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At least 271 records · Page 15

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),↗

Equally high efficiencies of organic solar cells processed from different solvents reveal key factors for morphology control

The power conversion efficiency of organic solar cells (OSCs) is exceeding 20%, an advance in which morphology optimization has played a significant role. It is generally accepted that the processing solvent (or solvent mixture) can help optimize morphology, impacting the OSC efficiency. Here we develop OSCs that show strong tolerance to a range of processing solvents, with all devices delivering high power conversion efficiencies around 19%. By investigating the solution states, the film formation dynamics and the characteristics of the processed films both experimentally and computationally, we identify the key factors that control morphology, that is, the interactions between the side chains of the acceptor materials and the solvent as well as the interactions between the donor and acceptor materials. Our work provides new understanding on the long-standing question of morphology control and effective guides to design OSC materials towards practical applications, where green solvents are required for large-scale processing.

14 SOLAR ENERGY↗

Hydrazine-free precursor for solution-processed all-inorganic Se and Se 1− x Te x photovoltaics

Selenium (Se) has reemerged as a promising absorber material for indoor and tandem photovoltaics (PVs), and its alloys with Te (Se 1−x Te x ) offer a widely tunable bandgap. Solution processing of this materials system offers a route to low-cost fabrication. However, solution processing of Se has, thus far, only used hydrazine, which is an extremely hazardous solvent. In this work, we prepare and isolate propylammonium poly-Se and poly-Se–Te precursors from a safer thiol-amine solvent system. We formulate molecular inks by dissolving the precursor in dimethylformamide (DMF) with a monoethanolamine (EA) additive and process high-quality Se and Se 1−x Te x films with bandgaps ranging from 1.20 eV to 1.86 eV. We fabricate PVs from these films using TiO 2 and MoO 3 charge transport layers (CTLs) to achieve power conversion efficiencies as high as 2.73% for Se and 2.33% for Se 0.7 Te 0.3 under solar simulation. Se devices show excellent stability with no degradation after 1 month in air, enabled by the excellent stability of Se and the use of inorganic CTLs. This work represents an important step towards low-cost solution-phase processing of Se and Se 1−x Te x alloys for PVs and photodetectors with low toxicity and high bandgap tunability.

36 MATERIALS SCIENCE↗

Scalable, low-cost ink-based processing of high-performance silver selenide thermoelectrics

The growing global energy demand and its accelerating contribution to climate change emphasize the urgent need for sustainable energy conversion/harvesting technologies. Thermoelectric (TE) devices offer a compelling route to directly convert waste heat into electricity and enable solid-state cooling without moving parts or harmful refrigerants. Achieving their full potential requires not only higher TE performance (zT) but also scalable, low-cost manufacturing processes. Here, we introduce a transformative ink-based processing approach for scalable manufacturing of high-performance silver selenide-based TE materials and devices. Using a simple, high-throughput ink-mixing and blade coating strategy, our Ag 2 Se-based materials under the optimized composition and processing conditions yield an ultrahigh room-temperature power factor of 2.8 mW m −1 K −2 , over 100% higher than baseline samples and a reproducible figure of merit zT of 1 at room temperature. A thermoelectric generator (TEG) achieves a very competitive power density of 112 mW cm −2 at a 90 °C temperature difference between the hot and cold sides of the device, which is among the highest reported for silver selenide-based TE devices to date. This facile, scalable ink-based processing establishes a practical pathway toward industrial-scale manufacturing and widespread adoption of thermoelectric devices, advancing sustainable energy technologies.

Bappy, Md. Omarsany [University of Notre Dame, IN ↗

Comparison of multi-stage air treatment process divided by the same temperature and enthalpy difference

The multi-stage air treatment system has been proposed recently, and lower grade chilled/hot water could be used and energy efficiency could be improved. However, it has not been studied which division method of air treatment processes has higher energy efficiency. In this study, the model to calculate the energy consumption of multi-stage air treatment process is introduced, and the effects of two division methods, i.e. multi-stage air treatment process divided by the same temperature difference (ST method) or same enthalpy difference (SE method) between inlet and outlet at each stage, under 9 different air inlet parameters in the 2-stage and 3-stage air treatment processes are analysed and compared. The results show that (1) the system energy consumption of the SE method is generally lower than that of the ST method; (2) there is generally a larger energy consumption reduction rate of SE method when the air relative humidity is 70% compared to relative humidity of 50% and 90%; (3) the difference between ST method and SE method is not great, so both methods can be used for the design of multi-stage treatment system although SE method is normally recommended.

Wang, Wentao↗

Preparation of the Multi-Site Data Processing at the Vera C. Rubin Observatory

The Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) Camera is scheduled to start taking data in the summer of 2025. The Data Release Production will run the LSST Science Pipe software at data facilities in the US, France and the UK. The LSST Science Pipeline consists of complex directed acyclic graphs (DAGs) of tasks. Rubin will use the Production and Distributed Analysis (PanDA) workflow and workload management system to orchestrate this complex workflow and the distribution of workloads to the data facilities. When run end-to-end by a team of data production staff, this processing (the Science Pipelines, distributed by the workflow and workload management system) is referred to as a 'campaign'. This paper describes the central services and data facility specific services that support this multi-site data process model, including the service deployment infrastructure, the workload and workflow system, the Campaign Management tools, and connection to Rubin Data Management. This paper will also mention the experience of processing the Rubin Commissioning Camera data. All these are part of the effort to scale up the processing capabilities for the expected very large data volume from the LSST Camera.

Yang, Wei [SLAC]↗

Development of a microwave-assisted downdraft moving-bed gasifier for continuous processing of lignite and biomass chars

This research illustrates a microwave-assisted downdraft moving-bed gasifier for the first time. Such design enables continuous solid gasification process. An adjustable auger was applied to control the solid removal rate and the gas-solid interaction time. Both lignite and biomass chars were investigated to determine the capability of the current system for low-tar feedstocks with different densities. Here, the presented reactor design was able to operate continuously for 3 hours and 20 minutes under 700 ℃ and atmospheric pressure, with air as the gasifying agent. For yellow pine char, the processing rate could reach 34.1 grams per hour with decent syngas production. The downdraft moving-bed design shows better cold gas and syngas production efficiencies compared to the common fixed-bed design, due to controllable residence time and more homogeneous microwave heating. The limitations of the current design and the direction of novel microwave-assisted chemical reactor design were discussed. This novel reactor design provides a way to improve the efficiency of microwave-assisted gasification process and shows its potential to be incorporated into other established chemical reaction processes as a modular add-on.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Discrete Hankel Transform Approach to Nuclear Data Processing for Fusion Applications

This study introduces advancements to the numerical solutions employed in the processing of nuclear data for fusion applications. It leverages the convolution theorem and Fourier transform techniques to enhance computational efficiency and broaden applicability. Building upon a previously reported discrete Hankel transform approach for Doppler broadening, this work refines the solution of convolution integrals central to these applications. The methodology provides a general and unified framework for evaluating any convolution operation, regardless of whether the underlying problem involves temperature effects in nuclear reactions. The applicability to the nuclear data processing for fusion is demonstrated by deriving the convolution integrals for some of the fusion-related quantities. As before, the convolution operation utilizes a Gaussian-based kernel; however, the discrete Hankel transform of order $𝛼$ = $\frac{1}{2}$ is now applied to the forward Fourier transform of the nonkernel argument, rather than the inverse Fourier transform. This modification eliminates the need for the integration of the nonkernel, cross section–based function, which is a step that posed challenges for certain pointwise cross-section representations. It also removes the requirement for cross-section linearization. Optimized for graphics processing unit architectures, the approach significantly improves computational performance. These advancements are currently under evaluation as the foundation for the next-generation thermonuclear data file processing codes being developed at Lawrence Livermore National Laboratory.

Nuclear science and engineering↗

Successful νp -process in neutrino-driven outflows in core-collapse supernovae

The origin of the solar system abundances of several proton-rich isotopes, especially 92,94 Mo and 96,98 Ru, has been an enduring mystery in nuclear astrophysics. An attractive proposal to solve this problem is the νp-process, which can operate in neutrino-driven outflows in a core-collapse supernova after the shock is launched. Years of detailed studies, however, have cast doubt over the ability of this process to generate sufficiently high absolute and relative amounts of various p-nuclei. The νp-process is also thought to be excluded by arguments based on the long-lived radionuclide 92 Nb. Here, we present explicit calculations, in which both the abundance ratios and the absolute yields of the p-nuclei up to A ≲ 105 are successfully reproduced, even when using the modern (medium enhanced) triple-α reaction rates. The process is also shown to produce the necessary amounts of 92 Nb. The models are characterized by subsonic outflows and by the protoneutron star masses in the ≳ 1.7 M ⊙ range. In conclusion, this suggests that the Mo and Ru p-nuclides observed in the Solar System were made in CCSN explosions characterized by an extended accretion stage.

79 ASTRONOMY AND ASTROPHYSICS↗

Pre- and post-processing of cluster galaxies out to 5 × R 200: the extreme case of A2670

ABSTRACT We study galaxy interactions in the large-scale environment around A2670, a massive (M200 = $8.5 \pm 1.2~\times 10^{14} \, \mathrm{{M}_{\odot }}$) and interacting galaxy cluster at z = 0.0763. We first characterize the environment of the cluster out to 5× R200 and find a wealth of substructures, including the main cluster core, a large infalling group, and several other substructures. To study the impact of these substructures (pre-processing) and their accretion into the main cluster (post-processing) on the member galaxies, we visually examined optical images to look for signatures indicative of gravitational or hydrodynamical interactions. We find that ∼21 per cent of the cluster galaxies have clear signs of disturbances, with most of those (∼60 per cent) likely being disturbed by ram pressure. The number of ram-pressure stripping candidates found (101) in A2670 is the largest to date for a single system, and while they are more common in the cluster core, they can be found even at >4 × R200, confirming cluster influence out to large radii. In support of a pre-processing scenario, most of the disturbed galaxies follow the substructures found, with the richest structures having more disturbed galaxies. Post-processing also seems plausible, as many galaxy–galaxy mergers are seen near the cluster core, which is not expected in relaxed clusters. In addition, there is a comparable fraction of disturbed galaxies in and outside substructures. Overall, our results highlight the complex interplay of gas stripping and gravitational interactions in actively assembling clusters up to 5 × R200, motivating wide-area studies in larger cluster samples.

Astronomy & Astrophysics↗

Gamma-ray signatures of 𝑟-process radioactivity from the collapse of magnetized white dwarfs

We predict the gamma-ray line emission from 𝑟-process nuclei synthesized in the ejecta of the accretion-induced collapse (AIC) of a magnetized, rapidly rotating white dwarf. Using ejecta from a two-dimensional general-relativistic neutrino-magnetohydrodynamic simulation, further evolved with a radiation-hydrodynamics code coupled to an in situ nuclear reaction network, we construct angle-dependent gamma-ray spectra in the 0.01–10 MeV band via composition-dependent ray tracing through the ejecta. The emission between ∼1 and 10 d is dominated by 132 I (𝑡 1/2 = 2.3 h), continuously replenished by the decay of its parent 132 Te (𝑡 1/2 = 3.2 d), with additional contributions from 131 I, 133 Xe, and 132 Te . At 𝑡 ≳ 20 d, 56 Co (from 56 Ni decay) becomes the primary emitter. The simultaneous presence of 𝑟 process and iron-peak gamma-ray lines is distinctive of AIC ejecta and absent in binary neutron star mergers, where iron-peak nuclei are generally not synthesized. Comparing with the 3⁢𝜎 continuum sensitivities of planned MeV gamma-ray telescopes (COSI, AMEGO-X, e-ASTROGAM, GRAMS, GammaTPC), we find the brightest 𝑟-process lines detectable to ∼10 Mpc by GammaTPC and GRAMS, with the signal approaching their sensitivity threshold at 30 Mpc. As a result, the 𝑟-process spectral features survive time integration over ∼30 d exposures, demonstrating robustness against the long observation times required by gamma-ray detectors.

Nuclear reactions↗

Self-consistent analysis for the η c → γ γ process

The next-to-next-to-leading-order (NNLO) perturbative QCD (pQCD) predictions for both the decay width and the transition form factor in the η c → γ γ process, based on nonrelativistic QCD (NRQCD), deviate from precise experimental measurements. These significant discrepancies have cast doubt on the applicability of NRQCD to charmonium processes. In this paper, we analyze the η c → γ γ process by applying the principle of maximum conformality (PMC), a systematic method for eliminating renormalization scheme-and-scale ambiguities. The PMC renormalization scales are determined by absorbing the nonconformal β -terms that govern the behavior of the QCD running coupling via the renormalization group equation. We obtain the PMC scale Q ⋆ = 4.49 m c for the η c → γ γ decay width. Even after using the PMC method, the convergence of the pQCD series is still poor, which indicates the importance of uncalculated next-to-next-to-next-to-leading-order and higher-order terms. The resulting value for Γ η c → γ γ is in agreement with the Particle Data Group’s reported value of Γ η c → γ γ = 5.1 ± 0.4 keV within the bounds of uncertainties. Moreover, the transition form factor obtained using the PMC is also in good agreement with precise experimental measurements. The application of the PMC suggests a potential resolution to η c → γ γ puzzle and supports the applicability of NRQCD to charmonium processes. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Modeling Microwave-Enhanced Chemical Vapor Infiltration Process for Preventing Premature Pore Closure

The chemical vapor infiltration (CVI) process involves infiltrating a porous preform with reacting gases that undergo chemical transformation at high temperatures to deposit the ceramic phase within the pores, ultimately leading to a dense composite. The conventional CVI process in composite manufacturing needs to follow an isothermal approach to minimize temperature differences between the external and internal surfaces of the preform, ensuring that reactive gases infiltrate internal pores before external surfaces seal. Here, this study addresses the challenge of premature pore closure in CVI processes through microwave heating. A frequency-domain microwave solver is developed in OpenFOAM to investigate volumetric heating mechanisms within the preform. Through numerical studies, we demonstrate the capability of microwave heating of creating an inside-out temperature inversion. This inversion accelerates reactions proximal to the preform center, effectively mitigating the risk of premature external pore closure and ensuring uniform densification. The results reveal a significant enhancement in temperature inversion when high-permittivity reflectors are incorporated to generate resonant waves. This microwave heating strategy is then coupled with high-fidelity direct numerical simulation (DNS) of reacting flow, enabling the analysis of resulting densification processes. The DNS includes detailed chemistry and realistic diffusion coefficients. The numerical results can be used to estimate the impact of microwave-induced temperature inversion on densification in productions.

42 ENGINEERING↗

Modeling Microwave-Enhanced Chemical Vapor Infiltration Process for Preventing Premature Pore Closure

The chemical vapor infiltration (CVI) process involves infiltrating a porous preform with reacting gases that undergo chemical transformation at high temperatures to deposit the ceramic phase within the pores, ultimately leading to a dense composite. The conventional CVI process in composite manufacturing needs to follow an isothermal approach to minimize temperature differences between the external and internal surfaces of the preform, ensuring that reactive gases infiltrate internal pores before external surfaces seal. This study addresses the challenge of premature pore closure in CVI processes through microwave heating. A frequency-domain microwave solver is developed in Open-FOAM to investigate volumetric heating mechanisms within the preform. Through numerical studies, we demonstrate the capability of microwave heating of creating an inside-out temperature inversion. This inversion accelerates reactions proximal to the preform center, effectively mitigating the risk of premature external pore closure and ensuring uniform densification. The results reveal a significant enhancement in temperature inversion when high-permittivity reflectors are incorporated to generate resonant waves. This microwave heating strategy is then coupled with high-fidelity direct numerical simulation (DNS) of reacting flow, enabling the analysis of resulting densification processes. The DNS simulation includes detailed chemistry and realistic diffusion coefficients. The numerical results can be used to estimate the impact of microwave-induced temperature inversion on densification in productions.

Ge, Wenjun↗

Understanding and Enhancing Silicon Nanoparticle Distribution during Electrode Processing

Silicon-dominant anodes are of great interest because of their potential to boost the cell-level energy of state-of-the-art Li-ion batteries. While silicon materials have been extensively studied, understanding interactions at the electrode level has recieved little attention, especially the coating process of Si particles, which plays an equally important role in unlocking the full potential of silicon anodes. Herein, the electrode processing of a Si-dominated anode (52.8 wt%, 3.5–4.5 mAh cm −2 ) is being investigated to understand the relationship of processing on the morphology and properties of Si anodes at the electrode level. It has been found that almost-undetectable Si agglomerates easily form during electrode processing, which grow into largeprotrusions after lithiation and trigger potential internal shorting and self-discharge problems. A facile slurry filtration step is proposed to homogenize the particle distribution within Si-dominant electrodes which improves the electrochemical performance and storage stability of Si-based Li ion batteries.

Wu, Bingbin↗

NLR Data Processing Pipeline for MADIS [SWR-26-050]

The NLR Data Processing Pipeline for MADIS software package is for downloading, processing, and performing QA/QC on MADIS data. Designed to handle the following steps: 1) Download all MADIS data as compressed netcdf files for a given time period. 2) Unpack netcdf files into timeseries csvs for each coordinate within the given bounding box. 3) Process the csvs to filter according to quality control checks and convert variables to correct units. 4) Write processed csvs to a single nc file.

Benton, Brandon [National Laboratory of the Rockie↗

Sensitivity of Arctic Clouds to Ice Microphysical Processes in the NorESM2 Climate Model

Abstract Ice formation remains one of the most poorly represented microphysical processes in climate models. While primary ice production (PIP) parameterizations are known to have a large influence on the modeled cloud properties, the representation of secondary ice production (SIP) is incomplete and its corresponding impact is therefore largely unquantified. Furthermore, ice aggregation is another important process for the total cloud ice budget, which also remains largely unconstrained. In this study, we examine the impact of PIP, SIP, and ice aggregation on Arctic clouds, using the Norwegian Earth System Model, version 2 (NorESM2). Simulations with both prognostic and diagnostic PIP show that heterogeneous freezing alone cannot reproduce the observed cloud ice content. The implementation of missing SIP mechanisms (collisional breakup, drop shattering, and sublimation breakup) in NorESM2 improves the modeled ice properties, while improvements in liquid content occur only in simulations with prognostic PIP. However, results are sensitive to the description of collisional breakup. This mechanism, which dominates SIP in the examined conditions, is very sensitive to the treatment of the sublimation correction factor, a poorly constrained parameter that is included in the utilized parameterization. Finally, variations in ice aggregation treatment can also significantly impact cloud properties, mainly through their impact on collisional breakup efficiency. Overall, enhancement in ice production through the addition of SIP mechanisms and the reduction in ice aggregation (in line with radar observations of shallow Arctic clouds) result in enhanced cloud cover and decreased TOA radiation biases, compared to satellite measurements, especially during the cold months. Significance Statement Arctic clouds remain a large source of uncertainty in projections of the future climate due to the poor representation of the microphysical processes that govern their life cycle. Ice formation is among the least understood processes. While it is widely recognized that better constraints on primary ice production (PIP) are needed to improve existing parameterizations, we show that secondary ice production (SIP) and ice aggregation can have also a significant impact on ice number concentrations. Constraining ice formation through the addition of missing SIP mechanisms and reducing ice aggregation can improve the representation of the cloud macrophysical properties and enhance total cloud cover in the Arctic region, which in turn contributes to decreased TOA radiation biases in the cold months.

Meteorology & Atmospheric Sciences↗

Data for Process Strategies for Recovery of Sugars, Lipids, and Lignin from Oilcane Bagasse Using Natural Deep Eutectic Solvents (NADES)

Sugarcane is being enhanced as a bioenergy crop by engineering it to accumulate and store lipids along with polymeric sugars in vegetative tissues. However, there is no existing process that allows for processing this new crop to recover both lipid and cellulosic sugars from the oilcane bagasse. Therefore, a comprehensive investigation of two pretreatment methods—natural deep eutectic solvents (NADES) and chemical-free hydrothermal pretreatment (HT) was conducted to judge their suitability for recovering fermentable sugars, lipids, and lignin from bagasse. Two NADES, i.e., choline chloride: lactic acid (ChCl:LA) and betaine: lactic acid (BT:LA) were prepared using a 1:2 M ratio and were evaluated for pretreatment of oilcane bagasse at 10, 20, and 50 % (w/w) solids, followed by enzymatic hydrolysis at 10 % (w/w) solids. Notably, ChCl:LA NADES treatment at 10 % (w/w) solids at 140 °C for 2 h, solubilized 78.8 % of lignin and 80.4 % of hemicellulose and allowed 82.7 % enzymatic conversion of glucans to glucose. In contrast, HT pretreatment removed approximately 87.6 % of the hemicellulose and provided an enzymatic glucose yield of 69.7 %. Furthermore, ChCl:LA operated at 50 % solids loading the enriched lipids 2.6-fold (9.2 wt%) in recovered solids compared to HT (6.4 %) and BT:LA (5.1 %) pretreatment processes. NMR-HSQC and GPC analysis showed that ChCl:LA also cleaved the most lignin β–O–4 linkages and demonstrated lower molecular weight compared to HT. This study demonstrates that NADES pretreatment is an effective green processing method for recovering lipids, sugars, and lignin from bioenergy crops at high solid loading (50 % w/w) within the context of an integrated biorefinery.

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