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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Selection, Production, and Properties of Regolith Polymer Composites for Lunar Construction

NASA’s Artemis Program seeks to establish a long-term presence on the Moon to enable scientific exploration and expand the cis-lunar economy by utilizing lunar resources through public-private and international partnerships. Over the next decades, a lunar spaceport will need to be established to provide the services and facilities that are necessary to achieve this goal. Robotic construction technologies using in-situ materials must be developed to build up enabling infrastructure such as launch/landing pads, blast protection, power/communications infrastructure, improved roads, improved operational surfaces, and radiation protection shelters. Kennedy Space Center’s Granular Mechanics and Regolith Operations laboratory at Swamp Works has partnered with SpaceFactory and LERA Consulting Structural Engineers to develop the architectural and structural design of an unpressurized lunar shelter. The shelter, called Lunar Infrastructure Asset (LINA), is designed to support 2.3 m of regolith overburden to protect astronauts and surface assets from radiation, meteoroid impact, thermal gradients/cycling, and to withstand moonquakes. LINA’s structural design criteria and the resulting structure design are detailed in separate papers. A Fused Filament Fabrication (FFF) construction process using regolith polymer composites has been developed and is detailed in a separate publication. This paper presents material formulations and selection rationale for each of the composite components that were examined. Formulations include 70:30, 80:20, and 85:15 wt.% mixture ratios of lunar mare simulant Black Point-1 (BP-1): Polylactic Acid (PLA), 80:20 Lunar Highlands Simulant-1 (LHS-1): PLA and an 80:20 BP-1: PLA formulation with a flow enhancer additive. Test samples were printed in simulated lunar dirty thermal vacuum conditions (-190 °C, 10-3 torr). A series of tests were performed on each formulation to characterize the achieved mixture ratio, mechanical strength properties, off-gassing products during vacuum printing, and porosity and density of printed products. The LHS-1: PLA formulation yielded an advantageous combination of properties and was used in a final test that additively constructed a sub-scaled LINA on regolith simulant in dirty vacuum conditions. The materials and construction process presented in this paper are considered to be at Technology Readiness Level (TRL) 5 with additional testing necessary to characterize long term lunar environmental exposure effects.

lunar infrastructure↗
DOE OSTI2025

Dimuon production in the MicroBooNE detector

This analysis studies the production of the rare signal with two muons (dimuon) in the finalstate at µB using the Booster Neutrino Beam (BNB) as source of neutrino interactions. Themain background source for the dimuon signal are pions. Differentiating muons and pions hasbeen challenging at µB because the tracks left by these particles are almost identical. Thisanalysis faces this problem using a supervised classifier algorithm called boosted decisiontree (BDT). A Monte Carlo simulation (MC) enhanced dimuon signal sample was producedto train a BDT capable of recognizing this signal. A set of variables that show somediscrimination characteristics was used to perform the training. A MC neutrino interactionsimulation sample was used to estimate the background. Estimations of dimuon productionin real data samples were made for different cases. Additionally, an analysis of the systematicuncertainties, fake data studies, and BDT performance checks were obtained.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRSDate not supplied

Pneumatic Sampler (P-Sampler) for the Martian Moons Exploration (MMX)

The Martian Moons eXploration (MMX) mission, led by the Japanese Aerospace Exploration Agency (JAXA), will focus on the exploration of the two Martian moons – Phobos and Deimos (Figure 1). The spacecraft will perform close-up remote sensing and observations of both moons and collect a sample from Phobos for Earth sample return. MMX has set the two mission goals: (1) determining the origin of the Martian moons and (2) observing processes in the circumplanetary environment of Mars, based on remote sensing, in-situ observations, and laboratory analyses of returned samples of Phobos regolith [1-2]. To fulfill the mission goals, MMX employs a double sampling approach: Coring and Pneumatic Samplers (Figure 2).The Coring Sampler (C-Sampler), a core soil tube deployed by a robotic arm, providing access to the building blocks of Phobos beneath the surface (>2 cm), and also collect a mixture of near surface material. The P-Sampler, on the other hand, would selectively sample the surface veneer and provides reference of surface component with the C-Sampler. The double sampling system not only enhances the scientific merits of MMX but also reduces risks associated with the sampling of Phobos. Without enough knowledge of the physical and chemical properties, and the geotechnical conditions of the surface of Phobos (e.g., compositions, temperature gradient/variation, porosity, grain size distribution), having two sampling systems that utilize entirely different sampling approaches is prudent.

Dylan Van Dyne↗
NASA NTRS2000

Modern Microbial Ecosystems are a Key to Understanding Our Biosphere's Early Evolution and its Contributions To The Atmosphere and Rock Record

The survival of our early biosphere depended upon efficient coordination anion- diverse microbial populations. Microbial mats exhibit a 3.46-billion-year fossil record, thus they are the oldest known ecosystems. Photosynthetic microbial mats were key because, today, sunlight powers more than 99 percent of global primary productivity. Thus photosynthetic ecosystems have affected the atmosphere profoundly and have created the most pervasive, easily-detected fossils. Photosynthetic biospheres elsewhere will be most detectible via telescopes or spacecraft. As a part of the Astrobiology Institute, our Ames Microbial Ecosystems group examines the roles played by ecological processes in the early evolution of our biosphere, as recorded in geologic fossils and in the macromolecules of living cells: (1) We are defining the microbial mat microenvironment, which was an important milieu for early evolution. (2) We are comparing mats in contrasting environments to discern strategies of adaptation and diversification, traits that were key for long-term survival. (3) We have selected sites that mimic key environmental attributes of early Earth and thereby focus upon evolutionary adaptations to long-term changes in the global environment. (4) Our studies of gas exchange contribute to better estimates of biogenic gases in Earth's early atmosphere. This group therefore directly addresses the question: How have the Earth and its biosphere influenced each other over time Our studies strengthen the systematics for interpreting the microbial fossil record and thereby enhance astrobiological studies of martian samples. Our models of biogenic gas emissions will enhance models of atmospheres that might be detected on inhabited extrasolar planets. This work therefore also addresses the question: How can other biospheres be recogniZed" Our choice of field sites helps us explore Earth's evolving early environment. For example, modern mats that occupy thermal springs and certain freshwater environments experience conditions such as low O2 and sulfate and high inorganic carbon and sulfide levels that resemble those of ancient marine environments. Later in history, both biologically-induced carbonate precipitation and the trapping and binding of suspended grains of carbonate became a dominant mechanism for carbonate deposition. Modern marine carbonate platforms and alkaline offer good examples of microbiologically-induced calcification. Both marine platforms and solar salterns illustrate microbially-driven trapping and binding. We are also exploring the effects of water composition upon the exchange of biogenic gases with the atmosphere.

DesMarais, David J.↗
NASA NTRS2003

Asian Outflow and Trans-Pacific Transport of Carbon Monoxide and Ozone Pollution: An Integrated Satellite, Aircraft, and Model Perspective

Satellite observations of carbon monoxide (CO) from the Measurements of Pollution in the Troposphere (MOPITT) instrument are combined with measurements from the Transport and Chemical Evolution Over the Pacific (TRACE-P) aircraft mission over the northwest Pacific and with a global three-dimensional chemical transport model (GEOS-CHEM) to quantify Asian pollution outflow and its trans-Pacific transport during spring 2001. Global CO column distributions in MOPITT and GEOS-CHEM are highly correlated (R(exp 2) = 0.87), with no significant model bias. The largest regional bias is over Southeast Asia, where the model is 18% too high. A 60% decrease of regional biomass burning emissions in the model (to 39 Tg/yr) would correct the discrepancy; this result is consistent with TRACE-P observations. MOPITT and TRACE-P also give consistent constraints on the Chinese source of CO from fuel combustion (181 Tg CO/yr). Four major events of trans-Pacific transport of Asian pollution in spring 2001 were seen by MOPITT, in situ platforms, and GEOS-CHEM. One of them was sampled by TRACE-P (26-27 February) as a succession of pollution layers over the northeast Pacific. These layers all originated from one single event of Asian outflow that split into northern and southern plumes over the central Pacific. The northern plume (sampled at 6-8 km off California) had no ozone enhancement. The southern subsiding plume (sampled at 2-4 km west of Hawaii) contained a 8 - 17 ppbv ozone enhancement, driven by decomposition of peroxyacetylnitrate (PAN) to nitrogen oxides (NOx). This result suggests that PAN decomposition in trans-Pacific pollution plumes subsiding over the United States could lead to significant enhancements of surface ozone.

Heald, Colette L.↗
DOE OSTI2026

Cyclic moisture reactivation of calcium sorbents for long duration thermochemical energy storage

The transition to a flexible and reliable energy infrastructure, using electro-thermal energy generation technologies such as geothermal, concentrated solar power, and nuclear, usually demands simultaneous advancement of thermal energy storage (TES) to support on-demand electricity generation and industrial applications while mitigating the inherent intermittency of renewable energy sources and power outages from direct energy generation. Among TES technologies, thermochemical energy storage (TCES) based on calcium looping emerges as a compelling high-power energy storage candidate due to its high reaction enthalpy, compatibility with elevated operating temperatures, and abundance of low-cost materials. However, the long-term durability of calcium-based sorbents for TCES is hindered by surface sintering and particle aggregation, leading to performance degradation over repeated thermal cycles. This study explores a moisture hydration-based strategy to regenerate a degraded calcium sorbent and mitigate performance degradation for long duration TCES. The addition of moisture transforms calcium oxide into calcium hydroxide and produces intercalation water layers, associated with a regenerated surface area and reduced calcium oxide crystallite size. Both these effects are beneficial in restoring the sorbents' reactivity for carbonization. Additionally, an optimized hydration-assisted reactivation protocol balances the recovered energy storage capacity with heating penalty required for moisture removal from hydrated samples, resulting in an enhanced energy storage capacity up to 176% compared to benchmark sorbents that undergo cycling without reactivation after 60 cycles. In conclusion, these results highlight the potential of hydration-assisted reactivation to enhance the long-term performance of TCES, providing an effective pathway to advancing electro-thermal storage technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Path Sampling for Rare Events Boosted by Machine Learning

The study by Jung et al. introduced Artificial Intelligence for Molecular Mechanism Discovery (AIMMD), a novel sampling algorithm that integrates machine learning to enhance the efficiency of transition path sampling (TPS). By enabling on-the-fly estimation of the committor probability and simultaneously deriving a human-interpretable reaction coordinate, AIMMD offers a robust framework for elucidating the mechanistic pathways of complex molecular processes. Here, this commentary provides a discussion and critical analysis of the core AIMMD framework, explores its recent extensions, and offers an assessment of the method’s potential impact and limitations.

Minh, Porhouy [Univ. of Minnesota, Minneapolis, MN↗
DOE OSTI2026

Purcell enhancement of directional edge photocurrent in a van der Waals self-cavity

Cavities provide a means to manipulate the optical and electronic responses of quantum materials by selectively enhancing light-matter interaction at specific frequencies and momenta. While cavities typically involve external structures, exfoliated flakes of van der Waals (vdW) materials can form intrinsic self-cavities due to their small finite dimensions, confining electromagnetic fields into plasmonic cavity modes, characterized by standing-wave current distributions. While cavity-enhanced phenomena are well-studied at optical frequencies, the impact of self-cavities on nonlinear electronic responses—such as directional photocurrent—remains largely unexplored, particularly in the terahertz regime, critical for emerging ultrafast optoelectronic technologies. Here, we report a self-cavity-induced Purcell enhancement of directional photocurrents in the vdW semimetal WTe 2 . Using ultrafast optoelectronic circuitry, we measured coherent near-field THz emission resulting from nonlinear photocurrents excited at the sample edges. We observed enhanced emission at finite frequencies, tunable via excitation fluence and sample geometry, which we attribute to plasmonic interference effects controlled by the cavity boundaries. We developed an analytical theory that captures the cavity resonance conditions and spectral response across multiple devices. Our findings establish WTe 2 as a bias-free, geometry-tunable THz emitter and demonstrate the potential of self-cavity engineering for controlling nonlinear, nonequilibrium dynamics in quantum materials.

condensed-matter physics↗
DOE OSTI2020

Smart Scattering Scanning Near-Field Optical Microscopy

Scattering scanning near-field optical microscopy (s-SNOM) provides spectroscopic imaging from molecular to quantum materials with few nanometer deep subdiffraction limited spatial resolution. However, in its conventional implementation s-SNOM is slow to effectively acquire a series of spatio-spectral images, especially with large fields of view. This problem is further exacerbated for weak resonance contrast or when using light sources with limited spectral irradiance. Indeed, the generally limited signal-to-noise ratio prevents sampling a weak signal at the Nyquist sampling rate. Here, we demonstrate how acquisition time and sampling rate can be significantly reduced by using compressed sampling, matrix completion, and adaptive random sampling, while maintaining or even enhancing the physical or chemical image content. We use fully sampled real data sets of molecular, biological, and quantum materials as ground-truth physical data and show how deep under-sampling with a corresponding reduction of acquisition time by 1 order of magnitude or more retains the core s-SNOM image information. We demonstrate that a sampling rate of up to 6× smaller than the Nyquist criterion can be applied, which would provide a 30-fold reduction in the data required under typical experimental conditions. Furthermore, our smart s-SNOM approach is generally applicable and provides systematic full spatio-spectral s-SNOM imaging with a large field of view at high spectral resolution and reduced acquisition time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

Mars Solar Balloon Landed Gas Chromatograph Mass Spectrometer

A Mars surface lander Gas Chromatograph Mass Spectrometer (GCMS) is described to measure the chemical composition of abundant and trace volatile species and isotope ratios for noble gases and other elements. These measurements are relevant to the study of atmospheric evolution and past climatic conditions. A Micromission plan is under study where a surface package including a miniaturized GCMS would be delivered to the surface by a solar heated hot air balloon based system. The balloon system would be deployed about 8 km above the surface of Mars, wherein it would rapidly fill with Martian atmosphere and be heated quickly by the sun. The combined buoyancy and parachuting effects of the solar balloon result in a surface package impact of about 5 m/sec. After delivery of the package to the surface, the balloon would ascend to about 4 km altitude, with imaging and magnetometry data being taken for the remainder of the daylight hours as the balloon is blown with the Martian winds. Total atmospheric entry mass of this mission is estimated to be approximately 50 kg, and it can fit as an Ariane 5 piggyback payload. The GCMS would obtain samples directly from the atmosphere at the surface and also from gases evolved from solid phase material collected from well below the surface with a Sample Acquisition and Transport Mechanism (SATM). The experiment envisioned in the Mars Micromission described would obtain samples from a much greater depth of up to one meter below the surface, and would search for organic molecules trapped in ancient stratified layers well below the oxidized surface. Insitu instruments on upcoming NASA missions working in concert with remote sensing measurement techniques have the potential to provide a more detailed investigation of mineralogy and the extent of simple volatiles such as CO2 and H2O in surface and subsurface solid phase materials. Within the context of subsequent mission opportunities such as those provided by the Ariane 5 piggyback payload based Micromissions, it is essential to implement an even broader chemical analysis and to enable a significant extension of previous isotope measurements. Such a development would enhance the presently very active study of questions of atmospheric evolution and loss and past climatic conditions. The method selected to implement this program can be based on well-established mass spectrometry techniques. Sampled gas is chemically and physically processed to separate the gas mixture into components using gas chromatograph and related enrichment techniques. This allows trace species to be identified and reveals isotopic distributions in many cases with improved precision. Samples of interest, such as organic molecules, may lie deep below the highly oxidized surface layer and the suggested program includes enhanced sampling techniques to measure volatiles preserved in solid phase material deep below the surface as well as gas from the well mixed atmosphere.

Mahaffy, P.↗
DOE OSTI2024

Distinct Composition‐Dependent Topological Hall Effect in Mn 2‐x Zn x Sb

Abstract Spintronics, an evolving interdisciplinary field at the intersection of magnetism and electronics, explores innovative applications of electron charge and spin properties for advanced electronic devices. The topological Hall effect (THE), a key component in spintronics, has gained significance due to emerging theories surrounding noncoplanar chiral spin textures. This study focuses on Mn 2‐x Zn x Sb, a material crystalizing in centrosymmetric space group with rich magnetic phases tunable by Zn contents. Through comprehensive magnetic and transport characterizations, we found that the high‐Zn ( x > 0.6) samples display THE which is enhanced with decreasing temperature, while THE in the low‐Zn ( x < 0.6) samples show an opposite trend. The coexistence of those distinct temperature dependencies for THE suggests very different magnetic interactions/structures for different compositions and underscores the strong coupling between magnetism and transport in Mn 2‐x Zn x Sb. The findings contribute to understanding topological magnetism in centrosymmetric tetragonal lattices, establishing Mn 2‐x Zn x Sb as a unique platform for exploring tunable transport effects and opening avenues for further exploration in the realm of spintronics.

Nabi, Md Rafique Un↗
DOE OSTI2026

Machine Learning–Augmented Laser-Induced Breakdown Spectroscopy for Spectral Discrimination of Iron Oxalates

Enhanced characterization and phase identification of post-PUREX Pu Oxalates (PuOXA) are pivotal for nonproliferation and pre-detonation nuclear forensics. Despite significant advances in the characterization of PuO 2 samples, little is known about the impact of both the chemical structure and oxidation states of PuOXA (i.e., Pu(III) and Pu(IV)) have on optical emission signatures. Here, we demonstrate the analytical capabilities of laser-induced breakdown spectroscopy (LIBS) applied to Fe(II) and Fe(III) oxalate samples as surrogates for PuOXA, highlighting the discriminating features in the LIBS emission spectra arising from differences in the oxidation states within mixed FeOXA samples. We report the enhancement of spectral feature selection using Principal Component Analysis (PCA), which enables the analytical superiority of machine learning algorithms such as Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Random Forest Regression (RFR) over conventional univariate techniques for phase discrimination and chemometric analysis. Cluster analysis revealed how both matrix effects and laser ablation influence cluster separability by introducing spectral artifacts that misdirect the maximization of variance. PCA-selected emission lines were used in the regression models, demonstrating that both univariate and multivariate linear regression models (i.e., PLSR and SVR) can achieve acceptable performance, with machine learning models outperforming conventional calibration regressions. Furthermore, the application of non-linearly activated PCA-selected emission lines illustrates how simplifying the data while retaining captured variance enables the use of less complex and more computationally efficient models. Furthermore, this is particularly evident in the underperformance of RFR, which suffers from increased computational costs and overfitting owing to its high complexity.

Oxalates↗
DOE OSTI2024

Impact of fused silica debris shields and enhanced mitigation techniques on large-aperture beam-sampling optics for the National Ignition Facility

Here, we show that the large-scale routine use of the fused silica debris shield (FSDS) maintains the ∼100× reduction in damage initiation rate and 70% increase in the install lifetime of a new grating debris shield (GDS) observed during pilot operations. Furthermore, we show that the install lifetimes of recycled GDS optics are nearly tripled using additional mitigation strategies such as expanding mitigation processing to include all damage sites larger than 10 μm (LT10) rather than just larger than 50 μm (LT50) and FSDS. We note that there is still a 50% difference between new and recycled optic installation lifetimes. We show that recycled optics have a 3.5× higher apparent initiation rate than new optics when exposed to nominally identical laser conditions.

FSDS↗
NASA NTRS2024

Enhancing the Protection of Shielded Thermal Protection Systems in Sample Return Spacecraft Against MMOD Impact

Sample return missions seek to collect samples from planets, moons, asteroids, and other planetary bodies and return them to earth for in-depth analysis. Backward planetary protection requirements are often in place for such missions to prevent the introduction of any extra-terrestrial material into the Earth’s biosphere, which could occur if a meteoroid or space debris particle were to damage a critical part of the returning spacecraft. The ability of a shielding system used to mitigate this damage risk is typically characterized by a ballistic limit equation (BLE), which predicts whether or not a protected system or structural element will sustain a critical failure due to a high-speed impact. In this paper, we develop a particle-impact-based BLE for the thermal protection system (TPS) of a sample return spacecraft that is protected by a multi-shock shield. The predictions of the BLE we develop for TPS failure are shown to be consistent with the predictions of hydrocode simulations.

Sample Return Spacecraft↗
NASA NTRS1999

Nonmethane Hydrocarbon Measurements on the North Atlantic Flight Corridor During SONEX

Mixing ratios of nonmethane hydrocarbons (NMHCS) were not enhanced in whole air samples collected within the North Atlantic Flight Corridor (NAFC) during the fall of 1997. The investigation was conducted aboard NASA's DC-8 research aircraft, as part of the Subsonic Assessment-Ozone and Nitrogen Experiment (SONEX). NMHC enhancements were not detected within the general Organized Tracking System (OTS) of the NAFC, nor during two tail-chases of the DC-8's own exhaust. Because positive evidence of aircraft emissions was demonstrated by enhancements in both nitrogen oxides and condensation nuclei during SONEX, the NMHC results suggest that the commercial air traffic fleet operating in the North Atlantic region does not contribute significantly to NMHCs in the NAFC.

Simpson, I. J.↗
DOE OSTI2025

Role of Intersections in Fracture Connectivity

Networks of intersecting fractures often provide the flow paths through subsurface reservoirs. Assessing network connectivity is challenging because fracture intersections compose a vanishingly small fraction of the network void volume. In this paper, motivated by 3D X-ray imaging of the simplest element of fracture network, that is, two orthogonal fractures, we perform a percolation and finite-size scaling analysis to study the connectivity provided by fracture intersections. The conditions when an intersection enhances connectivity across a sample depend on spatial correlations in the fracture aperture distributions, on the stress state, and on the direction of flow. Here we consider three flow directions: (a) across intersections, (b) parallel to intersections and (c) around corners. For (a), intersections provide minimal enhancement of connectivity because they contribute little additional void area. For (b), intersections increase the probability of a connected path near threshold by enabling 3D connected pathways that are not possible in parallel fractures. Flow around corners, (c), is fundamentally the result of the intersection connecting two fractures in series and spatial correlations are broken around corners, suppressing the connectivity relative to (a). When the connected fractures are stressed equally, a joint percolation threshold emerges that continues to have scale invariance. However, when the fractures are stressed unequally, the system has mixed percolation without clearly defined percolation thresholds. In all cases, percolation probabilities are found to be scale dependent which has important consequences for the connectivity of larger fracture networks composed of the fundamental element studied here.

02 PETROLEUM↗
DOE OSTI2024

Enhancing high-fidelity neural network potentials through low-fidelity sampling

The efficacy of neural network potentials (NNPs) critically depends on the quality of the configurational datasets used for training. Prior research using empirical potentials has shown that well-selected liquid–solid transitional configurations of a metallic system can be translated to other metallic systems. This study demonstrates that such validated configurations can be relabeled using density functional theory (DFT) calculations, thereby enhancing the development of high-fidelity NNPs. Training strategies and sampling approaches are efficiently assessed using empirical potentials and subsequently relabeled via DFT in a highly parallelized fashion for high-fidelity NNP training. Our results reveal that relying solely on energy and force for NNP training is inadequate to prevent overfitting, highlighting the necessity of incorporating stress terms into the loss functions. To optimize training involving force and stress terms, we propose employing transfer learning to fine-tune the weights, ensuring that the potential surface is smooth for these quantities composed of energy derivatives. This approach markedly improves the accuracy of elastic constants derived from simulations in both empirical potential-based NNPs and relabeled DFT-based NNPs. Overall, this study offers significant insights into leveraging empirical potentials to expedite the development of reliable and robust NNPs at the DFT level.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Stimulated resonant inelastic X-ray scattering in a solid

Abstract When materials are exposed to X-ray pulses with sufficiently high intensity, various nonlinear effects can occur. The most fundamental one consists of stimulated electronic decays after resonant absorption of X-rays. Such stimulated decays enhance the number of emitted photons and the emission direction is confined to that of the stimulating incident photons which clone themselves in the process. Here we report the observation of stimulated resonant elastic (REXS) and inelastic (RIXS) X-ray scattering near the cobalt L 3 edge in solid Co/Pd multilayer samples. We observe an enhancement of order 10 6 of the stimulated over the conventional spontaneous RIXS signal into the small acceptance angle of the RIXS spectrometer. We also find that in solids both stimulated REXS and RIXS spectra contain contributions from inelastic electron scattering processes, even for ultrashort 5 fs pulses. Our results reveal the potential and caveats of the development of stimulated RIXS in condensed matter.

36 MATERIALS SCIENCE↗