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At least 1,009 records · Page 56

Binary pseudorandom array test standard optimized for characterization of large field-of-view optical interferometers

Recently, a technique for calibrating the modulation transfer function (MTF) of a broad variety of metrology instrumentation has been demonstrated. This technique is based on test samples structured as one-dimensional binary pseudo-random (BPR) sequences and two-dimensional BPR arrays (BPRAs). The inherent power spectral density of BPR gratings (sequences) and arrays has a deterministic white-noise-like character that allows direct determination of the MTF with uniform sensitivity over the entire spatial frequency range and field-of-view of an instrument. As such, the BPR samples satisfy the characteristics of a test standard: functionality, ease of specification and fabrication, reproducibility, and low sensitivity to manufacturing error. Here we discuss our recent developments directed to the optimization of the sample design, fabrication, application, and data processing procedures, suitable for thorough characterization of large aperture optical interferometers. Compared with the previous coded-aperture based design, the improved, 'highly randomized' BPRA pattern of the new test standard provides better accuracy and reliability of instrument MTF and aberration characterization, and enables operation optimization of large aperture optical interferometers. We describe the pattern generation algorithm and tests to verify the compliance to desired BPRA topography. The data acquisition and analysis procedures for different applications of the technique are also discussed.

Yashchuk, Valeriy V.↗

Performance and Stability Characterization of the ICARUS Light Detection System

The ICARUS detector, a key component of the Short Baseline Neutrino (SBN) Program at Fermilab, consists of two identical T300 modules filled with liquid argon. It is equipped with a Light Detection System (LDS) based on 360 8-inch Hamamatsu R5912-MOD photomultiplier tubes (PMTs) arranged behind the wire planes to collect Vacuum Ultraviolet (VUV, $\sim$ 128 nm) scintillation light. Operating under cryogenic conditions ( $\sim$ 87 K), the LDS is essential for determining the event start time (t0) with nanosecond precision for beam spill synchronization, improving longitudinal spatial resolution, and contributing to the event trigger and cosmic-ray mitigation. The performance of the LDS was investigated addressing both hardware and data analysis aspects. Following a progressive degradation in PMT gain observed during operations at FNAL, systematic gain measurements were first carried out from room temperature down to low temperatures. The results show stable performance at room temperature but a significant, irreversible reduction in gain at low temperatures. Based on these findings, a series of mitigation strategies were implemented in the ICARUS detector to preserve PMT performance and ensure reliable cryogenic operation. Currently, ongoing waveform analysis of the PMT signals is being performed to characterize signal shape, charge integration, and timing properties, aiming to refine and improve the agreement between experimental data and Monte Carlo simulations.

Saia, Clara [U. Catania (main); INAF, Catania; Cat↗

Surface heat flux feedback controlled impurity seeding experiments with Alcator C-Mod's high-Z vertical target plate divertor: performance, limitations and implications for fusion power reactors

The Alcator C-Mod team has recently developed a feedback system to measure and control surface heat flux in real-time. The system uses real-time measurements of surface heat flux from surface thermocouples and a pulse-width modulated piezo valve to inject low-Z impurities (typically N 2 ) into the private flux region. It has been used in C-Mod to mitigate peak surface heat fluxes >40 MW m -2 down to <10 MW m -2 while maintaining excellent core confinement, H 98 > 1. While the system works quite well under relatively steady conditions, use of it during transients has revealed important limitations on feedback control of impurity seeding in conventional vertical target plate divertors. In some cases, the system is unable to avoid plasma reattachment to the divertor plate or the formation of a confinement-damaging x-point MARFE. This is due to the small operational window for mitigated heat flux in the parameters of incident plasma heat flux, plasma density, and impurity density as well as the relatively slow response of the impurity gas injection system compared to plasma transients. Given the severe consequences for failure of such a system to operate reliably in a reactor, there is substantial risk that the conventional vertical target plate divertor will not provide an adequately controllable system in reactor-class devices. Finally, these considerations motivate the need to develop passively stable, highly compliant divertor configurations and experimental facilities that can test such possible solutions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Anisotropic thermal transport in bulk hexagonal boron nitride

Hexagonal boron nitride (h-BN) has received great interest in recent years as a wide band-gap analog of graphene-derived systems along with its potential in a wide range of applications, for example, as the dielectric layer for graphene devices. However, the thermal transport properties of h-BN, which can be critical for device reliability and functionality, are little studied both experimentally and theoretically. The primary challenge in the experimental measurements of the anisotropic thermal conductivity of h-BN is that typically the sample size of h-BN single crystals is too small for conventional measurement techniques, as state-of-the-art technologies synthesize h-BN single crystals with lateral sizes only up to 2.5 mm and thicknesses up to 200 μm. Recently developed time-domain thermoreflectance (TDTR) techniques are suitable to measure the anisotropic thermal conductivity of such small samples, as it only requires a small area of 50 × 50 μm 2 for the measurements. Accurate atomistic modeling of thermal transport in bulk h-BN is also challenging due to the highly anisotropic layered structure. Here we conduct an integrated experimental and theoretical study on the anisotropic thermal conductivity of bulk h-BN single crystals over the temperature range of 100–500 K using TDTR measurements with multiple modulation frequencies and a full-scale numerical calculation of the phonon Boltzmann transport equation starting from first principles. Our experimental and numerical results compare favorably for both the in-plane and the through-plane thermal conductivities. We observe unusual temperature dependence and phonon-isotope scattering in the through-plane thermal conductivity of h-BN and elucidate their origins. Here, this article not only provides an important benchmark of the anisotropic thermal conductivity of h-BN, but also develops fundamental insight into the nature of phonon transport in this highly anisotropic layered material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Robotics for Energy Infrastructure Construction on Earth and Beyond: Pilot Study Exploring Level 3-4 Semi-Autonomous Installation of a Reduced-Scale Photovoltaic Power Plant Prototype: Preprint

There is a growing need to build energy infrastructure at massive scale on both Earth and in space. On Earth, increasing electricity demand from applications such as AI data centers is driving rapid expansion of power systems, while in space, long-duration missions such as lunar operations require reliable and resilient energy infrastructure that can be deployed quickly. These needs outpace the capabilities of conventional construction methods. Robotic construction offers a path to faster, lower-cost, and more consistent deployment, yet most existing approaches focus on automating individual tasks rather than end-to-end assembly. The Industrialized Construction Innovation (ICI) team at the National Laboratory of the Rockies (NLR), in collaboration with the Colorado School of Mines, has been investigating robotics and automation strategies for rapid end-to-end energy infrastructure construction. This paper presents a pilot study demonstrating level 3-4 semi-autonomous, end-to-end robotic assembly of a reduced-scale photovoltaic power plant prototype under terrestrial conditions. The approach combines hardware redesign of photovoltaic components for robotic compatibility, discrete-event and physics-based robotic simulations in synthetic environments, and sim-to-real deployment to execute end-to-end robotic assembly of[NM1.1][NM1.2] tracking components, structural members, photovoltaic modules, and embedded electrical connections. The pilot identifies key limitations like tolerance management, perception and localization, end effector capability, fastening methods, and multi-physics simulation fidelity, that must be addressed to enable end-to-end robotic assembly of full-scale energy infrastructure. The study highlights how these insights inform scaling strategies for terrestrial energy infrastructure and adaptation to unstructured and extreme environments, including off-world scenarios such as robotic assembly of vertical tall lunar towers.

14 SOLAR ENERGY↗

Aeroacoustic Assessment of Wind Plant Controls

The Aeroacoustic Assessment project aims to quantify changes in aeroacoustic noise generation by a utility scale wind turbine operating under imposed yaw offsets common for wake steering and wind plant control strategies. Active plant control utilizing wake deflection control strategies have been shown experimentally and computationally to reliably produce 1-2% of additional annual energy production (AEP) without significant changes in turbine structural loads, the potential impact on aeroacoustic emissions has yet to be quantified or completely understood. Yawed operation of a wind turbine changes the three-dimensional aerodynamic interaction between the rotor blades and the incoming atmospheric flow, leading to changes in noise generation. This work quantifies the extent to which active control induces additional aeroacoustic emissions from additional separation and other flow interaction dynamic effects. Given public concerns about wind turbine noise and the need for observational data required for regulators to establish noise restrictions, we must understand potential acoustic emissions resulting from active control prior to commercial deployment and the development of practical noise reduction methods and technologies. The work outlined in this report details the new aeroacoustic measurement capability developed at NREL and its application to making full-field observations of noise from a utility-scale wind turbine. Preliminary noise modeling with the aeroacoustics module in OpenFAST helped to establish the design of the experiment, specifically targeting the noise observed at observers distributed around the DOE-owned GE 1.5 MW wind turbine. Low-frequency and infrasound measurement capability implemented in this project establish an operational baseline for the wind turbine, setting the stage for future control, rotor blade, and turbine design research.

17 WIND ENERGY↗

Provenance–aware workflow for data quality management and improvement for large continuous scientific data streams

Data quality assessment, management and improvement is integral part of any big data intensive scientific research to ensure accurate, reliable and reproducible science discoveries. The task of maintaining the quality of data, however, is non-trivial and pose a challenge for a program like Department of Energy’s Atmospheric Radiation Measurement (ARM) that collects data from hundreds of instruments across the world,and distributes thousands of streaming data products that are continuously growing in near-real-time in an archive 1.7 Petabyte in size and growing. We present a computational data processing workflow to collect the data quality issue via an easy and intuitive web-based portal that allows reporting of any quality issues for any site, facility or instruments at a granularity down to individual variable in the data files. Portal allows instrument specialists and scientists to provide corrective actions in form of symbolic equation. A parallel processing framework applies the data improvement to large volume of data in efficient parallel environment, while optimizing data transfer and file I/O operations. Corrected files are systematically versioned and archived. A provenance tracking module tracks and records any change made to the data during its entire life cycle which are communicated transparently to the scientific users. Developed in Python using open source technologies, software architecture enables efficient and fast management and improvement of data in an operational data center environment.

Kumar, Jitendra↗

Modeling and control of cascaded bridgeless multilevel rectifier under unbalanced load conditions

The goal of this project is to model and control a novel unidirectional cascaded multilevel bridgeless rectifier as an active front end in medium and high voltage applications. This topology has many advantages over a conventional cascaded H-bridge rectifier, such as lower implementation cost, higher reliability, and greater flexibility with similar power quality. The complete design process of the proposed converter is developed step by step in order to meet all the desired objectives. The steady-state mathematical model is used to develop a method for the voltage balancing of dc cells. Power factor analysis is discussed to mathematically derive requirements for the number of partially controlled and fully controlled H-bridges in the proposed H-bridge converter. Power loss, efficiency, and cost comparison studies between the traditional cascaded H-Bridge converter and the proposed bridgeless converter demonstrate the advantages. After exploring various well-established control methods, a novel control strategy is proposed to achieve dc voltage balancing, fast and robust grid synchronization, power factor correction, and elimination of zero crossing current distortion under both balanced and unbalanced load conditions. The converter can also be used for reactive power compensation in a grid tied power system if a sufficient number of fully controlled H-bridge modules are included. Processor-In-the-Loop (PIL) simulation has been the utilized to validate the performance of discrete control structure. Simulation and experimental results validate the models and control method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Digital Maskless Photolithographic Patterning of DNA-Functionalized Poly(ethylene glycol) Diacrylate Hydrogels with Visible Light Enabling Photodirected Release of Oligonucleotides

Soft biomaterials possessing structural hierarchy have growing applications in lab-on-chip devices, artificial tissues, and micromechanical and chemomechanical systems. The ability to integrate sets of biomolecules, specifically DNA, within hydrogel substrates at precise locations could offer the potential to form and modulate complex biochemical processes with DNA-based molecular switches in such materials and provide a means of creating dynamic spatial patterns, thus enabling spatiotemporal control of a wide array of reaction-diffusion phenomena prevalent in biological systems. In this paper, we develop a means of photopatterning two-dimensional DNA-functionalized poly(ethylene glycol) diacrylate (PEGDA) hydrogel architectures with an aim toward these applications. While PEGDA photopatterning methods are well-established for the fabrication of hydrogels, including those containing oligonucleotides, the photoinitiators typically used have significant crosstalk with many UV-photoswitchable chemistries including nitrobenzyl derivatives. We demonstrate the digital photopatterning of PEGDA-co-DNA hydrogels using a blue light-absorbing (470 nm peak) photoinitiator system and macromer comprised of camphorquinone, triethanolamine, and poly(ethylene glycol) diacrylate ($M$ n = 575) that minimizes absorption in the UV-A wavelength range commonly used to trigger photoswitchable chemistries. We demonstrate this method using digital maskless photolithography within microfluidic devices that allows for the reliable construction of multidomain structures. The method achieves feature resolutions as small as 25 μm, and the resulting materials allow for lateral isotropic bulk diffusion of short single-stranded (ss) DNA oligonucleotides. Finally, we show how the use of these photoinitiators allows for orthogonal control of photopolymerization and UV-photoscission of acrylate-modified DNA containing a 1-(2-nitrophenyl) ethyl spacer to selectively cleave DNA from regions of a PEGDA substrate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

3D nanolithography with metalens arrays and spatially adaptive illumination

The growing demand for advanced materials, miniaturized devices and integrated microsystems calls for the reliable fabrication of complex, multiscale, three-dimensional (3D) architectures, a need increasingly addressed through light-based and laser-based processes. However, owing to the field-of-view (FOV) limitations of conventional imaging optics, existing 3D laser nanofabrication techniques face fundamental challenges in throughput, proximity error and stitching defects on the path to scaling. Here, in this study, we present a scalable 3D nanofabrication platform that uses a metalens-generated focal spot array to parallelize two-photon lithography (TPL) beyond centimetre-scale write field areas. Metalenses are ideally suited for producing submicron-scale focal spots for high-throughput nanolithography, as they uniquely feature large numerical apertures (NAs), immersion media compatibility and large-scale manufacturability. We experimentally demonstrate a printing system that uses a 12-cm 2 metalens array to produce more than 120,000 cooperative focal spots, corresponding to a throughput exceeding 10 8 voxels s −1 . By programmatically patterning the focal spot array using a spatial light modulator (SLM), an adaptive parallel printing strategy is developed for precise greyscale linewidth modulation and choreographed printing of semiperiodic and fully aperiodic 3D geometries. We demonstrate parallel printing of replicated microstructures (>50 M microparticles per day), centimetre-scale 3D architectures with feature sizes down to 113 nm, and photonic and mechanical metamaterials. This work demonstrates the potential of 3D nanolithography towards wafer-scale production, showing how TPL could be used at scale for applications in microelectronics, biomedicine, quantum technology and high-energy laser targets.

Materials science↗

Understanding the Mechanism of Light and Elevated Temperature Induced Degradation of p-type Silicon Solar Cells (Final Report)

Light- and elevated-temperature-induced degradation (LeTID) was first discovered in multicrystalline Si (mc-Si) solar cells and was initially attributed to metal impurities. Later, LeTID was reported in Czochralski (Cz) and float-zone (FZ) Si, and is considered as an important efficiency loss mechanism in p-type passivated emitter rear contact (p-PERC) Cz Si solar cells. LeTID causes ~10% relative and permeant efficiency losses in these cells in warmer climate regions where the module temperature is > 50 °C. Unlike light-induced degradation (LID), which is also observed in p-PERC cells, LeTID is slower and takes weeks to months in the field to saturate. Another difference compared to LID is that regeneration in LeTID proceeds very slowly, and field regeneration could take > 25 years — essentially the life of the module. Unlike B-O defects that are responsible for LID, neither B nor O impurities are directly involved in LeTID. LeTID appears to be unique to p-type Si, and is also observed in Ga-doped Si. Currently, most experimental evidence relates LeTID to the injection of hydrogen present in the dielectric surface passivation layers, such as SiN x and Al 2 O 3 , into the monocrystalline Si (c-Si) bulk during the fast-firing step. The involvement of hydrogen is further strengthened by controlled studies that show that increasing the amount of hydrogen in the dielectric during fast-firing increases the degree of LeTID. Similar to LID, a regeneration process has been discovered for LeTID. Regeneration of LeTID defects occurs when samples are exposed to 2–4 Suns illumination at elevated temperatures of 140–220 °C for 2–15 hr. Given the slower kinetics of LeTID and sample regeneration compared to LID, this poses a challenge for the manufacturing and field reliability of p-PERC cells, which will be the leading photovoltaic technologies over the next decade. Therefore, there is a need to understand LeTID and develop strategies to mitigate this effect. The defect responsible for LeTID has been extensively studied with over 100 publications, but direct spectroscopic evidence of this defect’s structure is lacking. Without an atomistic understanding of the LeTID defect, it is difficult to assess the long-term efficacy of the current industrial mitigation strategies. This, in turn, has implications on energy production for tens of gigawatts of these cells that will be deployed yearly worldwide. Using electron paramagnetic resonance, we identified a defect associated with LeTID with a g-value of 2.006, which we attribute to an Si dangling bond in an extended defect such as a vacancy agglomerate with H possibly within or in close vicinity. These vacancy agglomerates are likely created during the firing process, during which time H atoms are also injected into the bulk from the hydrogenated SiN x dielectric layer. Our atomistic-level insight shows that the LeTID defect can be mitigated by targeted intrinsic defect engineering of the c-Si material through a slower pull rate of the Cz ingot or 1000 °C oxygen ambient processing of the Si wafer to reduce the vacancy concentration. This project was a collaborative effort between the Colorado School of Mines and the National Renewable Energy Laboratory.

14 SOLAR ENERGY↗

Assessing MP2 frozen natural orbitals in relativistic correlated electronic structure calculations

The high computational scaling with the basis set size and the number of correlated electrons is a bottleneck limiting applications of coupled cluster algorithms, in particular for calculations based on two- or four-component relativistic Hamiltonians, which often employ uncontracted basis sets. This problem may be alleviated by replacing canonical Hartree–Fock virtual orbitals by natural orbitals (NOs). Here, in this paper, we describe the implementation of a module for generating NOs for correlated wavefunctions and, in particular, second order Møller–Plesset perturbation frozen natural orbitals (MP2FNOs) as a component of our novel implementation of relativistic coupled cluster theory for massively parallel architectures [Pototschnig et al. J. Chem. Theory Comput. 17, 5509, (2021)]. Our implementation can manipulate complex or quaternion density matrices, thus allowing for the generation of both Kramers-restricted and Kramers-unrestricted MP2FNOs. Furthermore, NOs are re-expressed in the parent atomic orbital (AO) basis, allowing for generating coupled cluster singles and doubles NOs in the AO basis for further analysis. By investigating the truncation errors of MP2FNOs for both the correlation energy and molecular properties—electric field gradients at the nuclei, electric dipole and quadrupole moments for hydrogen halides HX (X = F–Ts), and parity-violating energy differences for H 2 Z 2 (Z = O–Se)—we find MP2FNOs accelerate the convergence of the correlation energy in a roughly uniform manner across the Periodic Table. It is possible to obtain reliable estimates for both energies and the molecular properties considered with virtual molecular orbital spaces truncated to about half the size of the full spaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

System-Level Thermal Management and Reliability of Automotive Electronics: Goals and Opportunities Using Phase-Change Materials

Abstract Electronic packaging for automotive applications are at particular risk of thermomechanical failure due to the naturally harsh conditions it is exposed to. With the rise of electric and hybrid electric vehicles (EVs and HEVs), combined with a desire to miniaturize, the challenge of removing enough heat from electronic devices in automotive vehicles is evolving. This paper closely examines the new challenges in thermal management in various driving environments and aims to classify each existing cooling method in terms of performance. Particular focus is placed upon emerging solutions regarded to hold great potential, such as phase-change materials (PCMs). PCMs have been regarded for some time as a means of transferring heat quickly away from the region with the electronic components and are widely regarded as a possible means of carrying out cooling in large scale from small areas, because of their high latent heat of fusion, high specific heat, temperature stability, and small volume change during phase change, etc. They have already been utilized as a method of passive cooling in electronics in various ways, but their adoption in automotive power electronics, such as in traction inverters, has yet to be fulfilled. A brief discussion is made on some of the potential areas of application and challenges relating to more widespread adoption of PCMs, with reference to a case study using computational model of a commercially available power module used in automotive applications.

Engineering↗

Towards high data-rate diffusive molecular communications: A review on performance enhancement strategies

Diffusive molecular communications (DiMC) have recently gained attention as a candidate for nano- to micro- and macro-scale communications due to its simplicity and energy efficiency. As signal propagation is solely enabled by Brownian motion mechanics, DiMC faces severe inter-symbol interference (ISI), which limits reliable and high data-rate communications. Herein, recent literature on DiMC performance enhancement strategies is surveyed; key research directions are identified. Signaling design and associated design constraints are presented. Here, studies on fundamental information theoretic limits of DiMC channel are reviewed. Classical and novel transceiver designs are discussed with an emphasis on methods for ISI mitigation and performance-complexity tradeoffs. Key parameter estimation strategies such as synchronization and channel estimation are considered in conjunction with asynchronous and timing error robust receiver methods. Finally, source and channel coding in the context of DiMC is presented.

42 ENGINEERING↗

Decomprolute is a benchmarking platform designed for multiomics-based tumor deconvolution

Tumor deconvolution is a reliable way to disentangle the diverse cell types that comprise solid tumors. To date, however, both the algorithms developed to deconvolve tumor samples, and the gold standard datasets used to assess the algorithms are geared toward the analysis of gene expression (e.g., RNA-seq) rather than protein levels in tumor cells. While gene expression is less expensive to measure, protein levels provide a more accurate view of immune markers. To facilitate the development as well as improve the reproducibility and reusability of multi-omic deconvolution algorithms, we introduce Decomprolute, a Common Workflow Language framework that leverages containerization to compare tumor deconvolution algorithms across multiomic data sets. Decomprolute incorporates the large-scale multiomic data sets produced by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), which include matched mRNA expression and proteomic data from thousands of tumors across multiple cancer types to build a fully open-source, containerized proteogenomic tumor deconvolution benchmarking platform. The platform consists of modular architecture and it comes with well-defined input and output formats at each module. As a result, it is robust and extendable easily with additional algorithms or analyses. The platform is available for access and use at http://pnnl-compbio.github.io/decomprolute.

60 APPLIED LIFE SCIENCES↗

More Than Recycling: The Importance of Multiple Metrics for a Circular Economy for PV in the Energy Transition

Energy transition to carbon-free electricity is a crucial pillar of the Circular Economy. Renewable energy reduces environmental impacts and decarbonizes the production of other goods. But, manufacturing renewable energy sources, such as photovoltaic (PV) modules, require energy inputs that are currently carbon intensive. So, how do we decarbonize and circularize these critical technologies to achieve a sustainable energy transition? This work proposes that effective capacity-the installed capacity accounting for degradation rates and failures-is a critical metric to evaluate renewable energy technologies on the path toward circular economy and energy transitions. Our analyses also emphasize the importance of examining a suite of metrics incorporating mass and energy flows to identify potential tradeoffs and inform design or lifecycle management decisions holistically.

bifacial↗

Circular Economy for Photovoltaics in Service of Energy Transition

The challenge of energy transition is immediate and immense; current projections target 75 TW of photovoltaics (PV) capacity by 2050. While any transition to renewable energy technology is preferable to the current fossil-based system, it is ideal to improve the sustainability of PV to minimize negative environmental and social impacts. Circular economy (CE) has been proposed as a method to improve the sustainability of PV, especially for emerging materials like perovskites. CE is a set of actions, principles, and systems which aim to design out waste and keep products and materials in use, to reduce environmental impacts and enable sustainable development. At the most basic level, CE is "reduce, reuse, recycle", the R-actions, in ranked order. CE of a PV technology can be metricized in a variety of ways, such as the Material Circularity Indicator (Smith and Jones, Ellen MacArthur Foundation, 2019) or recycling rates. Unfortunately, standard CE metrics have several shortcomings for measuring renewable energy technologies in the context of deployment for energy transition (Figge 2018, Saidani 2019): 1) Only measure mass flows; 2) De-prioritization of the use phase in favor of mass circularity when scoring; and 3) Tight focus on a single product scale The use phase and energy flows of PV are key to energy transition, and therefore need to be quantified. Additionally, correlating product-scale to system-scale is necessary for quantifying the environmental impacts of energy transition. Life Cycle Assessment (LCA) can address some of these concerns, but also focuses on a single product scale and has trouble capturing the dynamics of system-scale energy transition, such as the interaction of module lifetime with manufacturing demands for energy transition deployment schedules. Therefore, we developed an open-source Python-based system dynamics model to quantify the mass, energy and carbon impacts of CE R-actions for PV technologies in the energy transition; PV in the CE (PV ICE) (Ovaitt & Mirletz 2021). The tool captures supply chains from material extraction through end of life, incorporating 5 circular end of life pathways. PV ICE takes in any evolving bill of materials, module properties and deployment schedule to support researchers and decision makers with data-backed insights. In this work, we quantify and compare proposed CE sustainable PV module designs and lifecycle management strategies, spanning currently commercialized technologies, government and industry technology targets, and several low Technology Readiness Level (TRL) emerging PV technologies, including perovskites. Our analyses capture the projected evolutions of lifetime, efficiency and material circularity of these PV technologies, as well as their material supply chains. Our analyses emphasize the importance of examining a suite of metrics to identify priorities and tradeoffs, and inform design or lifecycle management decisions holistically. Previous analyses have demonstrated the central importance of PV module lifetime to support energy transition while minimizing impacts. High levels of material circularity (>90%) enable minimizing lifecycle wastes, can reduce virgin material demands if paired with improving efficiency, but demonstrate tradeoffs in energy return on investment. In the fervor of new material and technology development, it is important to remember that CE is not the end goal; decarbonization and energy transition are the end goal. CE should be used in service to improve the sustainability of PV, and R-actions evaluated for their usefulness and efficacy to this end.

carbon↗

Properties of water surface discharge at different pulse repetition rates

The properties of water surface discharge plasma for variety of pulse repetition rates are investigated. A magnetic pulse compression (MPC) pulsed power modulator able to deliver pulse repetition rates up to 1000 Hz, with 0.5 J per pulse energy output at 25 kV, was used as the pulsed power source. Positive pulse with a point-to-plane electrode configuration was used for the experiments. The concentration and production yield of hydrogen peroxide (H₂O₂) were quantitatively measured and orange II organic dye was treated, to evaluate the chemical properties of the discharge reactor. Experimental results show that the physical and chemical properties of water surface discharge are not influenced by pulse repetition rate, very different from those observed for under water discharge. The production yield of H₂O₂ and degradation rate per pulse of the dye did not significantly vary at different pulse repetition rates under a constant discharge mode on water surface. In addition, the solution temperature, pH, and conductivity for both water surface and underwater discharge reactors were measured to compare their plasma properties for different pulse repetition rates. The results confirm that surface discharge can be employed at high pulse repetition rates as a reliable and advantageous method for industrial and environmental decontamination applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗