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At least 433 records · Page 24

Autonomous platform for solution processing of electronic polymers

The manipulation of electronic polymers’ solid-state properties through processing is crucial in electronics and energy research. Yet, efficiently processing electronic polymer solutions into thin films with specific properties remains a formidable challenge. We introduce Polybot, an artificial intelligence (AI) driven automated material laboratory designed to autonomously explore processing pathways for achieving high-conductivity, low-defect electronic polymers films. Leveraging importance-guided Bayesian optimization, Polybot efficiently navigates a complex 7-dimensional processing space. In particular, the automated workflow and algorithms effectively explore the search space, mitigate biases, employ statistical methods to ensure data repeatability, and concurrently optimize multiple objectives with precision. The experimental campaign yields scale-up fabrication recipes, producing transparent conductive thin films with averaged conductivity exceeding 4500 S/cm. Feature importance analysis and morphological characterizations reveal key design factors. This work signifies a significant step towards transforming the manufacturing of electronic polymers, highlighting the potential of AI-driven automation in material science.

Wang, Chengshi [Argonne National Laboratory (ANL),↗

Data-driven reevaluation of f t values in superallowed β decays

We present a comprehensive reevaluation of the ft values in superallowed nuclear β decays crucial for the precise determination of V ud and low-energy tests of the electroweak standard model. It consists of the first, fully data-driven analysis of the nuclear β decay form factor, that utilizes isospin relations to connect the nuclear charged weak distribution to the measurable charge distributions. This prescription supersedes previous shell-model estimations, and allows for a rigorous quantification of theory uncertainties in f which is absent in the existing literature. Furthermore, our new evaluation shows an overall downward shift of the central values of f at the level of 0.01%.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Direct quarkonium production in DIS from a joint CGC and NRQCD framework

We compute the differential cross section for direct quarkonium production in high-energy electron-nucleus collisions at small 𝑥. Our computation is performed within the nonrelativistic QCD factorization formalism that separates the calculation into short distance coefficients and long distance matrix elements that depend on the color and spin of the state. We obtain the short distance coefficients of the production of the heavy quark pair within the framework of the color glass condensate effective field theory, which resums coherent multiple interactions of the heavy quark pair with the nucleus to all orders. Our results are expressed as the convolution of perturbatively calculable functions with multipoint lightlike Wilson line correlators. In the correlation limit, we establish the correspondence between our color glass condensate formulation with calculations employing the transverse momentum dependent (TMD) framework. We extend this correspondence by resumming kinematic power corrections within the improved TMD framework, which interpolates between the TMD formalism and 𝑘 ⊥ -factorization formalism. We present a detailed numerical analysis, focusing on 𝐽/𝜓 production in the kinematics accessible at the future Electron-Ion Collider, highlighting the importance of genuine higher-order saturation contributions when the electron collides with a large nucleus. Our results are also valid in the photoproduction limit where we expect the largest contribution from genuine higher-order saturation contributions which could be accessed in ultraperipheral collisions of relativistic heavy ions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Detection of translational noncrystallographic symmetry in Patterson functions

Detection of translational noncrystallographic symmetry (TNCS) can be critical for success in crystallographic phasing, particularly when molecular-replacement models are poor or anomalous phasing information is weak. If the correct TNCS is detected then expected intensity factors for each reflection can be refined, so that the maximum-likelihood functions underlying molecular replacement and single-wavelength anomalous dispersion use appropriate structure-factor normalization and variance terms. Here, an analysis of a curated database of protein structures from the Protein Data Bank to investigate how TNCS manifests in the Patterson function is described. These studies informed an algorithm for the detection of TNCS, which includes a method for detecting the number of vectors involved in any commensurate modulation (the TNCS order). The algorithm generates a ranked list of possible TNCS associations in the asymmetric unit for exploration during structure solution.

59 BASIC BIOLOGICAL SCIENCES↗

Exploring PV Circularity by Modeling Socio-Technical Dynamics of Modules’ End-of-Life Management

The circular economy (CE) tackles environmental and resource scarcity issues by maximizing value retention in the economy. The concept implies design strategies such as reducing the use of materials or improving products’ durability and end-of-life (EOL) strategies, for example, reusing products and components and recycling materials. With an estimated 80 million tons of global cumulative EOL photovoltaic (PV) modules, applying CE principles to the PV industry could alleviate resource scarcity issues while also providing economic benefits. However, transitioning to a CE may imply changes in organizations and consumer behaviors. In this context, assessment of CE strategies may require accounting for behavioral change, a requirement that methods from complex system science such as agent-based modeling meet. Thus, this paper uses an agent-based modeling (ABM) approach to study circularity in the photovoltaics supply chain. Four types of agents are represented in the ABM: PV owners, installers, recyclers, and manufacturers. Moreover, five possible EOL options – including three CE strategies – are modeled. Departing from traditional techno-economic analysis, the model includes techno-economic factors as well as social factors to model EOL management decisions. Results show that each dollar decrease in the recycling fees improves the recycling rate by roughly 1.1%. However, excluding social factors underestimates the effect that lower recycling prices have on material circularity.

agent-based modeling↗

A Compact, Single Stage, >1 kV Medium-Voltage Line Impedance Stabilization Network

This paper presents the design of a single-phase, single-stage line impedance stabilization network (LISN) for medium-voltage (MV) applications. More than 1 kV rated widebandgap (WBG) power semiconductor switches are increasingly utilized in new, emerging power electronics energy systems to improve power density and efficiency. However, due to inherently fast-switching speeds, WBG switch modules emit considerable electromagnetic interference (EMI) (e.g., common mode (CM) or differential mode (DM)). State-of-the-art offers standardized LISN solutions to validate and certify the new energy system for electromagnetic compatibility (EMC). However, most are for low voltage applications (i.e., < 1 kV). MV LISNs (i.e., > 1 kV) are rare until recently and literature does not provide sufficient guidelines for designing and characterizing such devices. It has been a critical challenge for many scientists and engineers to reliably certify the emerging MV energy systems (e.g., electric ships and aircraft). This paper addresses such a technology gap. Specifically, a CISPR 16-1-2 compliant 50Ω/50μH LISN with 1.5kV, 75A and 30MHz measurement capability has been proposed. Detailed performance study versus non-linear parasitic parameters variations in MV inductors and capacitors have been done. Based on new understandings, novel techniques to intuitively mitigate unwanted parasitic have been proposed to develop the proposed LISN successfully. Thorough characterization of important LISN parameters are presented and factors influencing them are analyzed. A rigorous analysis, experimental tests, and in-depth comparisons over state-of-the-art have been made to validate the effectiveness. This is done through the state-of-the-art 300kVA MV EMI testbed.

42 ENGINEERING↗

Leverage demand-side policies for energy security

Energy security is a top priority for governments, companies, and households because energy systems and the critical functions that they support are threatened by disruptions from wars, pandemics, climate change, and other shocks (1). More often than not, governments rely on policies focused on energy supply to enhance energy security while generally ignoring demand-side possibilities. Further, the indicators traditionally used to measure energy security are also tilted toward the supply side; this fails to capture the full spectrum of vulnerability to energy crises. Energy security assessments need to reflect the wider benefits of security related interventions more accurately. To that end, we develop a systematic approach to measuring the energy security impacts of policy interventions that explicitly considers energy demand (buildings, transport, and industry). Here, we determine that demand-side actions outperform conventional supply-side approaches at making countries more resilient. Energy demand links more directly than supply to the satisfaction of critical social functions and human well-being that are at the core of energy security. Yet, demand-side perspectives tend to be neglected or underrepresented in analysis and policy debates on energy security. Factors that contribute to this supply-side bias include the traditional sectoral organization of industries and policy institutions along fuels (coal, oil, and gas) and energy forms (electric utilities) as well as the decentralized and multivaried activities characteristic of energy demand (from vehicles to household appliances to manufacturing and more), which leads to a multitude of actors and institutional fragmentation. The basic fundamentals of energy systems and markets, where demand and supply are intricately linked, have also not yet risen from vague awareness to a central organizing principle among policy-makers for structuring the energy security discourse.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Optimizing Fast Charging and Wetting in Lithium-Ion Batteries with Optimal Microstructure Patterns Identified by Genetic Algorithm

To sustain the high-rate current required for fast charging electric vehicle batteries, electrodes must exhibit sufficiently high effective ionic diffusion. Additionally, to reduce battery manufacturing costs, wetting time must decrease. Both of these issues can be addressed by structuring the electrodes with mesoscale pore channels. However, their optimal spatial distribution, or patterns, is unknown. Herein, a genetic algorithm has been developed to identify these optimal patterns using a CPU-cheap proxy distance-based model to evaluate the impact of the added pore networks. Both coin-cell and pouch cell form factors have been considered for the wetting analysis, with their respective electrolyte infiltration mode. Regular hexagonal and mud-crack-like patterns, respectively, for fast charging and fast wetting were found to be optimal and have been compared with pre-determined, easier to manufacture, patterns. The model predicts that using cylindrical channels arranged in a regular hexagonal pattern is ∼6.25 times more efficient for fast charging as compared to grooved lines with both structuring strategies being restricted to a 5% electrode total volume loss. The model also shows that only a very limited electrode volume loss (1%–2%) is required to dramatically improve the wetting (5–20 times) compared to an unstructured electrode.

25 ENERGY STORAGE↗

Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction

Abstract Background West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement. Methods We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill. Results Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill. Conclusions Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases). Graphical Abstract

54 ENVIRONMENTAL SCIENCES↗

Enhanced lightning strike protection using vertically oriented carbon fiber melded with conventional carbon fiber-reinforced composite and its validation through damage analysis

Lightning strike protection (LSP) is one of the prime factors in aerospace and wind industries concerning safety, enhanced service life, and reduced downtime. To ensure better LSP, high electrical conductivity is required to dissipate the current, which is always a challenge for polymer composites due to the inherent insulating nature of the polymer matrix. Conventional carbon fiber-reinforced composites (CFRP) offer electrical conductivity in the planar direction while the vertical i.e. through-thickness conductivity still remains a challenge. Having been motivated by this fact, we have fabricated CFRP interleaved with vertically oriented CF (Z-fiber) for the lightning strike test (100 kA). A paint was applied to mimic the actual service condition of the composite laminates. We have prepared two Z-fiber composites: (a) Z-1 containing one Z-fiber layer on the top along with conventional CF layers and (b) Z-5 containing five interleaved Z-fiber layers and compared the properties with conventional CFRP (Z-0). Interestingly, even a single Z-fiber layer (Z-1) showed lower damage (visual damage diameter 22 mm) than Z-0 (visual damage diameter 26 mm). Z-5 displayed the lowest damage (visual damage diameter 16.7 mm), which was further confirmed by cross-sectional optical microscopy. Improved LSP was attributed to the higher through-thickness electrical conductivity in the case of Z-5 (9 times with respect to Z-0) reflecting a lower electrical anisotropy for Z-fiber composites. The residual mechanical property after the lightning test was analyzed through the flexural test, and the retention of flexural strength and modulus was 66% and 86%, respectively for Z-5 showing a significant improvement in comparison to Z-0 (>40% for both).

Saha, Subhabrata↗

Absorptive corrections to the forward elastic proton-proton analyzing power A N

In the RHIC Polarized Atomic Hydrogen Gas Jet Target (HJET) measurements of the protonproton analyzing power A N (t), absorptive corrections to the electromagnetic form factor were not considered in the data analysis. Recently, these corrections were evaluated theoretically. However, the results were presented in form of integral expressions which were calculated numerically. In this note, the expressions are simplified to make them more suitable for the HJET data analysis. Possible effect of the absorptive corrections in the A N (t) measurement is discussed.

43 PARTICLE ACCELERATORS↗

Tracking the Sun: Pricing and Design Trends for Distributed Photovoltaic Systems in the United States, 2022 Edition

Berkeley Lab’s annual Tracking the Sun report describes trends among grid-connected, distributed solar photovoltaic (PV) systems in the United States. The latest edition of the report focuses on systems installed through year-end 2021, and is based on data from roughly 2.5 million systems. New to the report this year is an expanded coverage of paired PV-plus-storage systems, including details on system design and pricing trends. The report describes trends related to: -Project characteristics, including system size, module efficiencies, prevalence of paired PV with storage, use of module-level power electronics, third-party ownership, mounting configurations, panel orientation, and non-residential customer segmentation ownership -Median installed-price trends, both nationally and by state, including preliminary data for first half of 2022 -Variability in pricing according to system size, state, installer, equipment type, and other factors, relying on both descriptive and econometric analysis

14 SOLAR ENERGY↗

Initial Delayed Critical Configuration of SHEBA I and Subcritical Measurements by Californium Source-Driven Noise Analysis

In September 1980, the initial delayed critical configuration of the Solution High-Energy Burst Assembly (SHEBA I) was assembled, and the US Department of Energy’s Oak Ridge National Laboratory (ORNL) staff performed near critical and subcritical measurements using the californium source-driven noise analysis (CSDNA) method at the Los Alamos National Laboratory (LANL) Critical Experiments Facility. An unreflected 56 cm outside diameter stainless-steel cylindrical tank was partially filled with uranyl fluoride solution (235U enrichment was 4.95 wt %) until delayed criticality was achieved. Then, measurements were performed for various fuel solution heights from delayed critical to 60% of the height required for delayed criticality. The stainless-steel tank had an inside diameter of 54.6 cm and a height of 105 cm and was partially (20–36.5 cm) filled with an aqueous solution of uranyl fluoride (with a density of 2.162 g/cm 3 ). The density of the uranium in solution was 1.042 g/cm 3 , and the solution had a H/U atomic ratio of 20.43. The tank had a 6.35 mm wall thickness and an axial reentrant tube with an inside diameter of 6.02 cm and wall thickness of 0.165 cm. The tank was essentially unreflected on the top and sides because it was in a thin metal shed. The reactivity of the near–delayed critical configuration was −10.4 cents, which corresponds to a k eff value of 0.99922. In addition to the CSDNA measurements, the prompt neutron decay constants were determined from break frequency noise analysis (BNFA) measurements. The subcritical neutron multiplication factors from CSDNA and BFNA compared extremely well. These data can be used as the basis of International Nuclear Criticality Safety Evaluation benchmark for the near-critical configuration, and the k eff values at various subcritical configurations can be used as subcritical benchmarks. Furthermore, the measured prompt neutron decay constants can be used as reactor physics benchmarks. This report documents the experimental information for the measurements performed so that, at a later date, researchers could perform the required uncertainty and calculational analyses and documentation to use these data for an International Criticality Safety Benchmark Evaluation Program (ICSBEP) or Nuclear Energy Agency benchmarks. The measured prompt neutron decay constants can be used as the basis of a benchmark for the International Reactor Physics Evaluation Program (IRPhEP). The data from these measurements are available from the ORNL Records Management Services Department, and the logbook is available from ICSBEP at Idaho National Laboratory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Temperature and dopant concentration effects on proton light quenching in rare-earth inorganic scintillators [Slides]

Rare-earth inorganic scintillators have characteristics that offer optimal detection qualities for space applications as long a quenching is considered; Incident proton and electron response was measured in four different rare-earth inorganic scintillators of interest; We observed: A temperature effect on quenching for GAGG type detectors. A dopant concentration/decay time effect on quenching for GAGG detectors; Extracting the Birks’ factor for future detectors will improve the analysis of data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Tracking the Sun: Pricing and Design Trends for Distributed Photovoltaic Systems in the United States (2023 Edition) [Slides]

Berkeley Lab’s annual Tracking the Sun report describes trends among grid-connected, distributed solar photovoltaic (PV) and paired PV+storage systems in the United States. For the purpose of this report, distributed solar includes residential systems, roof-mounted non-residential systems, and ground-mounted systems up to 5 MW-AC. Ground-mounted systems larger than 5 MW-AC are covered in Berkeley Lab’s companion annual report, Utility-Scale Solar. The latest edition of the report is based on 3.2 million systems installed through year-end 2022, representing more than 80% of systems installed to date. The report describes and discusses key trends related to: -Project characteristics, including system size, module efficiencies, prevalence of paired PV with storage, use of module-level power electronics, third-party ownership, mounting configurations, panel orientation, and non-residential customer segmentation ownership -Median installed-price trends, both nationally and by state -Variability in pricing according to system size, state, installer, equipment type, and other factors, relying on both descriptive and econometric analysis The report also includes a multi-variate regression analysis to estimate the effects of key pricing drivers for residential systems installed in 2022.

14 SOLAR ENERGY↗

Preparation and Qualification of Preproduction SSR2 Jacketed Cavities for PIP-II

The qualification of 325 MHz Single Spoke Resonators type 2 (SSR2) jacketed cavities to meet technical requirements represents a significant milestone in the development of the SSR2 cryomodules for the PIP-II Project at Fermilab. This poster reports the procedures and lessons learned in processing and preparing these cavities for horizontal cold testing prior to integration into a cavity string assembly, with a focus on addressing the field emission issues observed during the cold testing. A comprehensive root cause analysis identified critical fabrication, processing, and handling factors impacting field emission onset. New techniques were successfully developed and implemented to achieve field emission-free SSR2 cavities, and efforts were made to correlate radiation levels measured at the test stand with expected levels in the LINAC tunnel. Additionally, the evolution of field emission through assembly steps was thoroughly investigated, leading to a reassessment of design choices and enhancing our understanding of their effects on cavity performance.

Grassellino, L. [Fermilab]↗

Genesis Mission-Enabled Secure AI to Fortify Energy Process Safety (Genesis-SAFE)

Argonne National Laboratory is supporting the U.S. Department of Transportation’s (USDOT’s) Bureau of Transportation Statistics (BTS) with collaborative research on development and application of privacy preserving AI frameworks that leverage unmatched AI expertise and secure computing resources made available through the U.S. Genesis Mission1 . This research advances U.S. energy security goals by supporting a safe offshore energy industry with secure, domain-specific AI tools to analyze confidential industry datasets collected by BTS to rapidly improve identification of hazards, precursors, and systemic safety risks in high-risk operational environments. The staged, security-first approach begins with development and testing of Argonne’s Genesis Mission-enabled Secure AI to Fortify Energy Process Safety (Genesis-SAFE) framework within Argonne’s accredited secure computing enclave (ABLE) leveraging Argonne’s AI scientific assistant substrate (AISAC). Methods to build synthetic datasets were developed together with BTS for use in preparing synthetic datasets that can be used to validate data containment, governance, and security controls in the ABLE environment. Future research directions would focus on applying the Genesis-SAFE framework to CIPSEA-protected datasets entirely within ABLE to support confidentiality-preserving analysis of safety risks, trends, and contributing factors.

Kim, Hyekyung [Argonne National Laboratory (ANL), ↗

Mechanisms of Waterflood Inefficiency: Analysis of Geological, Petrophysical and Reservoir History, a Field Case Study of FWU (East Section)

The petroleum reservoir represents a complex heterogeneous system that requires thorough characterization prior to the implementation of any incremental recovery technique. One of the most commonly utilized and successful secondary recovery techniques is waterflooding. However, a lack of sufficient investigation into the inherent behavior and characteristics of the reservoir formation in situ can result in failure or suboptimal performance of waterflood operations. Therefore, a comprehensive understanding of the geological history, static and dynamic reservoir characteristics, and petrophysical data is essential for analyzing the mechanisms and causes of waterflood inefficiency and failure. In this study, waterflood inefficiency was observed in the Morrow B reservoir located in the Farnsworth Unit, situated in the northwestern shelf of the Anadarko Basin, Texas. To assess the potential mechanisms behind the inefficiency of waterflooding in the east half, geological, petrophysical, and reservoir engineering data, along with historical information, were integrated, reviewed, and analyzed. The integration and analysis of these datasets revealed that several factors contributed to the waterflood inefficiency. Firstly, the presence of abundant dispersed authigenic clays within the reservoir, worsened by low reservoir quality and high heterogeneity, led to unfavorable conditions for waterflood operations. The use of freshwater for flooding exacerbated the adverse effects of sensitive and migratory clays, further hampering the effectiveness of the waterflood. In addition to these factors, several reservoir engineering issues played a significant role in the inefficiency of waterflooding. These issues included inadequate perforation strategies due to the absence of detailed hydraulic flow units (HFUs) and rock typing, random placement of injectors, and uncontrolled injected fresh water. These external controlling parameters further contributed to the overall inefficiencies observed during waterflood operations in the east half of the reservoir. A detailed understanding of the mechanistic factors of inefficient waterflood operation will provide adequate insights into the development of the improved recovery technique for the field.

Morgan, Anthony (ORCID:0000000211519153)↗