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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Control of core–shell nanoparticles properties through plasma synthesis: a computational study

The improved properties of core–shell nanoparticles (CSNPs) over homogeneous nanoparticles (NPs) have expanded and diversified the applications of these nanomaterials. However, controlling the properties of CSNPs can be a challenging task. Low temperature plasmas have proven to be an effective method of producing NPs with uniform size and morphology, and high yield. That said, NP transport and growth dynamics are sensitive to LTP properties. We report on a computational investigation of the evolution of Ge–Si CSNP properties as a function of operating conditions through the modeling of a flowing, two-zone inductively coupled plasma (ICP) reactor. Ar/GeH 4 and Ar/SiH 4 gas mixtures were supplied to separate plasma zones at a pressure of 1 Torr to promote growth of Ge cores and Si shells. The negatively charged CSNPs are trapped electrostatically in the vicinity of the antennas where the plasma is generated and where the majority of particle growth occurs. Particles that grow to a critical size are then de-trapped by fluid drag due to neutral gas flow. A two-dimensional hybrid plasma model coupled with a three-dimensional kinetic NP transport model were utilized to resolve plasma chemistry and NP growth processes that take place on distinct timescales. The trends in CSNP properties and trapping mechanisms associated with flow rate, applied ICP power and inlet precursor fraction are discussed. While the spatial distribution of plasma produced radical species can have significant impact on the NP growth process, the NP transport dynamics are what ultimately dictates the growth environment that is unique to each particle and so determines their final dimension and composition. The key to optimizing reactor conditions involves controlling the spatial density of growth species and plasma profile as a means to tailor particle trapping dynamics suitable to produce CSNPs for a specific application.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Synthesizing Carbon‐Supported, High‐Loading, Ultra‐Small Pt 3 Ni Nanoparticles via Tuning the Surface Electrostatic Effect

Carbon‐supported nanoparticles (NPs) are widely used as catalysts in fuel cells and electrolyzers. While it is well known that NPs with smaller size and higher loading often lead to better catalytic activity, they remain challenging to synthesize due to the weak control over the surface properties of the support. Herein, a facile approach to synthesize carbon‐supported, high‐loading, and ultra‐small Pt 3 Ni NPs via applying thermal shock on strongly interacted carbon support with metal salt is reported. Specifically, sodium citrate is introduced into the precursor solution and substrate mixture, which induces strong electrostatic effect between metal salts and carbon particles that markedly improves precursor anchoring and dispersion, thereby achieving high particle loading as well as small size and distribution. As a proof‐of‐concept, the synthesis of Pt 3 Ni NPs supported on carbon black with particle size of 1.56 ± 0.36 nm at 30 wt% loading and 1.66 ± 0.56 nm at 40 wt% loading is reported, where the sizes are among the smallest while the loadings are among the highest in the literature. This approach can be readily extended to many compositions and substrates, with tunable particle size and loading, thereby substantially expanding the synthesis space for NP catalysts in various electrochemical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A 1D Model for Nucleation of Ice From Aerosol Particles: An Application to a Mixed‐Phase Arctic Stratus Cloud Layer

Abstract Mixed‐phase clouds (MPCs) have been identified as significant contributors to uncertainties in climate projections, attributable to model representation of processes controlling the formation and loss of supercooled water droplets and ice particles from the atmosphere. Arctic MPCs are commonly widespread and long‐lived, with sustained ice crystal formation processes that challenge current understanding. This study examines the ice‐nucleating particle (INP) reservoir dynamics governing immersion‐mode heterogeneous freezing in an observed case of Arctic MPCs using a simplified 1D aerosol‐cloud model. The model setup includes prescribed dynamical forcings and thermodynamic profiles, and represents INPs as multicomponent and polydisperse particle size distributions. Diagnostic and prognostic approaches to immersion freezing parameterization are compared, including time‐independent (singular) number‐ and surface area‐based descriptions and a time‐dependent description following classical nucleation theory (CNT). The choice of freezing parameterization defines the size of the INP reservoir. The CNT‐based description yields an orders of magnitude larger INP reservoir than the singular parameterizations, which is the dominant factor for sustained ice crystal formation. The efficiency of the freezing process and cloud cooling are of secondary importance. A diagnostic treatment neglecting INP loss is only accurate when the INP reservoir size is large and INP depletion weak. Since a larger INP reservoir sustains ice crystal formation substantially longer, and ice water path scales with ice crystal concentrations for the conditions considered, resolving the source of differences in INP reservoir dynamics due to model implementation is a high priority for advancing climate model physics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Large-Scale Molecular Dynamics Simulation of the Dehydration of a Suspension of Smectite Clay Nanoparticles

Fine-grained sediments and sedimentary rocks play important roles in a variety of modern energy technologies from petroleum geology to geological carbon sequestration and radioactive waste management. However, despite their utility and ubiquity, many of their properties remain poorly understood. In particular, the ability to predict the permeability and mechanics of these media remains a persistent fundamental challenge in the geosciences. In the present work, we show how large-scale classical molecular dynamics (MD) simulations can help interpret the properties of fine-grained sedimentary material. All-atom simulations containing 30 discrete clay particles are utilized to understand the evolution of a clay nanoparticle suspension during its progressive dehydration. Microstructural (pore size distribution, tortuosity, anisotropy), thermodynamic (enthalpy and free energy of hydration, anion exclusion), mechanical (total suction), and transport properties (diffusion coefficient tensors of water and sodium) are calculated and compared to the experiment. Overall, our results provide new insight into the coupled chemistry, mechanics, and transport properties of disordered nanoparticle assemblages and shed light upon the important role of water films in controlling these properties.

02 PETROLEUM↗
DOE OSTI2021

Synergy of Graphene Nanoribbons and Graphene Sheets for High-Rate Lithium-Sulfur Batteries

According to the increasing demands for shortening the battery charging time, high current rate (C-rate) performances become more significant in practical applications. With a higher theoretical capacity, lithium-sulfur batteries are treated as promising candidates for the next-generation batteries. In this work, the utilization of graphene nanoribbons (GNRs) exhibits the benefits in conductivity and other electrochemical performances, especially for high-rate applications. With air-controlled electrospray as the method, carbon encapsulated sulfur particles, poly(acrylic acid), reduced graphene oxide (rGO) sheets, and GNRs are mixed and directly deposited onto the carbon coated aluminum collector, to employ as the cathode. The scanning electron microscopy (SEM) imaging exhibits that the two-dimensional structure of GNRs helps construct inter-connected networks. This improved structure of cathode can increase the electroconductivity, confirmed by the electrochemical impedance spectroscopy (EIS), and modify the porosity, indicated through pore size distribution profiles. In this way, the polysulfides can be more efficiently trapped and utilized, realizing the promising behavior with faster charge transfer. In terms of the cycling performance at 0.2 C, the batteries with GNRs can perform 18% higher in capacity than those without GNRs, without decreasing the charge retention. According to the rate-capability tests, systems with GNRs can achieve enhanced performance compared to batteries with precursor carbon nanotubes (CNTs), especially at high C-rates. At 2 C, with 80 wt % of graphene-based materials as GNRs, batteries can achieve an increase in capacity by 78% and 41% compared with systems without GNRs and those with CNTs, respectively. Accordingly, the results testify the synergy of GNRs and rGO sheets in Li-S batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

Observations of particle number size distributions and new particle formation in six Indian locations

Atmospheric new particle formation (NPF) is a crucial process driving aerosol number concentrations in the atmosphere; it can significantly impact the evolution of atmospheric aerosol and cloud processes. This study analyses at least 1 year of asynchronous particle number size distributions from six different locations in India. We also analyze the frequency of NPF and its contribution to cloud condensation nuclei (CCN) concentrations. We found that the NPF frequency has a considerable seasonal variability. At the measurement sites analyzed in this study, NPF frequently occurs in March–May (pre-monsoon, about 21% of the days) and is the least common in October–November (post-monsoon, about 7% of the days). Considering the NPF events in all locations, the particle formation rate (J SDS ) varied by more than 2 orders of magnitude (0.001–0.6 cm –3 s –1 ) and the growth rate between the smallest detectable size and 25nm (GR SDS-25nm ) by about 3 orders of magnitude (0.2–17.2nm h –1 ). We found that J SDS was higher by nearly 1 order of magnitude during NPF events in urban areas than mountain sites. GR SDS did not show a systematic difference. Our results showed that NPF events could significantly modulate the shape of particle number size distributions and CCN concentrations in India. The contribution of a given NPF event to CCN concentrations was the highest in urban locations (4.3 × 10 3 cm –3 per event and 1.2 × 10 3 cm –3 per event for 50 and 100nm, respectively) as compared to mountain background sites (2.7 × 10 3 cm –3 per event and 1.0 × 10 3 cm –3 per event, respectively). We emphasize that the physical and chemical pathways responsible for NPF and factors that control its contribution to CCN production require in situ field observations using recent advances in aerosol and its precursor gaseous measurement techniques.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Size and Structure Effects of Carbon-Supported Ruthenium Nanoparticles on Waste Polypropylene Hydrogenolysis Activity, Selectivity, and Product Microstructure

Hydrogenolysis of plastic waste using Ru-based catalysts is promising for deconstructing polyolefins into lower molecular weight products. Yet, the effect of catalyst atomic structure and size on activity and product selectivity is poorly understood. Herein, we expose the effect of metal particle size and atomic structure on isotactic-polypropylene (i-PP) hydrogenolysis over Ru supported on carbon. Despite similar molecular weight distributions of solid and liquid products, their physical properties are distinct due to different chain regio-irregular CH3 sequences of steric pentads containing racemo configurations. We propose that i-PP hydrogenolysis entails an interplay of C–C bond scission and stereoisomerization. The active site’s local electronic environment and structure dictate the former, whereas polymer–catalyst surface interactions creating suitable polymer conformations control the latter. C–C scission and stereoisomerization are structure-sensitive. Small, disordered nanoclusters are effective in C–C bond scission, whereas larger metal nanoparticles promote stereoisomerization. Finally, we hypothesize that a heterogeneous distribution of metal active sites is essential for deconstruction and product (lubricant base oil) quality control.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Comprehensive Northern Hemisphere Particle Microphysics Data Set From the Precipitation Imaging Package

Microphysical observations of precipitating particles are critical data sources for numerical weather prediction models and remote sensing retrieval algorithms. However, obtaining coherent data sets of particle microphysics is challenging as they are often unindexed, distributed across disparate institutions, and have not undergone a uniform quality control process. This work introduces a unified, comprehensive Northern Hemisphere particle microphysical data set from the National Aeronautics and Space Administration precipitation imaging package (PIP), accessible in a standardized data format and stored in a centralized, public repository. Data is collected from 10 measurement sites spanning 34° latitude (37°N–71°N) over 10 years (2014–2023), which comprise a set of 1,070,000 precipitating minutes. The provided data set includes measurements of a suite of microphysical attributes for both rain and snow, including distributions of particle size, vertical velocity, and effective density, along with higher-order products including an approximation of volume-weighted equivalent particle densities, liquid equivalent snowfall, and rainfall rate estimates. The data underwent a rigorous standardization and quality assurance process to filter out erroneous observations to produce a self-describing, scalable, and achievable data set. Case study analyses demonstrate the capabilities of the data set in identifying physical processes like precipitation phase-changes at high temporal resolution. Bulk precipitation characteristics from a multi-site intercomparison also highlight distinct microphysical properties unique to each location. This curated PIP data set is a robust database of high-quality particle microphysical observations for constraining future precipitation retrieval algorithms, and offers new insights toward better understanding regional and seasonal differences in bulk precipitation characteristics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Electrochemical Imaging of Precisely‐Defined Redox and Reactive Interfaces

Abstract Understanding the diverse electrochemical reactions occurring at electrode‐electrolyte interfaces (EEIs) is a critical challenge to developing more efficient energy conversion and storage technologies. Establishing a predictive molecular‐level understanding of solid electrolyte interphases (SEIs) is challenging due to the presence of multiple intertwined chemical and electrochemical processes occurring at battery electrodes. Similarly, chemical conversions in reactive electrochemical systems are often influenced by the heterogeneous distribution of active sites, surface defects, and catalyst particle sizes. In this mini review, we highlight an emerging field of interfacial science that isolates the impact of specific chemical species by preparing precisely‐defined EEIs and visualizing the reactivity of their individual components using single‐entity characterization techniques. We highlight the broad applicability and versatility of these methods, along with current state‐of‐the‐art instrumentation and future opportunities for these approaches to address key scientific challenges related to batteries, chemical separations, and fuel cells. We establish that controlled preparation of well‐defined electrodes combined with single entity characterization will be crucial to filling key knowledge gaps and advancing the theories used to describe and predict chemical and physical processes occurring at EEIs and accelerating new materials discovery for energy applications.

Edgecomb, Joseph↗
DOE OSTI2024

Electrochemical Imaging of Precisely‐Defined Redox and Reactive Interfaces

Abstract Understanding the diverse electrochemical reactions occurring at electrode‐electrolyte interfaces (EEIs) is a critical challenge to developing more efficient energy conversion and storage technologies. Establishing a predictive molecular‐level understanding of solid electrolyte interphases (SEIs) is challenging due to the presence of multiple intertwined chemical and electrochemical processes occurring at battery electrodes. Similarly, chemical conversions in reactive electrochemical systems are often influenced by the heterogeneous distribution of active sites, surface defects, and catalyst particle sizes. In this mini review, we highlight an emerging field of interfacial science that isolates the impact of specific chemical species by preparing precisely‐defined EEIs and visualizing the reactivity of their individual components using single‐entity characterization techniques. We highlight the broad applicability and versatility of these methods, along with current state‐of‐the‐art instrumentation and future opportunities for these approaches to address key scientific challenges related to batteries, chemical separations, and fuel cells. We establish that controlled preparation of well‐defined electrodes combined with single entity characterization will be crucial to filling key knowledge gaps and advancing the theories used to describe and predict chemical and physical processes occurring at EEIs and accelerating new materials discovery for energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Computational fluid dynamics modeling and analysis of silica nanoparticle synthesis in a flame spray pyrolysis reactor

Flame Spray Pyrolysis (FSP) is a method for large-scale production of nanoparticles and nanoscale powders employed in a wide range of industrial applications. Particle size and morphology are complex functions of the physicochemical phenomena occurring in the FSP reactor. An extensive study of FSP-related phenomena can be utilized to develop effective strategies for achieving desired particle size/morphology and scaling up the overall yield of an FSP system. In this work, a computational fluid dynamics (CFD) model of an FSP reactor is developed to simulate the coupling of key phenomena involved in the particle synthesis process: liquid spray breakup and evaporation, mixing, combustion, and particle formation/growth of silica nanoparticles. Herein, the particle sizes and their distributions from the CFD simulations are validated against experimental data. Subsequently, the simulations are utilized to investigate the impact of process parameters on the resultant flame dynamics and particle growth. Firstly, the CFD results show that the particle sizes are strongly correlated with the precursor concentration in the solvent. At lower precursor concentrations, the spread of the distribution is relatively insensitive to the value of the concentration. At higher concentrations, the spread is higher as the collision probability between particles is higher. Secondly, increasing the pilot flow rate increases the length of the pilot flames impacting the local ignition location of the spray flame. Lastly, it is shown that the dispersion gas flow rate strongly influences the spray flame shape. This shape can be used for control of particle growth as it helps determine the regions of high temperature and the residence time of the particles in the high temperature region enabling the design and process optimization of the FSP reactor.

42 ENGINEERING↗
DOE OSTI2022

Relativistic non-thermal particle acceleration in two-dimensional collisionless magnetic reconnection

Magnetic reconnection, especially in the relativistic regime, provides an efficient mechanism for accelerating relativistic particles and thus offers an attractive physical explanation for non-thermal high-energy emission from various astrophysical sources. I present a simple analytical model that elucidates key physical processes responsible for reconnection-driven relativistic non-thermal particle acceleration in the large-system, plasmoid-dominated regime in two dimensions. The model aims to explain the numerically observed dependencies of the power-law index $p$ and high-energy cutoff $\gamma _c$ of the resulting non-thermal particle energy spectrum $f(\gamma )$ on the ambient plasma magnetization $\sigma$ , and (for $\gamma _c$ ) on the system size $L$ . In this self-similar model, energetic particles are continuously accelerated by the out-of-plane reconnection electric field $E_{\rm rec}$ until they become magnetized by the reconnected magnetic field and eventually trapped in plasmoids large enough to confine them. The model also includes diffusive Fermi acceleration by particle bouncing off rapidly moving plasmoids. I argue that the balance between electric acceleration and magnetization controls the power-law index, while trapping in plasmoids governs the cutoff, thus tying the particle energy spectrum to the plasmoid distribution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Combined Effect of the Wegener–Bergeron–Findeisen Mechanism and Large Eddies on Microphysics of Mixed-Phase Stratiform Clouds

Abstract The process of glaciation in mixed-phase stratiform clouds was investigated by a novel Lagrangian–Eulerian model (LEM) in which thousands of adjoining Lagrangian parcels moved within a turbulent-like velocity field with statistical parameters typical of the Arctic boundary layer. We used detailed bin microphysics to describe the condensation/evaporation processes in each parcel, in which droplets, aerosols, and ice particles were described using size distributions of 500 mass bins. The model also calculated aerosol mass inside droplets and ice particles. Gravitational sedimentation of droplets and ice particles was also accounted for. Assuming that droplet freezing is the primary source of ice particles, the Arctic clouds observed in Indirect and Semi-Direct Aerosol Campaign (ISDAC) were successfully simulated. The model showed that at a low ice particle concentration typical of ISDAC, large vortices (eddies) led to a quasi-stationary regime, in which mixed-phase St existed for a long time. The large eddies controlled the water partitioning in the mixed-phase clouds. Droplets formed and grew in updrafts, typically reaching the cloud top, and evaporated in downdrafts. Ice particles grew in updrafts and downdrafts. The Wegener–Bergeron–Findeisen (WBF) mechanism was efficient in downdrafts and some parts of updrafts, depending on ice concentration and vertical velocity. At low ice concentrations, the effect of ice on the phase partitioning was negligible. In this regime, liquid droplets were found near the cloud top, whereas ice particles precipitated through the cloud base. When ice concentration exceeded about 10 L −1 , the WBF mechanism led to glaciation of almost the entire cloud, with the exception of narrow cloud regions associated with strong updrafts. At ice particle concentrations of a few tens per liter, the oscillatory regime took place due to the ice–liquid interaction. The microphysical structure of mixed-phase St forms as a combined effect of cloud dynamics (large eddies) and the WBF mechanism.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

NCSU RDMA data

NCSU RDMA Data Level b1: QC checks applied to measurements Data Format: CSV Description: See "instrument description Site: Houston, TX; Tracking Aerosol Convection interactions ExpeRiment (HOU) Location: Houston, TX; AMF1 (main site for TRACER) Facility Code: M1 Category: Aerosol Properties Data Type: PI Data Source Instrument/Data: Nano-Scanning Mobility Particle (SMPS); A Radial Differential Mobility Analyzer (RDMA) coupled with 1 Condensation Particle Counter Start Date: 2022-06-01 End Date: 2022-9-26 Contact PI: Markus Petters (mdpetter@ncsu.edu) Funding Source: DOE ASR award US Department of Energy, Office of Science, Biological and Environment Research (grant no. DE-SC 0021074) Instrument description The NCSU RDMA was operated at a sheath-to-sample flow ratio of 5:1.5 L min−1. The RDMA was configured to scan from 5 to 55 nm. It was located into the temperature-controlled trailer adjacent to the NCSU Flux Tower to observe size distributions of the aerosols.The sample line was dried with three silica-gel driers in series, and then neutralized with X-ray neutralizer. Please contact mdpetter@ncsu.edu for further information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Modeling Solution Drying by Moving a Liquid-Vapor Interface: Method and Applications

A method of simulating the drying process of a soft matter solution with an implicit solvent model by moving the liquid-vapor interface is applied to various solution films and droplets. For a solution of a polymer and nanoparticles, we observe “polymer-on-top” stratification, similar to that found previously with an explicit solvent model. Furthermore, “polymer-on-top” is found even when the nanoparticle size is smaller than the radius of gyration of the polymer chains. For a suspension droplet of a bidisperse mixture of nanoparticles, we show that core-shell clusters of nanoparticles can be obtained via the “small-on-outside” stratification mechanism at fast evaporation rates. “Large-on-outside” stratification and uniform particle distribution are also observed when the evaporation rate is reduced. Polymeric particles with various morphologies, including Janus spheres, core-shell particles, and patchy particles, are produced from drying droplets of polymer solutions by combining fast evaporation with a controlled interaction between the polymers and the liquid-vapor interface. Our results validate the applicability of the moving interface method to a wide range of drying systems. The limitations of the method are pointed out and cautions are provided to potential practitioners on cases where the method might fail.

36 MATERIALS SCIENCE↗
DOE OSTI2023

TGA Study of the Reaction Kinetics of a CuFeMnAlO 4+δ Oxygen Carrier for Methane Chemical Looping Combustion under High Pressure and Atmospheric Pressure Conditions

Reduction and oxidation kinetics of a CuFeMnAlO 4+δ oxygen carrier for methane were studied using an atmospheric thermogravimetric analyzer (TGA) and a pressurized TGA. Important parameters such as temperature (500–900 °C), particle size distribution (150–650 μm), and partial pressures of reactants (methane and oxygen) were evaluated. Results showed that the reduction of the oxygen carrier was not affected by particle size distribution studied in this work, and that above 750 °C, the effect of the temperature on oxygen carrier reduction started to diminish. The reaction time approaches an asymptotic limit as methane partial pressure increases. For oxygen carrier oxidation, it was found that the rate of oxidation increased with increasing oxygen concentration. The effect of the oxygen concentration was more noticeable when the oxygen concentration was below 7.5%. Because of the inherent feature of the oxygen carrier, its chemical looping with oxygen uncoupling property was also assessed. A phase boundary-controlled shrinking sphere model was used to model the test data from the TGAs. Modeling results showed that the oxygen carrier reduction had a reaction order of 1 with an activation energy of ∼46 kJ/mol. Oxygen carrier oxidation demonstrated a reaction order of 1.1 with an activation energy of ∼55 kJ/mol. Additionally, the differences of the experimental results between the atmospheric pressure TGA and the pressurized TGA were discussed in detail and the limitations of the pressurized TGA were highlighted.

Hydrocarbons↗
DOE OSTI2021

Accelerator Real-time Edge AI for Distributed Systems (READS) (Proposal)

Over the last decade, Machine Learning (ML) technologies have slowly made their way into the accelerator community. Rapid advances in recent years in deep learning, particularly reinforcement learning for control system applications and the accessibility of deep learning in embedded hardware, have generated renewed interest and spawned a number of applications. The Fermilab Accelerator Complex, shown in Fig. 1, has provided High Energy Physics (HEP) experiments with proton beams for nearly fifty years. The current focus of the laboratory is its world-class experimental program at the intensity frontier. While increasing beam intensity certainly presents its own challenges, preserving beam size while minimizing beam losses – particles lost through interactions with the beam vacuum pipe – turns out to be, in many ways, the main challenge. The accelerator is controlled via a complex system of hundreds of thousands of devices. Enabling fine tuning and real-time optimization of their parameters using ML methods and stepping beyond experience-based reasoning of human operators are key to the success of future intensity upgrades. Our objective will be to integrate ML into accelerator operations and furthermore, provide an accessible framework, which can also be used by a broad range of other accelerator systems with dynamic tuning needs.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

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↗