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Characterization and Optimization of Skipper CCDs for the SOAR Integral Field Spectrograph

We present results from the characterization and optimization of Skipper charge-coupled devices (CCDs) for use in a focal plane prototype for the Southern Astrophysical Research Integral Field Spectrograph (SIFS). We tested eight Skipper CCDs and selected six for SIFS based on performance results. The Skipper CCDs are 6k × 1k, 15 μm pixels, thick, fully depleted, p-channel devices that have been thinned to ~250 μm, backside processed, and treated with an anti-reflective coating. We demonstrate a single-sample readout noise of <4.3 e - rms pixel -1 in all amplifiers. We optimize the readout sequence timing to achieve a readout noise of 0.5 e - rms pixel -1 after 74 non-destructive measurements, which can be accomplished in a region covering 5% of the detector area in a readout time of <4 minutes. We demonstrate single-photon-counting in all 24 amplifiers (four amplifiers per detector) with a readnoise of σ N ~ 0.18 e - rms pixel -1 after N samp = 400 samples, and we constrain the degree of nonlinearity to be ≲1% at low signal levels (0 e - to 50 e - ). Clock-induced charge (CIC) remains an important issue when the Skipper CCD is configured to provide a large full-well capacity. We achieve a CIC rate of <1.45 × 10 -3 e - pixel -1 frame -1 for a full-well capacity of ~900 e - , which increases to a CIC rate of ~3 e - pixel -1 frame -1 for full-well capacities ~40,000-65,000 e - . We also perform conventional CCD characterization measurements such as charge transfer inefficiency (3.44 × 10 -7 on average), dark current (~2 × 10 -4 e - pixel -1 s -1 ), photon transfer curves, cosmetic defects (<0.45% “bad” pixels), and charge diffusion (point-spread function < 7.5 μm) to verify that these properties are consistent with expectations from conventional p-channel CCDs used for astronomy. Furthermore, we provide the first measurements of the brighter-fatter effect and absolute quantum efficiency (≳80% between 450 and 980 nm; ≳90% between 600 and 900 nm) using Skipper CCDs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Digital Twins for Materials

Digital twins are emerging as powerful tools for supporting innovation as well as optimizing the in-service performance of a broad range of complex physical machines, devices, and components. A digital twin is generally designed to provide accurate in-silico representation of the form (i.e., appearance) and the functional response of a specified (unique) physical twin. This paper offers a new perspective on how the emerging concept of digital twins could be applied to accelerate materials innovation efforts. Specifically, it is argued that the material itself can be considered as a highly complex multiscale physical system whose form (i.e., details of the material structure over a hierarchy of material length) and function (i.e., response to external stimuli typically characterized through suitably defined material properties) can be captured suitably in a digital twin. Accordingly, the digital twin can represent the evolution of structure, process, and performance of the material over time, with regard to both process history and in-service environment. This paper establishes the foundational concepts and frameworks needed to formulate and continuously update both the form and function of the digital twin of a selected material physical twin. The form of the proposed material digital twin can be captured effectively using the broadly applicable framework of n-point spatial correlations, while its function at the different length scales can be captured using homogenization and localization process-structure-property surrogate models calibrated to collections of available experimental and physics-based simulation data.

36 MATERIALS SCIENCE↗

Performance of Graphene/Polydimethylsiloxane Surfaces against S. aureus and P. aeruginosa Single- and Dual-Species Biofilms

The increasing incidence of implant-associated infections has prompted the development of effective strategies to prevent biofilm formation on these devices. In this work, pristine graphene nanoplatelet/polydimethylsiloxane (GNP/PDMS) surfaces containing different GNP loadings (1, 2, 3, 4, and 5 wt%) were produced and evaluated on their ability to mitigate biofilm development. After GNP loading optimization, the most promising surface was tested against single- and dual-species biofilms of Staphylococcus aureus and Pseudomonas aeruginosa. The antibiofilm activity of GNP/PDMS surfaces was determined by the quantification of total, viable, culturable, and viable but nonculturable (VBNC) cells, as well as by confocal laser scanning microscopy (CLSM). Results showed that 5 wt% GNP loading reduced the number of total (57%), viable (69%), culturable (55%), and VBNC cells (85%) of S. aureus biofilms compared to PDMS. A decrease of 25% in total cells and about 52% in viable, culturable, and VBNC cells was observed for P. aeruginosa biofilms. Dual-species biofilms demonstrated higher resistance to the antimicrobial activity of GNP surfaces, with lower biofilm cell reductions (of up to 29% when compared to single-species biofilms). Still, the effectiveness of these surfaces in suppressing single- and dual-species biofilm formation was confirmed by CLSM analysis, where a decrease in biofilm biovolume (83% for S. aureus biofilms and 42% for P. aeruginosa and dual-species biofilms) and thickness (on average 72%) was obtained. Overall, these results showed that pristine GNPs dispersed into the PDMS matrix were able to inhibit biofilm growth, being a starting point for the fabrication of novel surface coatings based on functionalized GNP/PDMS composites.

Oliveira, Isabel M.↗

Crystal structures and formation mechanisms of boron-rich tungsten borides

Boron-rich tungsten borides tend to adopt mechanically unfavorable layered structures but experimentally exhibit excellent mechanical properties rivalling traditional superhard solids. Unravelling the contraindicated structure-property relationship, however, has been impeded by their structural ambiguities because of the difficulty in probing boron and atomic deficiency of these borides. Here, we study crystal structures of boron-rich tungsten borides WB 3+x and WB 2+x by neutron diffraction based on high-quality samples prepared by a high-pressure method, leading to definitive structural resolutions for both borides with unique compositions of WB 5.14 and WB 2.34 . Combined with theoretical calculations, their structural stability is revealed to be closely related to atomic deficiency, which is governed by the valence-band filling with an optimal valence-electron concentration of ~10 per cell. The presence of interstitial boron trimers at the vacant W : 2b sites in WB 5.14 alters the crystal symmetry, making the Wyckoff 2d site more favorably occupied by W, rather than the 2c site, as previously misassigned. Here, the staggered planar boron layers and wrinkled boron bonding in WB 2.34 are identified to be crucial for stabilizing its structure. These findings unveil the longstanding structural mysteries of boron-rich tungsten borides and offer powerful insights for rational design of borides by defect chemistry.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Microstructure effects on high velocity microparticle impacts of copper

Constitutive models can fail to predict high-rate deformation behavior due to their inability to account for microstructural effects. In part, this is because of a dearth of experimental benchmarking data in the high strain-rate, low pressure regime, since many high-rate experiments also probe a region of strong shockwaves, at which point microstructure effects no longer play a primary role. This work uses laser-induced particle impact testing to quantitatively study high velocity impacts of small, rigid alumina microspheres on flat copper substrates with varying amounts of initial cold work in the weak shock regime, but at very high strain rates up to ~10 7 s –1 . Through paired experiments and numerical simulations, this work shows that the initial microstructure condition can have significant influence on dynamical mechanical properties in this range. Specifically, prior work hardening of the copper substrate leads to increased rebounding of the microparticles (i.e., less plastic dissipation in the impact) as well as smaller craters. Each of these experimental measurables can be converted into a strength measure, i.e., the dynamic yield strength or dynamic hardness, respectively, neither of which is well predicted consistently by existing constitutive laws. The general trend of hardening can be captured by such models by incorporating an existing “pre-strain,” suggesting that future calibration of the materials parameters may yield a good fit over a broader range of conditions. Our results emphasize the importance of reporting the microstructural condition in dynamic studies, as well as the necessity of accounting for these factors when formulating and optimizing constitutive models.

36 MATERIALS SCIENCE↗

Dimensionally reduced machine learning model for predicting single component octanol–water partition coefficients

Abstract MF-LOGP, a new method for determining a single component octanol–water partition coefficients ( $$LogP$$ LogP ) is presented which uses molecular formula as the only input. Octanol–water partition coefficients are useful in many applications, ranging from environmental fate and drug delivery. Currently, partition coefficients are either experimentally measured or predicted as a function of structural fragments, topological descriptors, or thermodynamic properties known or calculated from precise molecular structures. The MF-LOGP method presented here differs from classical methods as it does not require any structural information and uses molecular formula as the sole model input. MF-LOGP is therefore useful for situations in which the structure is unknown or where the use of a low dimensional, easily automatable, and computationally inexpensive calculations is required. MF-LOGP is a random forest algorithm that is trained and tested on 15,377 data points, using 10 features derived from the molecular formula to make $$LogP$$ LogP predictions. Using an independent validation set of 2713 data points, MF-LOGP was found to have an average $$RMSE$$ RMSE = 0.77 ± 0.007, $$MAE$$ MAE = 0.52 ± 0.003, and $${R}^{2}$$ R 2 = 0.83 ± 0.003. This performance fell within the spectrum of performances reported in the published literature for conventional higher dimensional models ( $$RMSE$$ RMSE = 0.42–1.54, $$MAE$$ MAE = 0.09–1.07, and $${R}^{2}$$ R 2 = 0.32–0.95). Compared with existing models, MF-LOGP requires a maximum of ten features and no structural information, thereby providing a practical and yet predictive tool. The development of MF-LOGP provides the groundwork for development of more physical prediction models leveraging big data analytical methods or complex multicomponent mixtures. Graphical Abstract

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Rerouting reductant flux via protein tethering enhances biohydrogen production in Thermococcus kodakarensis

Microbes that generate copious amounts of hydrogen (H 2 ) via dark fermentation are a promising means to evolve and improve renewable biofuels. Many anaerobic hyperthermophilic archaea, such as the fast-growing, genetically tractable, heterotroph Thermococcus kodakarensis, produce generous quantities of H2 and provide an idealized platform to further optimize naturally high levels of biohydrogen reduction. Precise genetic manipulations and modifications to growth conditions have already resulted in substantial increases to H2 output but additional improvements are desired. An unexamined and potentially valuable route towards increased H 2 production is to tether select electron donor and acceptor proteins together to reroute and maximize the flow of electrons towards H 2 production. Such strategies have shown promise in Bacteria and Eukarya but have not yet been investigated in thermophilic Archaea. Here, we generate and evaluate twelve novel T. kodakarensis strains wherein a proteinaceous electron carrier (a ferredoxin, Fd) is physically tethered to the membrane-bound-hydrogenase (MBH), the sole H 2 producing enzyme, to direct electron flux towards biohydrogen generation. Growth assessments and H 2 output measurements demonstrate that strains encoding protein-fusions evolve up to ~ 40% more H2 per cell than the host strain. Eliminating H 2 consumption and alternative routes of electron sinks in concert with protein tethering further increased H2 output per cell for a maximum increase of ~ 66% over the host strain. Our results demonstrate that rerouting electron flux via protein tethering coupled with the elimination of reductant sinks is a promising means towards improved biohydrogen production in T. kodakarensis. KEY POINTS: Protein tethering between redox proteins can reroute electron flux in vivo. Enforced protein proximity results in ~ 40% increases in H2 production per cell. Protein-tethering provides a generalizable framework to redirect redox metabolism.

59 BASIC BIOLOGICAL SCIENCES↗

Variational approach to quantum state tomography based on maximal entropy formalism

Quantum state tomography is an integral part of quantum computation and offers the starting point for the validation of various quantum devices. One of the central tasks in the field of state tomography is to reconstruct, with high fidelity, the quantum states of a quantum system. From an experiment on a real quantum device, one can obtain the mean measurement values of different operators. With such data as input, in this report we employ the maximal entropy formalism to construct the least biased mixed quantum state that is consistent with the given set of expectation values. Even though, in principle, the reported formalism is quite general and should work for an arbitrary set of observables, in practice we shall demonstrate the efficacy of the algorithm on an informationally complete (IC) set of Hermitian operators. Such a set possesses the advantage of uniquely specifying a single quantum state from which the experimental measurements have been sampled and hence renders the rare opportunity not only to construct a least-biased quantum state but even replicate the exact state prepared experimentally within a preset tolerance. Here, the primary workhorse of the algorithm is reconstructing an energy function which we designate as the effective Hamiltonian of the system, and parameterizing it with Lagrange multipliers, according to the formalism of maximal entropy. These parameters are thereafter optimized variationally so that the reconstructed quantum state of the system converges to the true quantum state within an error threshold. To this end, we employ a parameterized quantum circuit and a hybrid quantum-classical variational algorithm to obtain such a target state, making our recipe easily implementable on a near-term quantum device.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Class of Sparse Johnson–Lindenstrauss Transforms and Analysis of their Extreme Singular Values

The Johnson–Lindenstrauss (JL) lemma is a powerful tool for dimensionality reduction in modern algorithm design. The lemma states that any set of high-dimensional points in a Euclidean space can be projected into lower dimensions while approximately preserving pairwise Euclidean distances. Random matrices satisfying this lemma are called JL transforms (JLTs). Inspired by existing $s$-hashing JLTs with exactly $s$ nonzero elements on each column, the present work introduces an ensemble of sparse matrices encompassing so-called $s$-hashing-like matrices whose expected number of nonzero elements on each column is $s$. The independence of the sub-Gaussian entries of these matrices and the knowledge of their exact distribution play an important role in their analyses. Using properties of independent sub-Gaussian random variables, these matrices are demonstrated to be JLTs, and their smallest nontrivial singular values and largest singular values are estimated nonasymptotically using a technique from geometric functional analysis. As the dimensions of the matrix grow to infinity, these singular values are proved to converge almost surely to fixed quantities (by using the universal Bai–Yin law) and in distribution to the Gaussian orthogonal ensemble Tracy–Widom law after proper rescalings. Understanding the behaviors of extreme singular values is important in general because they are often used to define a measure of stability of matrix algorithms. For example, JLTs were recently used in derivative-free optimization algorithmic frameworks to select random subspaces in which are constructed random models or poll directions to achieve scalability, and hence estimating their smallest singular value in particular helps determine the dimension of these subspaces.

97 MATHEMATICS AND COMPUTING↗

Inventory of Clean Energy Education and Workforce Programs in Connecticut's I-91 Corridor

This document reports on the findings of an inventory of the educational and workforce development resources in a four-county area on the I-91 corridor in Connecticut. The overarching goal of this exercise is to help the local workforce leaders in Bridgeport, Connecticut to optimize their training programs to support the county's clean energy transition. The inventory generally finds that Fairfield County, where Bridgeport is located, lacks adequate education and training programs compared to other surrounding counties with similar populations. More than half of Fairfield County's programs occur through high school or career technical education programs, suggesting that there are minimal opportunities for workers who are not currently high school students. Much of the existing focus within Fairfield County is on general construction or plumbing and electrical skills. There is room to expand by offering more programs focusing on energy efficiency and renewable energy skills. The document outlines some potential next steps and questions for consideration for the local workforce leaders in Bridgeport. Bridgeport is a city located within Fairfield County in southwestern Connecticut. It is the largest city in Connecticut with an estimated population of 150,000. Through the Department of Energy-funded Communities LEAP program, NREL conducted an analysis of existing education and workforce development (EWD) programs located in Fairfield County that align with (or could support) the worker pipeline for occupations related to building energy efficiency (EE), renewable energy (RE), and clean energy manufacturing. The analysis also looked at EWD offerings in other counties in Connecticut as a point of comparison.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Compare linear-system solver and preconditioner stacks with emphasis on GPU performance and propose phase-2 NGP solver development pathway

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. In this report we evaluated GPU-performance baselines for the linear solvers in the Trilinos and hypre solver stacks using two representative Nalu-Wind simulations: an atmospheric boundary layer precursor simulation on a structured mesh, and a fixed-wing simulation using unstructured overset meshes. Both strong-scaling and weak-scaling experiments were conducted on the OLCF supercomputer Summit and similar proxy clusters. We focused on the performance of multi-threaded Gauss-Seidel and two-stage Gauss-Seidel that are extensions of classical Gauss-Seidel; of one-reduce GMRES, a communication-reducing variant of the Krylov GMRES; and algebraic multigrid methods that incorporate the afore-mentioned methods. The team has established that AMG methods are capable of solving linear systems arising from the fixed-wing overset meshes on CPU, a critical intermediate result for ExaWind FY20 Q3 and Q4 milestones. For the fixed-wing strong-scaling study (model with 3M grid-points), the team identified that Nalu-Wind simulations with the new Trilinos and hypre solvers scale to modest GPU counts, maintaining above 70% efficiency up to 6 GPUs. However, there still remain significant bottlenecks to performance: matrix assembly (hypre), AMG setup (hypre and Trilinos) In the weak-scaling experiments (going from 0.4M to 211M gridpoints), it's shown that the solver apply phases are faster on GPUs, but that Nalu-Wind simulation times grow, primarily due to the multigrid-setup process. Finally, based on the report outcomes, we propose a linear solver path-forward for the remainder of the ExaWind project. Near term, the NREL team will continue their work on GPU-based linear-system assembly. They will also investigate how the use of alternatives to the NVIDIA UVM (unified virtual memory) paradigm affects performance. Longer term, the NREL team will evaluate algorithmic performance on other types of accelerators and merge their improvements back to the main hypre repository branch. Near term, the Trilinos team will address performance bottlenecks identified in this milestone, such as implementing a GPU-based segregated momentum solve and reusing matrix graphs across linear-system assembly phases. Longer term, the Trilinos team will do detailed analysis and optimization of multigrid setup.

17 WIND ENERGY↗

Resource Recovery and Environmental Protection in Wyoming’s Greater Green River Basin Using Selective Nanostructured Membranes (Final Report)

Produced water (PW) represents a sizable waste stream that is co-generated with oil and natural gas production. In 2021 Wyoming ranked 8th and 9th, respectively in domestic oil and natural gas production. In 2017 Wyoming ranked as the 4th highest generator of PW in the U.S, accounting for 7% of the total volume generated. In the context of being the 3rd most arid state in the U.S., the value of water reuse becomes obvious. PW reuse, and resource recovery, in any form requires some level of treatment to remove particulates, residual (free, dispersed) hydrocarbons, organics, and salts. The level of treatment depends on the requirements of the reuse, or resource recovery, application. PW management systems in Wyoming employ in order of volume of PW managed the following management strategies: reinjection for enhanced oil recovery, surface discharge, deep well injection, evaporation ponds (impoundments), and commercial management/treatment. Complicating treatment efforts are the relatively high concentrations of organics (natural and synthetic), dispersed/free hydrocarbons, benzene-toluene-ethylbenzene, and xylenes (BTEX) compounds, biologicals, salts, and minerals. Hydrocarbons (dispersed/dissolved crude oils) and BTEX compounds, as well as synthetic organics, present economic and environmental concerns. The former represents lost revenue, while the latter results in negative environmental impacts like emissions from surface impoundments. The overall objective of this proposal was to synthesize superhydrophilic/oleophobic and superhydrophobic/oleophilic membranes for selectively concentrating and then separating BTEX compounds and oil and grease (O&G) from PW originating from the Greater Green River Basin (GGRB) in Wyoming. Three specific research aims were pursued to accomplish this overall objective. This final report details the development of the superhydrophobic and superhydrophilic membranes, as well as the design of the membrane module prototypes specifically. The technoeconomic assessment is separately reported in another document. 1. Aim #1 – Material optimization and performance evaluation of superhydrophilic/oleophobic and superhydrophobic/oleophilic membranes made by electrospinning/spraying. 2. Aim #2 – Design and construction of cross-flow membrane modules for selectively concentrating and then separating BTEX/oil from GGRB produced water. 3. Aim #3 – Techno-economic assessment of BTEX/oil recovery, and clean water production, using superhydrophilic/oleophobic and superhydrophobic/oleophilic membrane separation for GGRB PW. Superhydrophobic membranes were synthesized by electrospinning poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) nanofibers onto polyester (PET) substrates and electrospraying nano-carbon black/PVDF-HFP onto the nanofibrous layer. These membranes were characterized by high (>8000 liters per square meter per hour per bar (LMH/bar)) permeance values for pure hydrocarbon phases and a high hydrocarbon selectivity (>96%) when treating GGRB PW. All results were obtained when operating the membrane in a crossflow configuration representative of actual field operating conditions. Solvent/oil properties, specifically viscosity and total surface energy/tension, affected permeance across the membrane, which resulted in light mineral oil (394 LMH/bar) and o-xylene (1834 LMH/bar) being characterized by lower permeance values in the pure phase tests. Mixed phase fluxes between 40 to 80 LMH were obtained for the PW when operating the membrane at a feed pressure of 0.3 bar. Flux decreased as the mixed phase concentration in the feed decreased pointing to the importance of maximizing the collision efficiency between the emulsion and the membrane surface and maximizing the emulsion concentration in the feed and the turbulence within the feed channel. These tests demonstrated that the superhydrophobic membranes developed here are a viable hydrocarbon recovery method for GGRB PWs and should be pursued for testing in pilot-scale trials. Superhydrophilic membranes were successfully synthesized via electrospinning/spraying using polyacrylonitrile (PAN) nanofibers as a base nanofibrous matrix. Integration of polyaniline (PANI) into the nanofibrous matrix produced a superior membrane, for water filtration applications, relative to PAN alone and reduced graphene oxide (RGO) when integrated into the nanofibrous matrix. This conclusion was based on the PANI-PAN resistance to flux loss (fouling) when treating model solvent/oil solutions representative of GGRB PWs and field collected PW from the GGRB. The synthesized PAN membranes outperformed a commercially available PAN membrane designed for oil/water separation. This finding indicates that the surface chemical and physical characteristics of the electrospun membranes presents improved properties for filtration of challenging waters like GGRB PWs. The electrospun membranes therefore show promise overall as a substitute for conventionally polymerized membranes in PW treatment applications. The PANI-PAN membrane specifically presents superior performance characteristics for concentration O&G prior to treatment by the hydrocarbon recovery membrane and producing high-quality filtrate for reuse and/or additional treatment (desalination).

02 PETROLEUM↗

A multiscale landscape approach for prioritizing river and stream protection and restoration actions

River and stream conservation programs have historically focused on a single spatial scale, for example, a watershed or stream site. Recently, the use of landscape information (e.g., land use and land cover) at multiple spatial scales and over large spatial extents has highlighted the importance of incorporating a landscape perspective into stream protection and restoration activities. Previously, we developed a novel framework that links information about watershed-, catchment-, and reach-scale integrity with stream biological condition using scatterplots and a landscape integrity map. Here we examined an application of this approach for streams in urban and other settings in King County, Washington State, United States, where we related stream macroinvertebrate condition to two indices of landscape integrity, the US Environmental Protection Agency's (USEPA) nationally available Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI). We generated a scatterplot of IWI versus ICI for sample sites, where points represented site macroinvertebrate condition from poor to good. The same data were also visualized as a landscape integrity map that displayed catchments of King County according to the level of watershed and catchment integrity (high or low IWI/ICI). Almost three-quarters of poor-condition sites were associated with high-integrity watersheds and catchments (i.e., underperforming sites), which suggested that either one or both national indicators were insufficient for this area, and that sites underperformed because of local-scale factors. In response, we used a catchment-scale indicator related to forest condition (PctForestCat) after examining several GIS-based dispersal indicators from the National Hydrography Dataset and other candidates from the USEPA's StreamCat dataset. We then compared the results of the scatterplots and maps based on the current and original analyses and found that many of the sites previously classified as underperforming now performed as expected, that is, they were poor-condition sites in poor-condition catchments. This analysis demonstrates how results based on a national dataset can be improved by developing an alternative that represents regionally important stressors. The methods used to develop an effective landscape indicator based on StreamCat datasets, and the utility of the multiscale approach, could provide important tools for prioritizing, optimizing, and communicating stream conservation actions.

54 ENVIRONMENTAL SCIENCES↗

Multi-Timescale Integrated Dynamics and Scheduling for Solar (MIDAS-Solar) (Final Technical Report)

Solar photovoltaic (PV) installations have experienced unprecedented growth in the United States. PV will become not only an energy producer but also a necessary provider of ancillary services at multiple timescales. Conventional methods to simulate power systems operations - such as long-term production simulation (which typically considers schedules from hours to minutes by using an optimization framework) and short-term transient studies (which simulate dynamics from seconds to sub-seconds using state variables and differential equations) - are not sufficient for studying the multiple-timescale variation of solar generation and its impact on system reliability. Long-term system economics and short-term system dynamics are highly coupled, particularly when the penetration level of renewable generation is extremely high, because the uncertainty and variability of solar generation will impact both power system steady-state and dynamic performance. This project helps meet and exceed the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Solar Energy Technologies Office goal of systems integration by directly addressing this stability and reliability challenge for power grid planning and operation. We have developed a temporally comprehensive, closed-loop simulation model, named Multi-timescale Integrated Dynamics and Scheduling (MIDAS), that seamlessly simulates power system operations from economic scheduling (day-ahead to hours) to dynamic response analysis (seconds to sub-seconds). For schedules with very high levels of inverter-based resources (IBRs), up to and including 100%, the stability of grid controls has been evaluated through electromagnetic transient (EMT) simulations and power-hardware-in-the-loop (PHIL) simulations of key transient events at key schedule points. Specifically, MIDAS provides: 1) a closed-loop simulation framework for simulating timescales from economic scheduling to dynamic stability analysis; 2) machine learning-based stability assessment; 3) EMT modeling and analysis for large-scale power systems; 4) MIDAS PHIL test bed. We worked with Hawaii Electric Companies to apply the MIDAS study framework to a Maui grid study. The entire island's transmission system was modeled in detail - from a yearly scheduling model, to a second-level frequency dynamic model, down to a sub-second-scale EMT model to address critical stability issues. The project demonstrated how MIDAS can help system planners and operators assess system reliability and stability while the power grid is marching toward a high-renewable, high-IBR future. In this Maui grid study, we found that 100% instantaneous IBR operation is achievable in EMT simulation and PHIL testing, and grid planners and operators might need new analysis/simulation tools to assess grid reliability and stability in the scheduling stage. MIDAS will bring Maui and other systems closer to 100% clean and stable energy futures. (In this study, we examined transient stability. Other topics necessary for 100% IBR operation, such as protection and resource adequacy, were not examined.)

100% Renewables↗

Controlling Preferred Grain Orientation in Vapor-Deposited Metal-Halide Perovskite Thin Films

Metal-halide perovskites are promising semiconductor materials for light-absorber layers in solar cells due to their optimized band gap, defect tolerance, and relative ease of synthesis. In this work, we demonstrate the viability of vapor transport deposition (VTD), a solvent-free processing method, to realize polycrystalline films of both lead iodide (PbI 2 ) and methylammonium lead iodide (MAPbI 3 ) perovskites showing preferential crystallographic orientation. Notable is the difference in perovskite film texturing observed for sequentially and co-deposited VTD films of MAPbI 3 , as well as the lack of strong preferential orientation in solution-processed MAPbI 3 films. While sequential deposition of the perovskite precursors PbI 2 and methylammonium iodide (MAI) leads to a MAPbI 3 film with a limited preferential grain orientation, co-deposited MAPbI 3 films mirror the orientation of excess PbI 2 present in the film. The latter is confirmed by the similar dependence of preferential orientation for PbI 2 and co-deposited MAPbI 3 on underlayer roughness, as well as the emergence of preferential orientation in MAPbI 3 only when excess PbI 2 is present. Both MAPbI 3 and PbI 2 films show a strong preferred lattice orientation on smooth substrates, while on rougher substrates, this orientation is disrupted. Furthermore, these results are interpreted as excess PbI 2 frustrating the diffusion of MAI in the film, which would otherwise disrupt the preferred orientation, pointing to a notable difference in lattice orientation arising from processing technique and conditions.

Deposition↗

Investigating Local Carrier Dynamics in PERC Patterned CdTe Solar Cells

Remarkable progress has been achieved in CdTe photovoltaics (PVs) to further improve cell performance while reducing manufacturing costs. Researchers optimized the front contact that leads the short-circuit current density (J sc ) over 31mA/cm 2 (e.g., (Zn, Mg)O buffer layer and/or alloying CdTe with Se). Reese et al. reported an open-circuit voltage (V oc ) over 1 V with group-V doped single crystal, showing the feasibility of increasing V oc in CdTe PV that is fixed to less than 900 mV in most cases. Recent studies suggested that the V oc improvement in polycrystalline CdTe PVs requires well-passivated back contact. One possible strategy is to use CdMgTe alloy (E g > 1.8 eV), where the band-gap offset (ΔE CB ≈ 0.2 eV) reflects minority carrier electrons, thereby decreasing surface recombination. Another strategy is to utilize a stable Al 2 O 3 layer as an electron reflector; experimental works confirmed the improved performance with a conformal Al 2 O 3 layer. In this configuration, the precise control of Al 2 O 3 (≈1 nm) over the entire CdTe layer is essential because the J sc greatly depends on the tunneling current. While promising, both CdMgTe and Al 2 O 3 passivation on CdTe introduce unfavorable valence band offset that blocks the hole transport. Kephart et al. proposed a patterned passixc vation layer (≈ 20 nm Al 2 O 3 ) with point contacts (≈ 3 μm in diameter) that extract hole carriers. This configuration is similar to the passive emitter and rear contact (PERC) design that has been extensively studied in Si PVs. While remarkably high carrier lifetime and photoluminescence (> 10 X) were measured, consistent improvement in V oc and efficiency in this CdTe PERC were not yet observed. At this time, it is unclear how the surface potential is distributed in the presence of patterned Al 2 O 3 reflectors and how this additional field impacts the PV performance for Cu-doped and group-V doped CdTe PERC devices. To tackle this challenge, we develop robust nanofabrication and characterization platform to study CdTe PERC devices consisting of a patterned Al 2 O 3 layer on CdSe( 1-x )Te x (Cu-doped, GrV-doped; x = 0 to 1; CST). First Solar supplies high-quality CST materials. The dark and light I-Vs under 1-sun illumination are extracted for a series of each set of devices. We perform quantitative and qualitative PV analysis for a series of Cu-doped and Gr-V doped PERC devices, showing notably different V oc changes for GrV-doped compared to Cu-doped PERC devices. This project attempts to produce individual contacts on single grains and grain boundaries to measure lateral transport. As a model system, we use a CdSe( 1-x )Te x film on glass prepared by a colossal grain growth (CGG) technique at National Renewable Research Laboratories (NREL). Our preliminary results confirm that intergranular transport is hindered by the electrical barrier formed near grain boundaries. The PERC fabrication and the lateral transport measurement platform developed in this project can easily be applied to other types of advanced CdSe( 1-x )Te x architectures to better understand local photocarrier transport, in turn, providing the fundamental knowledge to improve the performance of CdTe PVs.

14 SOLAR ENERGY↗

Removal of phosphorus using biochar derived from Fenton sludge: Mechanism and performance insights

Abstract A phosphorus removal biochar adsorbent was prepared from Fenton sludge. The adsorption process was optimized, and its phosphorus adsorption mechanism was discussed. It was found that the phosphorus adsorption performance of biochar prepared from single Fenton sludge (FBC‐400) was better than that of co‐pyrolysis of Fenton sludge and bamboo powder. The optimum condition was that Fenton sludge pyrolyzed at 400°C (FBC‐400). FBC‐400 had a larger specific surface area than that prepared by co‐pyrolysis with bamboo powder. And the high content of iron element could provide a higher surface charge of the biochar, thereby increasing the electrostatic adsorption of phosphorus onto FBC‐400. The phosphorus adsorption was highly pH dependent by FBC‐400, which can enhance electrostatic adsorption and increase adsorption capacity in acidic conditions. The effect of coexisting anion on adsorption performance was mainly affected by CO 3 2− , reducing the adsorption capacity by at least 49%, whereas other anions had no obvious interference. The adsorption process of FBC‐400 accorded with the pseudo‐second‐order kinetic model and the Langmuir model, which indicated that the adsorption process was monolayer adsorption and mainly chemical adsorption, and the maximum saturated phosphorus adsorption capacity was 8.77 mg g −1 . The mechanisms for phosphorus adsorption were electrostatic adsorption and inner‐sphere complexing. 1 M NaOH was used for desorption, and the adsorption capacity remained at 81% in the fifth cycle. Practitioner Points The Fenton sludge biochar usage as an adsorbent could be a win‐win strategy to convert waste biomass to valuable ‐ product. The adsorption process accorded with the Langmuir model, the maximum phosphorus adsorption capacity was 8.77 mg/g at 25°C. The adsorption mechanisms were electrostatic adsorption and inner‐sphere complexing. 1M NaOH was used for desorption, and the adsorption capacity remained at 81% in the fifth cycle.

Liu, Yanfang↗

Nuclear charge densities in spherical and deformed nuclei: Toward precise calculations of charge radii

Precise measurements of atomic transitions affected by electron-nucleus hyperfine interactions offer sensitivity to explore basic properties of the atomic nucleus and study fundamental symmetries, including the search for new physics beyond the standard model of particle physics. Specifically, such measurements, augmented by atomic and nuclear calculations, will enable extraction of the higher-order radial moments of the charge-density distribution in spherical and deformed nuclei. The new data impose higher precision requirements on a theoretical description. The nuclear charge density is composed of the proton point distribution folded with the nucleonic charge distributions. The latter induce subtle relativistic corrections due to the coupling of nucleon magnetic moments with the nuclear spin-orbit density. Additional corrections come from the effect of center-of-mass projection. We assess the precision of nuclear charge density calculations by studying the behavior of relativistic and center-of-mass motion corrections to the second and fourth charge radial moments. Special attention has been paid to the magnetic spin-orbit density associated with the local variations of the spin-orbit current. The calculations for semimagic and open-shell nuclei are performed in the framework of self-consistent mean-field theory using quantified energy density functionals and density-dependent pairing forces. We used the general expression for the spin-orbit form factor that is valid for spherical and deformed nuclei. We studied the impact of various correction terms on the charge radii, fourth radial moments, diffraction radii, and surface thickness of spherical and deformed nuclei. The spin-orbit corrections to charge radial moments and surface thickness show strong shell fluctuations which can make an appreciable effect when aiming at high-precision predictions of isotopic shifts. The inclusion of relativistic and center-of-mass corrections impacts the quality of energy density functionals optimized to charge radii data. To establish reliable constraints on the existence of new forces from isotope shift measurements, precise calculations of nuclear charge densities of deformed nuclei are needed. The proper inclusion of the spin-orbit charge density and other correction terms is essential when aiming at extraction of subtle effects which become particularly visible in isotopic trends. It is also important when developing high-quality nuclear energy density functionals optimized using heterogeneous datasets involving absolute charge radii, differential charge radii, and charge form factor properties deduced from electron-scattering data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗