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At least 163 records · Page 9

High-shade dryland agrivoltaic conditions enhanced carbon uptake and water-use efficiency in zucchini ( Cucurbita pepo )

Introduction: The increasing global demand for food and energy is intensifying land-use competition. Agrivoltaic systems are a multifunctional land-use approach that vertically integrates the production of agricultural crops and solar power on the same land area. Most food crops are adapted to full-sun conditions, and the physiological responses of these crops to the novel microclimate under solar panels remain poorly understood. We hypothesized that the microclimate beneath the high-density photovoltaic system would influence carbon uptake, water use, and yield outcomes of zucchini summer squash.Methods: We conducted a field experiment in a hot, semi-arid climate on zucchini (Cucurbita pepo). Plants were grown under an agrivoltaic system with a 75% ground cover ratio (GCR) and in a full-sun control plot, each with two irrigation regimes (100 and 50%). We measured leaf-level photosynthesis, microclimate variables, and fruit yield at plant maturity and throughout the growing season.Results: The agrivoltaic array reduced photosynthetically active radiation (PAR) by ~79%, resulting in a cooler (−1.1 °C), more humid environment with higher soil moisture. These microclimatic conditions enhanced midday photosynthesis and daily cumulative carbon uptake. However, fruit yield was consistently lower under the panels, indicating a shift in carbon allocation toward vegetative growth. Photosynthesis was primarily driven by PAR across treatments, while soil moisture significantly influenced photosynthesis only in the control plots, suggesting water limitation was alleviated under the panels.Discussion: These findings highlight a trade-off between improved physiological performance and reduced yield under high-density agrivoltaics. While the system buffered heat and drought stress and improved overall plant function, excessive shade reduced reproductive output. Optimizing panel density or selecting crops cultivated for non-fruit yields will be essential for balancing food production and energy generation in dryland agrivoltaic settings.

14 SOLAR ENERGY↗

Ultrabroad-band x-ray source using a picosecond, laser-driven plasma accelerator

An ultrabroad-band x-ray source, with photon energies from 10 keV to >1 MeV, based on a picosecond laser-driven plasma accelerator, is characterized and used to radiograph high-energy-density-science relevant targets. The measured yield of 10 12 photons/shot is reaching the necessary photon yields to radiograph, in a single shot, high areal density objects and matter under extreme conditions. By focusing a short laser pulse (120 J, 1 ps) into a gas jet, a < 100 mrad electron beam with energies up to 350 MeV and up to 70 nC of charge was produced by a combination of laser self-modulation instability and direct laser acceleration. A foil placed at the exit of the gas jet is used to convert part of the electron beam energy into x rays through inverse bremsstrahlung and/or inverse Compton scattering, generating a bright, broad-band, high-photon-energy beam. This beam is used to radiograph a gold half hohlraum with a high-density sphere inside with relevant characteristics for high-energy-density science and inertial confinement fusion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Implementation of stacked ensemble machine learning for the detection of surrogate plutonium contamination in soil via LIBS

Supervised machine learning methods have demonstrated increased utility for the quantification of lanthanide and actinide elements in atomic spectroscopy applications. This study implements laser-induced breakdown spectroscopy (LIBS) for the identification of plutonium surrogate material (CeO 2 ) in soil matrices by training supervised machine learning methods on the recorded spectral data. A bagged ensemble using Random Forest yields the highest sensitivity predictions with a detection limit of 0.015 wt.% CeO 2 . However, high precision in Ce content prediction required the use of a stacked ensemble regression, which provided the superlative Ce quantification model with an error of 0.107% and a detection limit of 0.022 wt.%. Furthermore, the high performance of the stacked ensemble demonstrates its potential to enhance the accuracy and sensitivity of nuclear contaminant detection using field-deployable spectroscopic analyzers in real-world scenarios.

47 OTHER INSTRUMENTATION↗

Cell-Free-Based Thermophilic Biocatalyst for the Synthesis of Amino Acids from One-Carbon Feedstocks

Bioproduction from one-carbon compounds, such as formate, is an attractive prospect due to reduced energy requirements and the possibility for using CO 2 as a sustainable feedstock. Formate-fixing pathways engineered using Escherichia coli lysate-based cell-free expression (CFE) biocatalysts have the potential to route 100% of feedstock carbon toward chemical synthesis but are undermined by siphoning of in-pathway metabolites and cofactors by the CFE background metabolism. To address this limitation, we engineer a CFE-based thermophilic multienzyme biocatalyst for the synthesis of serine and glycine from formate, bicarbonate, and ammonia. After expression of the thermophilic formate-to-serine pathway in a one-pot reaction, the mesophilic E. coli CFE background machinery is removed by simple heat denaturation, eliminating the siphoning of cofactors, inpathway metabolites, and products. After bioprocess optimization, including pathway gene expression duration and chemical synthesis temperature, we achieve near stoichiometric conversion of formate and bicarbonate to serine and glycine, reaching 97% of stoichiometric yield. The use of a moderately thermophilic biocatalyst allowed chemical synthesis to take place at mesophilic temperatures, enabling the balance of optimal enzyme activity with minimal metabolite/cofactor thermal degradation. In a fed-batch experiment, the biocatalyst shows sustained chemical synthesis rates for 8 h, paving the way toward a continuous bioprocess. Finally, a sensitivity analysis of cofactor usage revealed that the most expensive cofactors, THF and NADPH, can be reduced by 5-fold without significantly lowering product yields. To the best of our knowledge, this is the first instance of expressing a thermophilic pathway in an E. coli lysate-based CFE system to generate a thermophilic biocatalyst for use at mesophilic temperatures. The CFEbased thermophilic formate-to-serine biocatalyst triples the combined serine and glycine yield previously obtained by a CFE-based mesophilic formate-to-serine biocatalyst (30%), and quadruple the yield obtained by a purified enzyme system (22%). Ultimately, this work opens the door to using E. coli lysate-based CFE for thermophilic biocatalyst generation to achieve high chemical synthesis yields.

bacteria↗

Comparison of tungsten versus molybdenum for double shell capsules using machine learning design optimization

Double shell targets are an alternative ignition platform for inertial confinement fusion. One design consideration for double shell targets is the choice of inner shell material to help trap radiation emitted by the hot fuel to aid ignition. Materials such as molybdenum and tungsten are of interest for the inner shell layer of the targets. While molybdenum has a lower density that could inhibit instability growth and allow for radiography and code benchmarking, tungsten has a higher density that could provide more compression and confinement. These tradeoffs have been explored using optimized designs for each material. Our previous work [Vazirani et al., “Coupling 1D xRAGE simulations with machine learning for graded inner shell design optimization in double shell capsules,” Phys. Plasmas 28, 122709 (2021); Vazirani et al., “Coupling multi-fidelity xRAGE with machine learning for graded inner shell design optimization in double shell capsules,” Phys. Plasmas 30, 062704 (2023); and Vazirani et al., “Bayesian batch optimization for molybdenum versus tungsten inertial confinement fusion double shell target design,” Stat. Anal. Data Min. 17, e11698 (2024)] resulted in a multi-fidelity Bayesian optimization framework to find yield-optimized double shell target geometries. By leveraging simulations of varying fidelities (one-dimensional and two-dimensional) to inform one another, the multi-fidelity optimization was able to optimize a design in the highest fidelity with significantly fewer simulations than would be used in a systematic parameter scan. In this work, we apply the multi-fidelity Bayesian optimization to explore the optimized designs of double shell targets with molybdenum and tungsten inner shells as well as the physics producing the high performing implosions. A physics exploration of all the simulations used in this study shows trends in designs that contribute to high yields, ion temperatures, and fuel areal densities. Comparison of molybdenum and tungsten simulations shows that they can produce similar implosion conditions with different geometries, which would be important to study in experiments. Graded density layers produce varying performances with the two materials but continue to be of interest for future studies along with studies of doped inner shell materials and applied surface roughness.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

SPUTTERED THIN FILMS FOR VERY HIGH POWER, EFFICIENT, AND LOW-COST COMMERCIAL SOFCS

The aim of this project was to leverage the low area specific resistance (ASR) of Redox’s GDC electrolyte-based cell architecture and increase solid oxide fuel cell (SOFC) efficiency (i.e., open circuit voltage, or OCV) without significantly increasing cell resistance. The key to achieving the increased SOFC efficiency is the introduction of a thin sputtered yttria stabilized zirconia (YSZ) electron-blocking layer and a thin sputtered gadolinia doped ceria (GDC) barrier layer on top of the half-cell substrate (i.e., anode and GDC electrolyte). A key initial effort of the project was to improve the quality of the half-cell substrate surface so that any remaining defects were significantly smaller than the desired film thickness. During lab-scale trials, we had to overcome challenges with film cracking during post-sputtering treatments (e.g., thermal anneals) as well as damage to the sputtering targets. After the initial lab-scale trials, the focus shifted toward the use of commercial scale sputtering equipment with a sputtering equipment manufacturer in the microelectronics industry. Using the commercial sputtering equipment, we deposited films with different variations of power, PO2, sputtering time, platen speed, etc. We then determined the combinations of sputtering conditions and post-sputtering treatments that yielded high-quality films without cracks or other significant defects. While thin films were deposited on cells as large as 10 cm by 10 cm, the processing was optimized using 4 cm by 4 cm cells. Cell performance was evaluated in stainless-steel test fixtures between 500 °C and 700 °C with hydrogen fuel fed to the anode and air fed to the cathode. Extensive studies allowed us to determine that modified cathode and cathode contact firing processes were required to achieve theoretical OCV. Moreover, use of the new firing processes resulted in the need for a modified cathode contact to achieve a low ASR. In summary, the project demonstrated the performance of high OCV (1.13 V at 650 °C) from sputtered layers and a low ASR (~0.25 Ohms-cm2 at 650 °C) resulting from a modification of cathode/contact processing and the introduction of alternative contact layers that are sufficient to yield a Gen-1 cell with a maximum power density of approximately 1.2 W/cm2. At an operating voltage of 0.74 V, this would yield a cell power density of ~1.1 W/cm2. While not utilized in this project, a Redox Gen-2 cell has a catalyst-infiltrated porous anode that reduces the ASR by more than 50% from that of the Gen-1 cells used in this project. Therefore, if the sputtered YSZ electron-blocking layer and GDC barrier layer are added to a Gen-2 half cell with a similar increase in OCV to the theoretical value of ~1.13 V at 650 °C, and if the same improvement in ASR (from that demonstrated in this project) is achieved when using the Gen-2 half-cell architecture as a sputtered cell substrate, then the power density at 0.74 Vop could be as high as ~2.6 W/cm2. The impact of such power density gains, while still maintaining high cell efficiency, and thus high system efficiency, is a dramatic decrease in system cost because the stack represents ~30-40% of the SOFC system cost.

01 COAL, LIGNITE, AND PEAT↗

Hot or Not? An Evaluation of Methods for Identifying Hot Moments of Nitrous Oxide Emissions From Soils

Abstract Effectively quantifying hot moments of nitrous oxide (N 2 O) emissions from agricultural soils is critical for managing this potent greenhouse gas. However, we are challenged by a lack of standard approaches for identifying hot moments, including (a) determining thresholds above which emissions are considered hot moments, and (b) considering seasonal variation in the magnitude and frequency distribution of net N 2 O fluxes. We used one year of hourly N 2 O flux measurements from 16 autochambers that varied in flux magnitude and frequency distribution in a conventionally tilled maize field in central Illinois, USA, to compare three approaches to identify hot moment thresholds: standard deviations (SD) above the mean, 1.5x the interquartile range (IQR), and isolation forest (IF) identification of anomalous values. We also compared these approaches on seasonally subdivided data (early, late, and non‐growing seasons) versus the whole year. Our analyses revealed that 1.5x IQR method best identified N 2 O hot moments. In contrast, using 2 or 4 SD both yielded hot moment threshold values too high, and IF yielded threshold values too low, leading to missed N 2 O hot moments or low net N 2 O fluxes mischaracterized as hot moments, respectively. Furthermore, seasonally subdividing the data set not only facilitated identification of smaller hot moments in the late‐ and non‐growing seasons when N 2 O hot moments were generally smaller but it also increased hot moment threshold values in the early growing season when N 2 O hot moments were larger. Consequently, of the methods evaluated here, we recommend using the 1.5x IQR method on whole year data sets to identify N 2 O hot moments.

Stuchiner, Emily R. [Institute for Sustainability,↗

Templated epitaxy of TiO 2 (B) on a perovskite

The bronze-phase TiO 2 (B) has an open atomic framework that makes it a good candidate for applications in photochemical and electrochemical conversion of energy. However, the synthesis of bronze-phase TiO 2 (B) thin films on perovskite substrates, such as SrTiO 3 (STO), which is one of the most conventional versatile substrates for oxide epitaxy, has been extremely challenging owing to the preferential formation of the anatase TiO 2 over TiO 2 (B). The main reason is that the anatase TiO 2 has not only a smaller lattice mismatch than TiO 2 (B), but also a better structural symmetry match when grown on STO. Here, we demonstrate a way to circumventing this problem by using a VO 2 (B) buffer layer, yielding the growth of a high-quality single crystalline TiO 2 (B) film on a (001)-oriented STO substrate. Finally, from the resulting TiO 2 (B) film, we found that this film has a large optical bandgap of ~3.6 eV, which is close to the known theoretical value, the largest among TiO 2 polymorphs, and useful for developing high-power energy devices.

36 MATERIALS SCIENCE↗

Using real-time nuclear activation detectors for measuring neutron yields from D(D, T)n reactions on the national ignition facility (NIF)

The National Ignition Facility (NIF) has 48 Real-Time Nuclear Activation Detectors distributed around the target chamber capable of measuring deuterium-triton reaction neutron yields with high precision. Here, in this work, we extend this functionality to deuterium–deuterium (DD) reaction neutrons using a nuclear reaction that occurs in the detector’s scintillator material. The corresponding decay of the activated material has a very short half-life of 5 s, which necessitates rapid data collection immediately following an experiment. In this regime, dead time can be very high (>50%) adding significant uncertainty to the measurement. To combat this, we have developed a dead time model that can self-consistently describe the measured data. Initial results show reasonable agreement (within 20%) with DD neutron yields from neutron time-of-flight spectrometers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The role of lignin in the conversion of wheat straw to cellobionic acid by Neurospora crassa HL10

An engineered Neurospora crassa strain (HL10) naturally produces cellulases, cellobiose dehydrogenase (CDH), and heterologously expresses laccase. It can convert Avicel (cellulose) to cellobionic acid (cellobionate) without any enzyme addition at high yields. However, the addition of a catalytic amount of artificial redox mediators was required to achieve a high yield conversion. When a lignocellulosic substrate like wheat straw was used as the carbon source, it was found that adding exogenous artificial redox mediators did not improve cellobionate yield. We hypothesized that lignin and lignin degradation products were able to serve as redox mediators for the CDH-laccase conversion system. Experiments were designed to prove the hypothesis. When N. crassa HL10 was grown on Avicel, the addition of enzyme hydrolyzed lignin (EHL) can achieve a similar level of cellobionate production as with ABTS addition. The addition of EHL can increase the cellobionate production rate in the CDH-laccase bi-enzyme system using cellobiose as the substrate. The formation of lignin radicals, and the quenching of lignin radicals by reduced CDH, were verified by an electron paramagnetic resonance (EPR) experiment, providing further evidence that lignin radicals can serve as the electron acceptor of reduced CDH. Hence, lignocellulosic biomass is a self-sufficient substrate for the production of cellobionate. The conversion of the lignocellulosic substrate to cellobionate using N. crassa HL10 can be achieved without any exogenous enzyme addition or redox mediator addition.

59 BASIC BIOLOGICAL SCIENCES↗

Protein-based approach for high-purity Sc, Y, and grouped lanthanide separation

Rare earth elements (REEs: Sc, Y, La- Lu) are irreplaceable components in many clean energy and consumer technologies. However, the extraction and subsequent separation of individual REEs from ore-based feedstocks remains a significant economic and environmental challenge. Here in this work, we investigated the intra-REE separation potential of lanmodulin (LanM), a natural protein from Methylorubrum extorquens that has emerged as a sustainable potential alternative to conventional solvent extraction-based separation. By determining the intra-REE selectivity of immobilized LanM and systematically testing pH-based and small chelator-based (i.e., citrate and malonate) desorption processes, we established the framework and methodology for achieving select individual and grouped REE separations from a mixed REE feedstock. We show that Sc forms the tightest complex with LanM among REEs but can be readily and selectively desorbed using malonate to generate high-purity Sc (>99 % purity, >99 % yield) in a single adsorption/desorption cycle. We further show that the intrinsic REE selectivity of LanM is sufficient to achieve heavy REE (HREE) separation from light and middle REEs (L-MREEs), yielding an yttrium-enriched product. This separation effect is further magnified by pairing LanM’s unique M-LREE preference with a HREE-preferring chelator in the desorption process, which enriches HREE and MREE fractions relative to low value, abundant La/Ce. Finally, by combining pH- and citrate-based desorption processes in a two-cycle separation scheme, we demonstrate the generation of fractions highly enriched in Y, Gd-Lu, Pr-Eu, and La-Ce. Collectively, these data support the application of a LanM-based approach for achieving impactful REE separations from mixed REE feedstocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Conjugated Zwitterionic Oligomers as Ligands on Perovskite Nanocrystals: Hybrid Structures with Tunable Interparticle Spacing

Conventional ligands for CsPbBr 3 perovskite nanocrystals (NCs), composed of polar, coordinating head groups (e.g., ammonium or zwitterionic) and aliphatic tails, are instrumental in stabilizing the NCs against sintering and aggregation. Nonetheless, the aliphatic (insulating) nature of these ligands represents drawbacks with respect to objectives in optoelectronics, and yet removing these ligands typically leads to a loss of colloidal stability. Here, in this paper, we describe the preparation of CsPbBr 3 NCs in the presence of discrete conjugated oligomers that were prepared by an iterative synthetic approach and capped at their chain ends with sulfobetaine zwitterions for perovskite coordination. Notably, these zwitterionic oligofluorenes are compatible with the hot injection and ligand exchange conditions used to prepare CsPbBr 3 NCs, yielding stable NC dispersions with high photoluminescence quantum yields (PLQY, >90%) and spectral features representative of both the perovskite core and conjugated ligand shell. Controlling the chain length of these capping ligands effectively regulated inter-NC spacing and packing geometry when cast into solid films, with evidence derived from both transmission electron microscopy (TEM) and grazing incidence X-ray scattering measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photo-exfoliation of MoS 2 quantum dots from nanosheets: an in-situ transmission electron microscopy study

Fabrication of transition metal dichalcogenide (TMD) quantum dots (QDs) is complex and requires submerging of powders in binary solvents and the constant tuning of wavelength and pulsed frequency of light to achieve a desired reaction. Here,iInstead of liquid state photoexfoliation, we utilize infrared laser irradiation of free-standing MoS 2 flakes in transmission electron microscope (TEM) to achieve solid-state multi-level photoexfoliation of QDs. By investigating the steps involved in photochemical reaction between the surface of MoS 2 and the laser beam, we gain insight into each step of the photoexfoliation mechanism and observe high yield production of QDs, led by an inhomogeneous crystalline size distribution. Additionally, by using a laser with a lower energy than the indirect optical transition of bulk MoS 2 , we conclude that the underlying phenomena behind the photoexfoliation is from multi-photon absorption achieved at high optical outputs from the laser source. These findings provide an environmentally friendly synthesis method to fabricate QDs for potential applications in biomedicine, optoelectronics, and fluorescence sensing.

36 MATERIALS SCIENCE↗

Robustness of inertial fusion energy relevant implosions to low-mode asymmetries

Inertial confinement fusion implosions for power production need to be robust. Degradation sources need to be understood and considered for an economic power plant. In this work, the impact of low-mode asymmetries on yield is studied using 2D radiation hydrodynamics simulations for inertial fusion energy relevant implosions. First, a high-gain indirectly driven capsule design is developed. This design is subsequently degraded with low-mode drive asymmetries. The results show that yield is constant with increasing amounts of asymmetry until a cliff is reached where the yield quickly drops below ignition. Robustness arises because the degraded hotspot still has enough time to get to ignition before capsule decompression. This robustness occurs even though the asymmetry couples less energy to the hotspot and causes decompression to occur sooner. The robustness is linked to the generalized Lawson parameter, χ⁠. The value of χ steadily decreases with increasing asymmetry. Once χ is close to one, the hotspot is no longer able to ignite before the capsule decompresses. A simple piston model is used to predict where the robustness cliff is for any design. The trade-off between yield and robustness is also demonstrated.

Physics - Plasma physics↗

Influence of soil heterogeneity on soybean plant development and crop yield evaluated using time-series of UAV and ground-based geophysical imagery

Understanding the interactions among agricultural processes, soil, and plants is necessary for optimizing crop yield and productivity. This study focuses on developing effective monitoring and analysis methodologies that estimate key soil and plant properties. These methodologies include data acquisition and processing approaches that use unmanned aerial vehicles (UAVs) and surface geophysical techniques. In particular, we applied these approaches to a soybean farm in Arkansas to characterize the soil–plant coupled spatial and temporal heterogeneity, as well as to identify key environmental factors that influence plant growth and yield. UAV-based multitemporal acquisition of high-resolution RGB (red–green–blue) imagery and direct measurements were used to monitor plant height and photosynthetic activity. We present an algorithm that efficiently exploits the high-resolution UAV images to estimate plant spatial abundance and plant vigor throughout the growing season. Such plant characterization is extremely important for the identification of anomalous areas, providing easily interpretable information that can be used to guide near-real-time farming decisions. Additionally, high-resolution multitemporal surface geophysical measurements of apparent soil electrical conductivity were used to estimate the spatial heterogeneity of soil texture. By integrating the multiscale multitype soil and plant datasets, we identified the spatiotemporal co-variance between soil properties and plant development and yield. Our novel approach for early season monitoring of plant spatial abundance identified areas of low productivity controlled by soil clay content, while temporal analysis of geophysical data showed the impact of soil moisture and irrigation practice (controlled by topography) on plant dynamics. Our study demonstrates the effective coupling of UAV data products with geophysical data to extract critical information for farm management.

54 ENVIRONMENTAL SCIENCES↗

An approach towards plastic scintillators from thermally activated delayed fluorescent dyes and cross-linkable bismuth compounds

Cross-linked polyvinyltoluene (PVT) based plastic scintillators loaded with dyes exhibiting thermally activated delayed fluorescence (TADF) and various amounts of (caproate)di-(methacrylate) bismuth (CMB) were developed. The co-polymerization of vinyl toluene monomer loaded with different weight ratios of CMB and 1 wt% of TADF dye yielded highly transparent cross-linked plastic scintillators with intense green photoluminescence. The thermal and mechanical properties of the scintillators were investigated using thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and micro indentation techniques. Here, their performance for radiation detection was assessed by performing gamma spectroscopy using a Cs-137 source and benchmarked to commercial plastic scintillators. The loading of CMB was guided by Monte Carlo N-Particle (MCNP) simulations. The results of this study show that the cross-linking approach and the use of TADF dyes yield scintillators with good mechanical properties with a uniaxial yield strength up to ~66 MPa for compositions loaded with 40 wt% of CMB and high optical quality. However, the light yield in gamma spectroscopy experiments is found to be reduced with the addition of CMB, suggesting a trade-off between mechanical yield strength and light yield in gamma spectroscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Compressing Hamiltonians with ab initio downfolding for simulating strongly-correlated materials on quantum computers

The accurate first-principles description of strongly correlated materials is an important and challenging problem in condensed matter physics. Ab initio downfolding has emerged as a way of deriving compressed many-body Hamiltonians that maintain the essential physics of strongly correlated materials. The solution of these material-specific models is still exponentially difficult to generate on classical computers, but quantum algorithms allow for a significant speed-up in obtaining the ground states of these compressed Hamiltonians. Here, we demonstrate that using quantum algorithms to obtain the properties of downfolded Hamiltonians can indeed yield high-fidelity solutions. By combining ab initio downfolding and variational quantum eigensolvers, we correctly predict the antiferromagnetic state of one-dimensional cuprate Ca 2 Cu O 3 , the excitonic ground state of monolayer W Te 2 , and the charge-ordered state of correlated metal Sr VO 3 . Numerical simulations using a classical tensor network implementation of variational quantum eigensolvers allow us to simulate large models with up to 54 qubits and encompassing up to four bands in the correlated subspace, which is indicative of the complexity that our framework can address. Through these methods we demonstrate the potential of classical preoptimization and downfolding techniques for enabling efficient materials simulation using quantum algorithms.

Alvertis, Antonios M. [NASA, Ames; LBNL, Berkeley]↗

PowderJet: Spherical metal powder production via multi-orifice droplet-on-demand metal jetting

Leading metal additive manufacturing techniques, such as laser powder bed fusion and directed energy deposition, rely on high-quality spherical metal powders. However, traditional powder production methods like gas atomization face limitations, including low in-spec yield, asphericity, and internal porosity. We introduce PowderJet, a powder production platform that uses electromagnetic pulses to eject liquid metal droplets from a multi-orifice nozzle. Unlike stochastic methods, PowderJet tightly controls powder size, distribution, and purity through a droplet-on-demand approach. We detail the system’s design, operation, and performance using a combined experimental and computational fluid dynamics (CFD) framework. Initial results with Al4008 and Cu110 alloys demonstrate successful production, yielding unsieved aluminum powder batches with a mean diameter of 200 µm and a narrow size distribution (15 µm standard deviation). The produced powders are highly spherical, achieving a roundness > 0.95. PowderJet operates with a small melt volume (3 mL) and supports continuous refilling, enabling production rates between 30 and 140 cm³/hr depending on jetting frequency, number of orifices and particle size. CFD simulations show that future systems could achieve rates exceeding 1000 cm³/hr for particle sizes as small as 40 µm. PowderJet’s high yield of in-spec powder makes it ideal for producing precious or hazardous materials that are inefficient to manufacture using conventional methods. This platform offers a scalable, precise, and efficient solution for producing high-quality powders tailored for advanced manufacturing applications.

Atomization↗