of this work is to identify where the missing components partition, and develop a strategy to close the mass balance or identify the unknowns, while utilizing a rigorous characterization approach for characterizing algal biomass. Although only 75–80% of the biomass was accounted for, the fractionation approach utilized here provides key insight into possible chemical components for future investigations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Netting and pan traps fail to identify the pollinator guild of an agricultural crop

Pollinator decline is expected to cause significant reductions in food production and plant reproduction. Quantifying the impact of pollinator decline on food production requires survey methods that can identify insect and bee species responsible for pollination of specific crops. To address this issue, we compared the effectiveness of two survey methods, netting and pan traps, at capturing the pollinators of alfalfa, Medicago sativa. Alfalfa is a major component of forage for cows and an important ingredient in chicken feed. We also examined bee species richness and diversity with these two survey methods, and compared these measures among three different colors of pan traps. Netting was more effective at capturing known pollinators of alfalfa, especially those belonging to the Bombus and Apis genera. Pan traps captured a higher bee diversity relative to netting and, like previous studies, each survey method and each trap color was more efficient at capturing certain bee genera. However, without a priori knowledge of pollinators, neither survey method could identify which of the bee species captured could pollinate alfalfa. We therefore recommend direct observations when the goal of a study is to identify pollinators or link pollinator decline to food production.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Substructure in the stellar halo near the Sun: II. Characterisation of independent structures

In an accompanying paper, we present a data-driven method for clustering in ‘integrals of motion’ space and apply it to a large sample of nearby halo stars with 6D phase-space information. The algorithm identified a large number of clusters, many of which could tentatively be merged into larger groups. The goal here is to establish the reality of the clusters and groups through a combined study of their stellar populations (average age, metallicity, and chemical and dynamical properties) to gain more insights into the accretion history of the Milky Way. To this end, we developed a procedure that quantifies the similarity of clusters based on the Kolmogorov–Smirnov test using their metallicity distribution functions, and an isochrone fitting method to determine their average age, which is also used to compare the distribution of stars in the colour–absolute magnitude diagram. Also taking into consideration how the clusters are distributed in integrals of motion space allows us to group clusters into substructures and to compare substructures with one another. We find that the 67 clusters identified by our algorithm can be merged into 12 extended substructures and 8 small clusters that remain as such. The large substructures include the previously known Gaia-Enceladus, Helmi streams, Sequoia, and Thamnos 1 and 2. We identify a few over-densities that can be associated with the hot thick disc and host a small metal-poor population. Especially notable is the largest (by number of member stars) substructure in our sample which, although peaking at the metallicity characteristic of the thick disc, has a very well populated metal-poor component, and dynamics intermediate between the hot thick disc and the halo. We also identify additional debris in the region occupied by Sequoia with clearly distinct kinematics, likely remnants of three different accretion events with progenitors of similar masses. Although only a small subset of the stars in our sample have chemical abundance information, we are able to identify different trends of [Mg/Fe] versus [Fe/H] for the various substructures, confirming our dissection of the nearby halo. We find that at least 20% of the halo near the Sun is associated to substructures. When comparing their global properties, we note that those substructures on retrograde orbits are not only more metal-poor on average but are also older. We provide a table summarising the properties of the substructures, as well as a membership list that can be used for follow-up chemical abundance studies for example.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Non-autoregressive time-series methods for stable parametric reduced-order models

Advection-dominated dynamical systems, characterized by partial differential equations, are found in applications ranging from weather forecasting to engineering design where accuracy and robustness are crucial. There has been significant interest in the use of techniques borrowed from machine learning to reduce the computational expense and/or improve the accuracy of predictions for these systems. These rely on the identification of a basis that reduces the dimensionality of the problem and the subsequent use of time series and sequential learning methods to forecast the evolution of the reduced state. Often, however, machine-learned predictions after reduced-basis projection are plagued by issues of stability stemming from incomplete capture of multiscale processes as well as due to error growth for long forecast durations. To address these issues, we have developed a non-autoregressive time series approach for predicting linear reduced-basis time histories of forward models. In particular, we demonstrate that non-autoregressive counterparts of sequential learning methods such as long short-term memory (LSTM) considerably improve the stability of machine-learned reduced-order models. Further, we evaluate our approach on the inviscid shallow water equations and show that a non-autoregressive variant of the standard LSTM approach that is bidirectional in the principal component directions obtains the best accuracy for recreating the nonlinear dynamics of partial observations. Moreover-and critical for many applications of these surrogates-inference times are reduced by three orders of magnitude using our approach, compared with both the equation-based Galerkin projection method and the standard LSTM approach.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Simulating charged defects at database scale

Point defects have a strong influence on the physical properties of materials, often dominating the electronic and optical behavior in semiconductors and insulators. The simulation and analysis of point defects is, therefore, crucial for understanding the growth and operation of materials, especially for optoelectronics applications. In this work, we present a general-purpose Python framework for the analysis of point defects in crystalline materials as well as a generalized workflow for their treatment with high-throughput simulations. The distinguishing feature of our approach is an emphasis on a unique, unit cell, structure-only, definition of point defects which decouples the defect definition, and the specific supercell representation used to simulate the defect. This allows the results of first-principles calculations to be aggregated into a database without extensive provenance information and is a crucial step in building a persistent database of point defects that can grow over time, a key component toward realizing the idea of a “defect genome” that can yield more complex relationships governing the behavior of defects in materials. We demonstrate several examples of the approach for three technologically relevant materials and highlight current pitfalls that must be considered when employing these methodologies as well as their potential solutions.

36 MATERIALS SCIENCE↗

DOE OSTI2020

The cryoelectron microscopy structure of the human CDK-activating kinase

The human CDK-activating kinase (CAK), a complex composed of cyclin-dependent kinase (CDK) 7, cyclin H, and MAT1, is a critical regulator of transcription initiation and the cell cycle. It acts by phosphorylating the C-terminal heptapeptide repeat domain of the RNA polymerase II (Pol II) subunit RPB1, which is an important regulatory event in transcription initiation by Pol II, and it phosphorylates the regulatory T-loop of CDKs that control cell cycle progression. Here, we have determined the three-dimensional (3D) structure of the catalytic module of human CAK, revealing the structural basis of its assembly and providing insight into CDK7 activation in this context. The unique third component of the complex, MAT1, substantially extends the interaction interface between CDK7 and cyclin H, explaining its role as a CAK assembly factor, and it forms interactions with the CDK7 T-loop, which may contribute to enhancing CAK activity. We have also determined the structure of the CAK in complex with the covalently bound inhibitor THZ1 in order to provide insight into the binding of inhibitors at the CDK7 active site and to aid in the rational design of therapeutic compounds.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

A framework for discrete optimization of stellarator coils

Designing magnets for three-dimensional plasma confinement is a key task for advancing the stellarator as a fusion reactor concept. Stellarator magnets must produce an accurate field while leaving adequate room for other components and being reasonably simple to construct and assemble. In this paper, a framework for coil design and optimization is introduced that enables the attainment of sparse magnet solutions with arbitrary restrictions on where coils may be located. The solution space is formulated as a 'wireframe' consisting of a mesh of interconnected wire segments enclosing the plasma. Two methods are developed for optimizing the current distribution on a wireframe: Regularized Constrained Least Squares, which uses a linear least-squares approach to optimize the currents in each segment, and Greedy Stellarator Coil Optimization, a fully discrete procedure in which loops of current are added to the mesh one by one to achieve the desired magnetic field on the plasma boundary. Examples are presented of solutions obtainable with each method, some of which achieve high field accuracy while obeying spatial constraints that permit easy assembly.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

TAG… You’re It, Synechocystis sp. PCC 6803!

Triacylglycerol (TAG), a ubiquitous energy storage molecule found mainly in eukaryotes, comprises glycerol esterified with three fatty acids of variable lengths and saturation states. TAG is also considered as a high-value biochemical because it can be converted into fatty acid methyl esters, key components of biodiesel, through transesterification with methanol. Thus, considerable efforts have been made to produce TAGs from CO2 as a renewable energy source.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗

DOE OSTI2025

Superexponential primordial black hole production via delayed vacuum decay

If a cosmological first-order phase transition occurs sufficiently slowly, delayed vacuum decay may lead to the formation of primordial black holes. Here we consider a simple model as a case study of how the abundance of the produced black holes depends on the model’s input parameters. We demonstrate, using both numerical and analytical arguments and methods, that the black hole abundance is controlled by a double, “super”-exponential dependence on the three-dimensional Euclidean action over temperature at its minimal value. We show that a modified expansion rate during the phase transition, such as one driven by an additional energy density component, leads to a weaker dependence on the underlying model parameters, but maintains the same superexponential structure. We argue that our findings generalize to any framework of black hole production via delayed vacuum decay. Published by the American Physical Society 2025

Wu, Yanda (ORCID:000000034487305X)↗

DOE OSTI2021

Understanding the Role of π-Conjugated Polymers as Binders in Enabling Designs for High-Energy/High-Rate Lithium Metal Batteries

Developing lithium-ion batteries with both high specific energy and high-power capability is a challenging task because of the necessity for meeting conflicting design requirements. We show that high-energy and high-rate capability can be achieved by using various π -conjugated p-dopable polymers as binders at the cathode and by lowering the mass fraction of all the inactive components of the cell. We report a lithium-metal battery that can deliver 320 Wh kg −1 at C/2 using a mass-efficient cell design. To this end, three conducting polymers with different ionic and electronic conductivities have been studied; dihexyl-substituted poly(3,4-propylenedioxythiophene) (PProDOT-Hx 2 ), poly(3-hexylthiophene) (P3HT), and a new Random Copolymer (Hex:OE)(80:20) PProDOT. These conducting polymers are compared against a conventional polymer binder, PVDF. We show that under the mass-efficient conditions required for achieving high specific energy and rate capability, the conducting polymers play a crucial role by providing electronic and ionic conductivity, protection against rapid growth of solid electrolyte interphase (SEI), and access to a large electrochemically active surface area. Thus, the use of conducting polymers with appropriate molecular structure as binders opens a viable pathway to maximizing the specific energy and rate capability of lithium-ion battery cathodes.

25 ENERGY STORAGE↗

DOE OSTI2020

Micrometer-accuracy 2D displacement interferometer with plasmonic metasurface resonators

In this Letter, a high-accuracy, two-dimensional displacement sensor is proposed, designed, and demonstrated based on the concept of an extrinsic Fabry–Perot Interferometer. The sensor is composed of two bundled single-mode optic fibers in parallel and two plasmonic metasurface resonators inscribed on a gold substrate via a focused ion beam. The fiber end surface and the metasurface are in parallel with a small cavity between. The cavity change or Z -component displacement is determined from the pattern of interference fringes. The X -component displacement, perpendicular to the Z component, is identified from wavelength-selective metasurface resonators, which possess unique resonant wavelengths due to different nanostructure designs. The sensor was calibrated with six displacements applied through a three-axis precision linear stage. Test results indicated that the proposed interferometer can measure displacements with a maximum error of 5.4 µm or 2.2%.

Guo, Chuanrui (ORCID:0000000271412972)↗

DOE OSTI2021

Report on Properties and Microstructure of 3D Printed Inc-718

The report presents the microstructure and mechanical properties of 3D printed Inconel 718 to assess its potential use as a structural material for the Transformation Challenge Reactor (TCR). The structural components near the outlet of the core will experience significant neutron fluxes and outlet coolant temperatures from the hot standby temperature of 300°C to nearly 550°C at the center of the part. These components must support the core in appropriate loading conditions and require structural analysis at relevant temperatures. Strong spatial and chemical heterogeneity was found in as-built (ASB) Inconel 718. Three heat treatments were designed and conducted to simplify the microstructure and determine how each precipitating phase contributed to the overall strength. Baseline mechanical properties were measured from uniaxial tensile tests on subsize SS-J2 specimens at room temperature and at elevated temperatures of 300, 450, and 600°C. Microstructure electron microscopy was performed on ASB Inconel 718 and heat treated to correlate the observed mechanical properties with nanoscale features. Homogenization of the microstructure led to a highly ductile Inconel with lower strength compared with wrought Inconel 718. The tensile properties of additively manufactured 718 using a standard ASTMrecommended heat treatment were consistent with literature and with the ASTM for the properties of this alloy. A higher fraction of the δ phase led to shorter uniform elongation without altering other engineering properties.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗