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At least 415 records · Page 23

The PAU Survey: narrow-band photometric redshifts using Gaussian processes

Here, we study the performance of the hybrid template machine learning photometric redshift (photo- z ) algorithm delight , which uses Gaussian processes, on a subset of the early data release of the Physics of the Accelerating Universe Survey (PAUS). We calibrate the fluxes of the 40 PAUS narrow bands with six broad-band fluxes ( uBVriz ) in the Cosmic Evolution Survey (COSMOS) field using three different methods, including a new method that utilizes the correlation between the apparent size and overall flux of the galaxy. We use a rich set of empirically derived galaxy spectral templates as guides to train the Gaussian process, and we show that our results are competitive with other standard photometric redshift algorithms. delight achieves a photo- z 68th percentile error of σ 68 = 0.0081(1 + z ) without any quality cut for galaxies with i auto < 22.5 as compared to 0.0089(1 + z ) and 0.0202(1 + z ) for the bpz and annz 2 codes, respectively. delight is also shown to produce more accurate probability distribution functions for individual redshift estimates than bpz and annz 2. Common photo- z outliers of delight and bcnz 2 (previously applied to PAUS) are found to be primarily caused by outliers in the narrow-band fluxes, with a small number of cases potentially indicating spectroscopic redshift failures in the reference sample. In the process, we introduce performance metrics derived from the results of bcnz 2 and delight , allowing us to achieve a photo- z quality of σ 68 < 0.0035(1 + z ) at a magnitude of i auto < 22.5 while keeping 50 per cent objects of the galaxy sample.

79 ASTRONOMY AND ASTROPHYSICS↗

Effects of Photonic Curing Processing Conditions on MAPbI 3 Film Properties and Solar Cell Performance

Thermal annealing is the most used postdeposition materials processing method in laboratory research, but due to its slow speed and high energy cost, it is not compatible with the upscaling and commercialization of perovskite solar cell (PSC) manufacturing. Here, we adapt photonic curing (PC), which uses millisecond light pulses to deliver energy to the sample, to replace thermal annealing for crystallization of methylammonium lead iodide (MAPbI 3 ) films and rapid fabrication of PSCs. We study how PC conditions affect the outcome of MAPbI 3 conversion from the precursor to the crystalline perovskite phase by evaluating the films’ optical, crystalline, and morphological properties, as well as PSC performance. The results are understood using simulated film temperature profiles. We show that MAPbI 3 is readily converted under a wide range of PC conditions. While previous reports all used short pulses (<3 ms), we find that longer pulses produce more dense films and higher-performing PSCs. We achieve a champion power conversion efficiency in a PC-processed MAPbI 3 PSC of 11.26% under forward scan and 10.34% under reverse scan, with the processing time for the MAPbI 3 layer reduced by 30,000-fold, from 10 min to 20 ms. Using a 6 in. lamp, spatial uniformity tests show a cross-web efficiency variation of 5%. Our results indicate that using longer pulse lengths, >10 ms, is the best PC strategy for perovskite conversion, and PC is a promising annealing method for large-area, high-throughput PSC manufacturing.

14 SOLAR ENERGY↗

Assessing the coating implications of slurry formulations in NCMA and LFMP blend cathodes for lithium-ion batteries

This paper investigates the implications of slurry formulations and electrode processing on the performance of lithium-ion battery (LIB) cathodes, focusing on Nickel Cobalt Manganese Aluminum (NCMA) and Lithium Ferro Manganese Phosphate (LFMP) blends. Through a comprehensive examination of electrode processing steps, from material selection to coating application, we elucidate the critical role of processing parameters in shaping electrode morphology and electrochemical behavior. Rheological studies reveal the influence of slurry composition on viscosity and flow behavior, highlighting the importance of achieving optimal rheological properties for uniform coating deposition. Electrochemical characterization, including cyclic voltammetry and rate capability tests, unveils the electrochemical behavior of NCMA, LFMP, and their blend, showcasing the synergistic effects of material blending on battery performance. In conclusion, our findings underscore the intricate relationship between slurry formulation, electrode processing, and LIB performance, offering valuable insights for the design and optimization of high-performance electrode materials for next-generation batteries.

25 ENERGY STORAGE↗

Ancilla-assisted process tomography of a deployed fiber link

We perform ancilla-assisted process tomography over a deployed 1.6 km fiber-optic link using Bayesian inference, confirming a stable, high-fidelity polarization channel. Overall, our approach should offer value for in situ analyses of entanglement networks.

Rahman, Arefur [Arizona State University]↗

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N. One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an “intelligent” mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗

Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization

In an in transit setting, a parallel data producer, such as a numerical simulation, runs on one set of ranks M, while a data consumer, such as a parallel visualization application, runs on a different set of ranks N: One of the central challenges in this in transit setting is to determine the mapping of data from the set of M producer ranks to the set of N consumer ranks. This is a challenging problem for several reasons, such as the producer and consumer codes potentially having different scaling characteristics and different data models. The resulting mapping from M to N ranks can have a significant impact on aggregate application performance. In this work, we present an approach for performing this M-to-N mapping in a way that has broad applicability across a diversity of data producer and consumer applications. We evaluate its design and performance with a study that runs at high concurrency on a modern HPC platform. By leveraging design characteristics, which facilitate an ''intelligent'' mapping from M-to-N, we observe significant performance gains are possible in terms of several different metrics, including time-to-solution and amount of data moved.

Loring, Burlen↗

Influence of Single-Point Incremental Force Process Parameters on Forming Characteristics and Microstructure Evolution of AA-6061 Alloy Sheet

Single-point incremental forming (SPIF) process comprises a set of process variables, such as forming tool diameter, vertical pitch, spindle rotation speed, and tool velocity, which may affect the forming behavior of the sheet to be deformed. The objective of this work is to study the effect of SPIF process parameters on forming characteristics and microstructure development for the AA-6061 (T6) aluminum alloy sheet. The SPIF experiments and finite element (FE) simulations were performed at different process parameters to achieve conical shapes from the AA-6061 blanks. The effect of process parameters on forming forces, thickness uniformity in wall region of the cone and surface roughness of the blank was analyzed. A detailed microstructure study was performed to analyze the effect of process variables on microstructure and texture evolution during the SPIF process. This study reveals that the process parameters are likely to influence the texture development especially at high tool diameter and vertical pitch values. Therefore, suitability and consequences of using different combinations of tool diameter and vertical pitch values are discussed for AA-6061 alloy.

36 MATERIALS SCIENCE↗

Data processing pipeline for Tianlai experiment

The Tianlai project is a 21cm intensity mapping experiment for detecting dark energy by measuring the baryon acoustic oscillation (BAO) features in the large scale structure power spectrum. This experiment provides an opportunity to test the data processing methods for cosmological 21cm signal extraction, which is still a great challenge in current radio astronomy research. The 21cm signal is much weaker than the foregrounds and easily aected by the imperfections in the instrumental responses. Furthermore, processing the large volumes of interferometer data poses a practical challenge. We have developed a data processing pipeline called tlpipe to process the drift scan survey data from the Tianlai experiment. It performs oine data processing tasks such as radio frequency interference (RFI) agging, array calibration, binning, and map-making, etc. It also includes utility functions needed for the data analysis, such as data selection, transformation, visualization and others. A number of new algorithms are implemented, for example the eigenvector decomposition method for array calibration and the Tikhnov regularization for m-mode analysis. In this paper we describe the design and implementation of the pipeline and illustrate its functions with some analysis of real data. Finally, we outline directions for future development of this publicly code.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Improved Glow Discharge Polymer Removal from Beryllium Capsules Using Ozone

Copper-doped beryllium spheres are an attractive ablator for inertial confinement fusion experiments. Beryllium spheres are made by sputtering beryllium onto spherical plastic mandrels which must then be removed through a hole that is laser drilled through the shell wall. The currently used mandrel material is glow discharge polymer. This material cannot be removed by solvent and must be “burned” out. The burnout process was originally performed by etching with dry air at 425°C, but this process can substantially roughen the inner surface, which can seed instabilities and increase mix during implosion experiments. In this paper, we explore the use of pure oxygen and ozone to reduce process temperature and improve inner and outer surface quality.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Low Regeneration Temperature Sorbents for Direct Air Capture of CO 2

Susteon Inc., in partnership with University of Wyoming and SoCalGas, successfully met all major technical objectives to (1) scale up the ionic liquid catalyst for amine-based sorbents for improved desorption and absorption kinetics, (2) evaluate the catalyzed amine-based sorbents for direct CO 2 capture process to determine CO 2 adsorption and desorption rates and energy requirements, and (3) based on the experimental results, develop a conceptual process design to perform a preliminary economic assessment to evaluate the potential for DAC process cost reduction using the catalyzed sorbents. Amine doped solid sorbents are effective for DAC applications and can be regenerated by heat or by a combination of heat, steam, and vacuum. The best sorbent composition identified was polyethyleneimine (PEI) on fumed silica with 200 ppm ionic liquid catalyst. This sorbent formulation was shown to have a CO 2 breakthrough capacity twice that of the non-catalyzed sorbent, in laboratory tests with air at 75% relative humidity (RH). The CO 2 adsorption rate was also 40% higher than that of the non-catalyzed sorbent. This type of sorbents has the attributes required for lowering the overall cost of DAC with high CO 2 capacity and high rate of adsorption. The combination of an industrially utilized amine-based sorbent with a highly active catalyst to form a new class of materials for DAC provides a technically viable pathway for reducing the cost of DAC to <$100/tonne of CO 2 . Laboratory measurements show that the silica/PEI (polyethyleneimine) sorbents with 100 ppm of ionic liquid catalyst have almost 100% higher CO 2 cyclic capacity and 40% higher adsorption rate. Generally, CO 2 desorption occurred at higher temperatures with a rate of desorption 10 times faster than adsorption (which occurred at ambient conditions). Therefore, adsorption rate is a much more important factor in the cost of DAC because it is directly linked to the CAPEX of the total system and the cycle time (i.e., sorbent productivity in ton/day of CO 2 captured per unit volume of the air contactor). An initial process design, coupled with techno-economic analysis, based on optimal experimental results and preliminary resulting from structured sorbent testing, showed a path to lower the DAC cost from the current cost of over $200/tonne CO 2 to less than $100/tonne with a scale-up, mature state of the technology, with projected material and process improvements. These results demonstrate the effectiveness of the catalyst in silica/PEI sorbents in enhancing sorbents’ CO 2 working capacity, in (a) increasing the rate of adsorption and desorption, and (b) in lowering the CAPEX and OPEX of the DAC system employing the ionic liquid catalyzed sorbents.

01 COAL, LIGNITE, AND PEAT↗

Implementing the LSST Software Stack for DESGW processing and the Integration of Convolutional Neural Networks into the DESGW Pipeline

The Dark Energy Survey Gravitational Wave (DESGW) group strives to understand thelargescale structure of the universe and galaxies by looking for electromagnetic signatures intelescope images following gravitational wave detections. The DESGW group uses a processing pipeline to perform difference imaging to look for potential candidates. In order to perform these searches more effectively, we first explored using an alternative processing pipeline, the LSST Software Stack to analyze the telescope images. Because the LSST software stack is currently transitioning between its generation 2 and generation 3 system, we decided that while the software will be usable in the future once generation 3 is complete, at the moment its incompleteness makes it impractical to use. We then decided to work on improving the current pipeline by developing a module that integrates a Convolutional Neural Network (CNN) to test difference imaging products for bad subtractions due to misalignment.

Navarro, Alexander↗

Operando X-Ray Diffraction During High Temperature Electrolysis

This work presents the design, development, and deployment of an operando X-ray diffraction (XRD) system for high-temperature electrolysis (HTE), enabling real-time characterization of solid oxide electrolysis cells (SOECs) under true operational conditions. The integration of an HTE test stand within a synchrotron radiation environment, mimicking the conditions of a laboratory setup, aims to enhance our understanding of the degradation processes affecting the performance and longevity of SOECs. Utilizing a custom furnace and a high precision motor stack assembly at the Stanford Synchrotron Radiation Lightsource (SSRL), the system revealed unparalleled insights into the structural evolution of SOEC components through various operational stages, including initial heat ramp, cell reduction, fuel ramp, and wet electrolysis. Initial results demonstrate the significant impact of the initial heating and cooling on secondary phase formation within the SOEC, highlighting the utility of operando XRD for developing more efficient and durable hydrogen production technologies.

08 HYDROGEN↗

4D Printing via an Unconventional Fused Deposition Modeling Route to High-Performance Thermosets

An unprecedented four-dimensional (4D) printing process allowing high-performance and shape memory thermoset to be printed, for the first time, by fused deposition modeling (FDM) with isotropic properties has been achieved. Here, bisphenol A-based epoxy and benzoxazine were formulated to a low-temperature thermoplastic and high-temperature thermoset resin, which is melt-extrudable and can be postcured into covalently cross-linked material. Carbon nanotube (CNT) was added in the resin to work as both mechanical enhancement filler and rheology modifier to prevent shape deformation during postcuring process. The cross-layer reaction fuses individual layers into an integrity, thus eliminating layer delamination induced by FDM, offering isotropic mechanical properties regardless of the printing orientations. The highly cross-linked network provides outstanding mechanical strength and superb thermal stability. The excellent shape memory performance with fast recovery rate and large recovery degree is also obtained in the three-dimensional (3D) printed composites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Morphological–Electrical Property Relation in Cu(In,Ga)(S,Se) 2 Solar Cells: Significance of Crystal Grain Growth and Band Grading by Potassium Treatment

Abstract Solution‐processed Cu(In,Ga)(S,Se) 2 (CIGS) has a great potential for the production of large‐area photovoltaic devices at low cost. However, CIGS solar cells processed from solution exhibit relatively lower performance compared to vacuum‐processed devices because of a lack of proper composition distribution, which is mainly instigated by the limited Se uptake during chalcogenization. In this work, a unique potassium treatment method is utilized to improve the selenium uptake judiciously, enhancing grain sizes and forming a wider bandgap minimum region. Careful engineering of the bandgap grading structure also results in an enlarged space charge region, which is favorable for electron–hole separation and efficient charge carrier collection. Besides, this device processing approach has led to a linearly increasing electron diffusion length and carrier lifetime with increasing the grain size of the CIGS film, which is a critical achievement for enhancing photocurrent yield. Overall, 15% of power conversion efficiency is achieved in solar cells processed from environmentally benign solutions. This approach offers critical insights for precise device design and processing rules for solution‐processed CIGS solar cells.

Kim, Joo‐Hyun↗

Understanding structure-processing relationships in metal additive manufacturing via featurization of microstructural images

Understanding and predicting accurate property-structure-processing relationships for additively manufactured components is important for both forward and inverse design of robust, reliable parts and assemblies. While direct mapping of process parameters to properties is sometimes plausible, it is often rendered difficult due to poor microstructural control. Exploring the direct relationship between processing conditions and microstructural features can thus provide significant physical insights and aid the overall design process. Here, in this study, we develop an automated high-throughput framework to simulate an uncertainty-aware additive manufacturing (AM) process, characterize microstructural images, and extract meaningful features/descriptors. A kinetic Monte Carlo (KMC) based model of the AM process is used to simulate microstructural evolution for a diverse set of experimentally relevant processing conditions. We perform a parametric study to explore the relationship between microstructural features and processing conditions. Our results indicate that a many-to-one mapping can exist between processing conditions and typical descriptors; therefore, multiple descriptors are thus necessary to unambiguously represent microstructural images. Our work provides crucial quantitative and qualitative in-formation that would aid in the selection of features for microstructural images. Featurized microstructures could then be utilized to build data-driven models for predictive control of microstructures and thereby properties of additively manufactured components.

36 MATERIALS SCIENCE↗

Improved CO 2 Capture Performance of Electrochemically Mediated Amine Regeneration Processes with Ionic Surfactant Additives

For the effective reduction of global CO 2 emissions, it is essential to develop and deploy efficient and cost-effective technologies for CO 2 capture, especially from large point sources. We recently developed an electrochemically mediated amine regeneration (EMAR) system to replace traditional thermal desorption for the capture of CO 2 from post-combustion flue gases. Despite EMAR effectiveness on a laboratory scale, concerns regarding the high gas-to-liquid ratio in the electrochemical cell and long-term instability of the electrodes need to be addressed before further scale-up of the process to a pilot plant and beyond can be entertained. Accordingly, we investigated the effect of using sodium dodecyl sulfate (SDS) as an anionic surfactant and dodecyltrimethylammonium bromide (DTAB) as a cationic surfactant on the process operation. It was found that it is advantageous to use an anionic surfactant for a system such as EMAR that contains hydrophilic electrodes and a positively charged electrochemically active species. The overall cell resistance was notably reduced when SDS anionic surfactant was used. The precipitation of copper particles observed in the anode outlet when no surfactant was used was effectively avoided when SDS was added to the electrolyte, resulting in electrode stability. In addition, smaller gas bubbles were produced in the presence of the SDS surfactant, which resulted in less blockage of the electrode by the gas with a resultant lower cell potential under constant current conditions, driving more efficient CO 2 desorption. This led to an ~25% reduction in the electrochemical energy requirement, the lowest ever achieved experimentally for the EMAR process. Altogether, the addition of a very low concentration of SDS resulted in the successful circumvention of the important problems faced by the EMAR system regarding further scale-up.

36 MATERIALS SCIENCE↗