Search NASA⌕ Search

SEARCH · Search NASA

Results for “Injection”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Utah FORGE: Injection and Production Test results and Reports from August 2024

This dataset includes results and reports from the injection/production test for wells 16A(78)-32 and 16B(78)-32 in August, 2024 at Utah FORGE. Materials include injection, post stimulation production, flow rate, gamma, temperature and pressure survey results. For the respective wells, injection and production profile results and interpretations are provided in .xlsx and .las file formats. Additionally, for both wells, preliminary and final reports are included and provide logging procedures and visualizations of the results.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Impurity Powder Injection Experiments in the Large Helical Device

The Impurity Powder Dropper (IPD) is a device capable of injecting controlled amounts of sub-millimetre powder into the plasma under the action of gravity. In 2019 the IPD was first installed on the Large Helical Device (LHD) in Japan, with the aim of improving the plasma performances through real time boronization and assessing the compatibility of this technique with steady state operation. Extensive series of experiments have been performed using the IPD, focused on the improvement of the plasma performance via low-Z powder injection and the understanding of the underlying physical phenomena. In this article, we review the experiments that took place in the period 2019-2024. The main results include the demonstration of the improvement of the wall conditions (reduction of intrinsic impurity content, wall recycling) both on a shot-to-shot basis and in real time. Furthermore, a reduced-turbulence improved confinement regime has been observed coincident with powder injection, resulting in an increase of the plasma temperature of the order of 25%, with enhancements that can reach up to 50% for ion temperature.

Nespoli, F. [Princeton Plasma Physics Laboratory (↗
DOE OSTI2024

CFD unified approach under Eulerian–Lagrangian framework for methanol and gasoline direct injection sprays in evaporative and flash boiling conditions

Innovative synthetic fuels for advanced propulsion systems, such as methanol and ammonia, and synthetic blended fuels (E00, E10, and E30), known for their high volatility, are often injected directly into combustion chambers. It follows that Eulerian–Lagrangian spray models need to accurately capture the spray collapse as a consequence of flash boiling onset and be capable of proficiently handling the preferential evaporation of multi-component fuels in evaporative scenarios. So, we performed the assessment of an Eulerian–Lagrangian CFD code for simulating methanol and E00 gasoline blend sprays in both early and late injection conditions involving flash boiling conditions and preferential evaporation. The adoption of an effervescent breakup model and of a non-equilibrium phase transition model for the discrete phase allows the adoption of a setup that is almost completely free from specific constant tuning, especially for what concerns the breakup model. We validated the simulations using experimental PLV maps of methanol and E00 sprays issued from the ECN Spray M injector. The results highlight a significantly different morphology of the methanol spray compared to the E00 one under late injection conditions. Under stratified combustion, low-volatile fuels are likely to be ignited first, and the flame propagates toward the high-volatile fuels. In conclusion, the spray collapse was also correctly reproduced, inducing the presence of a low-pressure zone and modifying the spray morphology.

E00↗
DOE OSTI2026

Silyl Hot-Injection Versus Thiocyanate Heat-Up Synthesis of Chalcohalides: Pushing the Size and Composition Envelope

Chalcohalide semiconductors are rapidly gaining traction as stable, biocompatible materials for energy conversion applications. While the solid-state synthesis of bulk chalcohalides is relatively well-developed, the colloidal chemistry of these materials is still in its early stages. Colloidal semiconductors are often advantageous in device fabrication due to the cost effectiveness of solution processing. Thus, we aim to increase the utility of chalcohalides in device fabrication by establishing solution phase chemistry of promising compositions. We show that silyl hot-injection is a versatile and effective method of making colloidal PnChI (Pn = Sb, Bi; Ch = S, Se) and Sn 2 PnS 2 I 3 (Pn = Sb, Bi) chalcohalides of tunable sizes and compositions. Furthermore, we demonstrate the preparation of mixed-pnictide chalcohalides through direct hot-injection and/or postsynthetic cation exchange, the latter being one of the few reported instances in chalcohalides. Additionally, we use the thiocyanate heat-up approach in combination with density functional theory to study halide mixing in quaternary tin chalcohalides. By pushing the limits of each synthetic technique, we have designed more soluble chalcohalides with tunable compositions while also gaining a better understanding of the efficacy of each procedure in respect to thin film and subsequent device fabrication. In addition to size and composition tuning, silyl hot-injection can help facilitate the future development and wide-scale application of chalcohalide-based devices by expanding the selection of solution-processable chalcohalides.

halogens↗
DOE OSTI2026

Hot-Carrier Injection and Millisecond Charge Separation from a Robust Heteroleptic Iron(II) Chromophore Immobilized on TiO 2

The synthesis, spectroscopic characterization, computational analysis, and photoelectrochemical behavior of a new iron-based chromophore, [(Cpy) 2 Fe- (deeb)](PF 6 ) 2 (Fe(Cpy) 2 (deeb)), where Cpy is 1-methyl-3-(2-pyridyl)imidazole and deeb is 4,4’-(CO 2 CH 2 CH 3 ) 2 -2,2’-bipyridine, is reported. Electrochemically reversible waves assigned to a metal-centered E o (Fe III/II ) = +0.48 and a ligand-centered E o (Fe 2+/+ ) = −1.47 V vs Fc +/0 reduction were evident in cyclic voltammetry measurements. The combination of a strong σ-donor and a π-acceptor lowered the energy of the metal-toligand charge-transfer (MLCT) excited state relative to the metal-centered state. Two MLCT transitions appear in the visible region at 424 and 580 nm. TDDFT calculations revealed that the lower-energy band was well formulated as Fe(II)→deeb, and the higher-energy transition was charge transfer to both the deeb and Cpy ligands. Resonance Raman spectroscopy supports these findings showing enhanced deeb vibrational modes with 532 nm excitation, both deeb and Cpy modes with 473 nm excitation, and exclusively Cpy with 405 nm excitation. Ultrafast spectroscopy reveals a short-lived (∼2 ps) MLCT excited state and a longer-lived (∼20 ps) metal-centered state. Efficient methods to deprotect the ester groups and anchor the complex to mesoporous TiO 2 (anatase) thin films in high surface coverages, Fe(Cpy) 2 (dcb)|TiO 2 σ = 3 × 10 −8 mol/cm 2 , were established. Pulsed light excitation of Fe(Cpy) 2 (dcb)|TiO 2 resulted in rapid excited state injection (k inj > 10 8 s −1 ) and formation of a charge-separated state, Fe III (Cpy) 2 (dcb)|TiO 2 (e), which persists on the millisecond time scale before returning cleanly to the ground state with secondorder kinetics. Injection yields measured 50 ns after light excitation were found to double from Φ = 0.15 with green (532 nm) light to 0.30 with blue (457 nm) light excitation. Incident photon-to-current efficiency (% IPCE) measurements as a function of excitation wavelength in a 0.5 M LiI/I 2 /CH 3 CN electrolyte provide clear evidence for band-selective “hot carrier” injection from the remote Cpy-localized excited state. Collectively, the spectroscopic and photoelectrochemical data indicate that a semiconductor can intercept hot electrons from iron chromophores even when the excited-state dipole is oriented away from the surface-anchoring ligand.

Charge transfer↗
DOE OSTI2025

Injection locking and coupling dynamics in superconducting nanowire-based cryogenic oscillators

Oscillators designed to function at cryogenic temperatures play a critical role in superconducting electronics and quantum computing by providing stable, low-noise signals with minimal energy loss. Here, in this work, we present a comprehensive numerical study of injection locking and mutual coupling dynamics in superconducting nanowire (ScNW)-based cryogenic oscillators. Using the design space of a standalone ScNW-based oscillator, we investigate two critical mechanisms that govern frequency synchronization and signal coordination in cryogenic computing architectures: (1) injection locking induced by an external AC signal with a frequency near the oscillator's natural frequency, and (2) the mutual coupling dynamics between two ScNW oscillators under varying coupling strengths. We identify key design parameters—such as shunt resistance, nanowire inductance, and coupling strength—that govern the locking range. Additionally, we examine how the amplitude of the injected signal affects the amplitude of the locked oscillation, offering valuable insights for power-aware oscillator synchronization. Furthermore, we analyze mutual synchronization between coupled ScNW oscillators using capacitive and resistive coupling elements. Our results reveal that the phase difference between oscillators can be controlled by tuning the coupling strength, enabling programmable phase-encoded information processing. These findings could enable building ScNW-based oscillatory neural networks, synchronized cryogenic logic blocks, and on-chip cryogenic resonator arrays.

Artificial neural networks↗
DOE OSTI2025

Aligning thermal and current quenches with a high density low-Z injection

The conventional approach for thermal quench (TQ) mitigation in a tokamak disruption is through a high- Z impurity injection that radiates away the plasma’s thermal energy before it reaches the wall. The downside is a robust Ohmic-to-runaway current conversion due to the radiatively clamped low post-thermal-quench electron temperature. An alternative approach is to deploy a low- Z (either deuterium or hydrogen) injection that aims to slow down the TQ, and ideally aligns it with the current quench (CQ). This approach has been investigated here via 3D MHD simulations using the PIXIE3D code. By boosting the hydrogen density, a fusion-grade plasma is dilutionally cooled at approximately the original pressure. Energy loss to the wall is controlled by a Bohm outflow condition at the boundary where the magnetic field intercepts a thin plasma sheath at the wall, in addition to Bremsstrahlung bulk losses. Robust MHD instabilities proceed as usual, while the collisionality of the plasma has been greatly increased and parallel transport is now in the Braginskii regime. The main conclusion of this study is that the decreased transport loss along open field lines due to a sufficient low- Z injection slows down the TQ rate to the order of 20 ms, aligned with the CQ timescale for a 15 MA ITER plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Numerical studies of collinear laser-assisted injection from a foil for plasma wakefield accelerators

We present a laser-assisted electron injection scheme for beam-driven plasma wakefield acceleration. The laser is collinear with the driver and triggers the injection of hot electrons into the plasma wake by interaction with a thin solid target. We present a baseline case using the AWAKE Run 2 parameters and then perform variations on key parameters to explore the scheme. It is found that the trapped witness electron charge may be tuned by altering laser parameters, with a strong dependence on the phase of the wake upon injection. Normalized emittance settles at the order of micrometres and varies with witness charge. The scheme is robust to misalignment, with a 1/10th plasma skin-depth offset ( 20 μ m for the AWAKE case) having a negligible effect on the final beam. The final beam quality is better than similar existing schemes, and several avenues for further optimization are indicated. The constraints on the AWAKE experiment are very specific, but the general principles of this mechanism can be applied to future beam-driven plasma wakefield accelerator experiments. Published by the American Physical Society 2024

Physics↗
DOE OSTI2024

Guided Mode Evolution and Ionization Injection in Meter-Scale Multi-GeV Laser Wakefield Accelerators

Here, we show that multi-GeV laser wakefield electron accelerators in meter-scale, low density hydrodynamic plasma waveguides operate in a new nonlinear propagation regime dominated by sustained beating of lowest order modes of the ponderomotively modified channel; this occurs whether or not the injected pulse is linearly matched to the guide. For a continuously doped gas jet, this emergent mode beating effect leads to axially modulated enhancement of ionization injection and a multi-GeV energy spectrum of multiple quasimonoenergetic peaks; the same process in a locally doped jet produces single multi-GeV peaks with <10% energy spread. A three-stage model of drive laser pulse evolution and ionization injection characterizes the beating effect and explains our experimental results.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Injection simulations of space charge dominated proton beams in IOTA

A 2.5 MeV proton injector is being constructed for the IOTA ring at Fermilab to study the interaction of nonlinear integrable optics (NIO) with high space charge beams. Space charge in the transport line from the RFQ to the injection location has a significant current dependent effect on the phase space. Simulation studies to support efficient injection of intense bunches into IOTA are presented, included schemes to inject directly into NIO lattices.

Accelerator Physics↗
DOE OSTI2024

Measured vs. Calculated Dose Rates During Ring Injection Dump Replacement

One of the most irradiated Spallation Neutron Source (SNS) accelerator components is the ring injection dump (RID), which is located downstream of the accumulator ring injection section. The unstripped and only partially stripped H - beam, about 5% of the full SNS beam current, is discarded in the injection into the accumulator ring and is redirected to the RID. According to the accelerator operation plan, the beam stop and the window assemblies of the existing RID are removed and replaced when they have reached their end-of-life owing to radiation exposure. This procedure, which includes multiple steps, took place during a facility maintenance period in March 2023. To support work planning and meet as low as reasonably achievable (ALARA) requirements during removal and exchange of the components, dose rates were calculated for each stage of the exchange operation. During each stage, dose rates were measured before and after work. This comparison shows that measured dose rates are within a factor of 2 of the predicted (calculated) dose rates.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Study of Particle Loss in Synchrotron Phase Space Injection for ESR Using Weak-Strong Beam-Beam Simulation with Nonlinear Lattice

In this report, we use tracking simulations to investigate synchrotron phase space injection for electron accumulation in the electron storage ring of the Electron Ion Collider. Our simulation model accounts for both beam-beam interactions and lattice nonlinearities. Specifically, we examine how particle loss is influenced by various parameters. Additionally, we conduct a theoretical analysis and derive an analytical formula for the rapid evaluation of particle loss. Our results demon strate the feasibility of synchrotron phase-space injection for the electron storage ring and provide insights to guide parameter selection for the design of the injection line.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Fracture Network Quantification during CO2 Injection

This is the presentation prepared for the ARMA 2025 (59th US Rock Mechanics/Geomechanics Symposium) Conference held in Santa Fe, New Mexico, June 8-11, 2025. Accurate mapping and quantification of these networks are essential to ensure the integrity of CO2 storage reservoirs, understand and reduce potential leakage, and maintain long-term environmental safety. This study presents a novel machine learning-driven approach, integrated with geomechanical analysis, to quantify fracture networks and assess their spatial distribution during CO2 injection. This paper combines microseismic monitoring data with principles of hydraulic diffusivity and geomechanical analysis to characterize reservoir scale fracture network. The novelty of our approach lies in its capacity to assimilate time-dependent pressure data and microseismicity into a cohesive framework, which not only identifies microseismic triggering fronts but also tracks fracture distribution during active injection. Besides, leveraging image log data and analysis our approach also provides another angle of the insights to solidate the fracture networks understanding and geomechanical impacts. Key results from our study include the detection of over 100 distinct fracture clusters across the injection site, with fracture orientations strongly correlated with the prevailing in-situ stress field.

CO2 storage and sequestration↗
DOE OSTI2025

Enabling Next Generation Reaction Injection Molding (RIM) for Lightweight Structures

Replacing metal components in trucks, trailers, and buses with lightweight polymer composites is challenging due to high temperatures and complex manufacturing. The Reaction Injection Molding (RIM) process using Dicyclopentadiene (DCPD) resin offers a solution by producing robust parts with excellent stiffness, impact strength, and resistance properties. Simulations are essential for optimizing this process, predicting defects, and improving quality. However, most commercial software is tailored for thermoplastics, requiring thermoset users to generate their own datasets. In this project, a material data card for DCPD was developed to perform RIM simulations. Design of Experiments (DOE) was used to identify key factors affecting filling, curing, and warpage, aiming to minimize cycle time and defects. The simulations explored varying injection gate parameters (size, location, number) and process conditions (mold/resin temperature, injection/curing pressure). Results showed that gate design significantly impacts filling behavior and defects. A single central gate provided balanced flow with fewer defects, while two corner gates led to more defects. Additionally, lower injection pressure increased filling time, while higher mold temperature accelerated curing but led to more warpage. This optimization framework aims to enhance DCPD part performance and promote sustainable manufacturing by reducing waste and energy consumption. This research has been performed in collaborations with McClarin Composites. The research outcome has been submitted to the Journal of Manufacturing Processes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electron-Ion Collider (EIC) Hadron Storage Ring (HSR) Injection Transport Beamline (Y-Line Ext.) Lattice Design and Magnet Parameters

The preliminary design of the Electron-Ion Collider (EIC) Hadron Storage Ring (HSR) Normal Conducting Injection Beamline ( Y-Line Ext. ) lattice is discussed. The preliminary design includes the periodic cells, matching sections, state of the art Twiss parameters at the HSR injection, the magnet parameters and first order instrumentation placement. Furthermore, the beamline parameters, element coordinates, and other information are discussed. The names of the HSR Injection Beamline elements used in this technical report ( i.e. HD1, HQ1 ) are preliminary and not the official site wide names.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Estimation of radiation fields generated by injected beam losses at the EIC's RCS

This technical note provides a general estimate of radiation fields generated by injection fault events at the electron-ion collider´s (EIC) Rapid Cycling Synchrotron (RCS), calculated with the Monte Carlo particle transport and interaction code FLUKA. Calculations were performed for two major injection loss scenarios that involve iron targets and featured different electron beam energy and current values. The results presented here constitute a first order assessment of several radiological quantities associated with these electromagnetic showers and their potential effect on environmental safety and health (ESH) systems in the vicinity of injection areas.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Dark Energy Survey Year 6 Results: Synthetic-source Injection Across the Full Survey Using Balrog

Synthetic source injection (SSI), the insertion of sources into pixel-level on-sky images, is a powerful method for characterizing object detection and measurement in wide-field, astronomical imaging surveys. Within the Dark Energy Survey (DES), SSI plays a critical role in characterizing all necessary algorithms used in converting images to catalogs, and in deriving quantities needed for the cosmology analysis, such as object detection rates, galaxy redshift estimation, galaxy magnification, star-galaxy classification, and photometric performance. We present here a source injection catalog of 146 million injections spanning the entire 5000 deg 2 DES footprint, generated using the Balrog SSI pipeline. Through this SSI sample, we demonstrate that the DES Year 6 (Y6) image processing pipeline provides accurate estimates of the object properties, for both galaxies and stars, at the percent-level, and we highlight specific regimes where the accuracy is reduced. We then show the consistency between SSI and data catalogs, for all galaxy samples developed within the weak lensing and galaxy clustering analyses of DES Y6. The consistency between the two catalogs also extends to their correlations with survey observing properties (seeing, airmass, depth, extinction, etc.). Lastly, we highlight a number of applications of this catalog to the DES Y6 cosmology analysis, such as estimates of the redshift distribution and lens magnification. This dataset is the largest SSI catalog produced at this fidelity and will serve as a key testing ground for exploring the utility of SSI catalogs in upcoming surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Machine Learning-Based Process Control for Injection Molding of Recycled Polypropylene

The increased interest in artificial intelligence in manufacturing has driven the adoption of machine learning to optimize processes and improve efficiency. A key challenge in injection molding is the variability of recycled materials, which affects part quality and processing stability. This study presents a novel closed-loop process control approach for injection molding, leveraging machine learning to adaptively predict processing inputs and quality outcomes. The methodology was tested on five blends of recycled polypropylene (rPP), using artificial neural networks (ANNs), linear regression, and polynomial regression to model the relationships between material properties and process parameters. The dataset was split 80/20 into training and testing sets. The ANN model was implemented using TensorFlow and Keras, with six hidden layers of 32 neurons per layer, ReLU activation, and an Adam optimizer. Empirical tuning and early stopping were used to optimize performance and prevent overfitting. Predictions were evaluated based on mean absolute error (MAE), mean squared error (MSE), and percentage error. The results showed that yield stress, ultimate elongation, and part weight were accurately predicted within a 5% error for linear and polynomial regression models and within a 10% error for the ANN. However, modulus predictions were less reliable, with errors of ~11% for ANN and linear regression and ~40% for polynomial regression, reflecting the inherent variability of this property in rPP blends. Predictions of processing inputs had errors ranging from 3% to 25%, depending on the model and response variable. No single modeling approach was consistently superior across all responses, highlighting the complexity of the relationship between material properties, process parameters, and quality metrics. Overall, the work demonstrates that closed-loop process control, powered by machine learning, can effectively predict key quality parameters in injection molding of recycled materials. The proposed approach can improve process stability and material utilization, facilitating increased adoption of sustainable materials.

Krantz, Joshua↗