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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

2012-2013 Delaware Valley Household Travel Survey

The 2012-2013 Delaware Valley Household Travel Survey collected data for multiple planning purposes such as the calibration of a new activity-based travel demand model. It features data from households across nine counties in the region, including southern New Jersey and southeastern Pennsylvania. The Delaware Valley Regional Planning Commission (DVRPC) sponsored the survey, which was administered by Abt Srbi Inc. A sampling strategy was designed to recruit households for survey participation that would best represent overall regional travel trends. Households were selected randomly, but with special consideration given to under-represented geographies and transit propensity. On their assigned travel day, households were asked to record all trips made within a 24-hour period. Additionally, select households were chosen to participate in a wearable global positioning system (GPS) technology-based component of the study. A total of 811 participants wore the GPS system.

1Hz data↗
DOE OSTI2025

3D-printed micro ion trap technology for quantum information applications

Trapped-ion applications, such as in quantum information processing1, precision measurements, optical clocks and mass spectrometry, rely on specialized high-performance ion traps. The last three of these applications typically use traditional machining to customize macroscopic 3D Paul traps, whereas quantum information processing experiments usually rely on photolithographic techniques to miniaturize the traps and meet scalability requirements. Using photolithography, however, it is challenging to fabricate the complex 3D electrode structures required for optimal confinement. Here, in this work, we demonstrate a high-resolution 3D printing technology based on two-photon polymerization (2PP) that is capable of fabricating large arrays of high-performance miniaturized 3D traps. We show that 3D-printed ion traps combine the advantages, such as strong radial confinement, of traditionally machined 3D traps with on-chip miniaturization. We trap calcium ions in 3D-printed ion traps with radial trap frequencies ranging from 2 MHz to 24 MHz. The tight confinement eases ion cooling requirements and allows us to implement high-quality Rabi oscillations with Doppler cooling only. Also, we demonstrate a two-qubit gate with a Bell-state fidelity of 0.978 ± 0.012. With 3D printing technology, the design freedom is greatly expanded without sacrificing scalability and precision, so that ion trap geometries can be optimized for higher performance and better functionality.

quantum information↗
DOE OSTI2025

Microbial Community Analysis & Functional Evaluation in Soils

The overall objective of this proposal was to develop technologies to alter the composition and function of important members of microbial communities. In particular, the overall objective of the microbial community editing portion of the proposal focuses on developing foundational tools and understanding required to predict, alter and design grass rhizosphere communities impacting DOE missions. Specifically, the project is centered on the Microbial Community Analysis & Functional Evaluation in Soils (m-CAFES) to manipulate microbial consortia associated with plants of interest for the bioenergy sector, under the presumption that bacterial communities can be manipulated to enhance plant health. For tasks of specific interest to us, we are focusing on developing novel Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) based technologies (primarily focusing on Aim 1) and their delivery modalities (notably subaim 1.2) to edit specific bacterial genomes of interest to enhance their functionalities, and programmably ablate specific undesirable members of bacterial communities for plant health. We are focusing on engineering bacteriophages (bacterial viruses, for subaim 1.2) to carry programmable CRISPR-Cas systems (subaim 1.1) to target (ablate) or alter (edit) genomes of interest. This will enable us to carry out microbial perturbations that will impact community composition and function and ultimately plant growth and health, to enable the next phase of the project by deploying them in situ (subaims 1.3 and 1.4).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Collaborative: in situ visual analytics technologies for extreme scale combustion simulations

This project aims to drastically enhance the usability of in situ analysis and visualization for extreme-scale scientific simulations. Current exascale computing capabilities promise to offer greater predictive ability of simulations and to further push the frontiers of science and technology. However, to validate the simulation output at extreme scale, examine the modeled phenomena, and discover previously unknowns from the output data, the output must be reduced or transformed in situ as it is being generated during the simulation such that the amount of data to examine and store is kept to a minimum. Such in situ approaches allow us to process and analyze the data and any embedded geometry to an extent that would be prohibitively expensive, if not impossible, to perform as a post hoc task. While in situ processing has been demonstrated to be a feasible and promising approach, its full potential has not yet been leveraged. In this project, we have developed comprehensive enhancements to in situ technology based on probability distributions in data. Our research focuses on jointly developing new ways of interacting with massive statistical samples while creatively utilizing new state-of-the-art computational resources to push the boundaries of in situ exploration. Moreover, we have developed new time-dependent techniques to enable previously unattainable capabilities in areas such as intelligent simulation steering and precise feature identification. We have experimentally studied our design and implementation at NERSC and OLCF, and are able to leverage existing in situ infrastructures whenever possible. While the exemplar in this project is combustion, many other fields for which turbulent transport is important, e.g., fusion, climate, astrophysics among others, encounter similar issues as simulations scale up to the exascale. This project shows its potential to generate high impact on DOE missions since the resulting technology promises to improve scientists’ ability to rapidly and correctly interpret and tune extreme-scale simulations, leading to new scientific understanding and advancements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

DUNE Photon Detection System

The Deep Underground Neutrino Experiment (DUNE) aims to provide a broad physics program primarily addressed to probing CP violation in the neutrino sector and identifying the neutrino mass hierarchy. The search for proton decay, the observation of supernova neutrino bursts, and the investigation of solar neutrinos represent other additional goals of DUNE experiment, which can be enhanced by the use and the high performances of the Photon Detection System (PDS). Using the technology based on liquid argon Time Projection Chamber (LArTPC), the experiment plans to observe neutrino interactions inside detectors located 1300 km away from the Long Baseline Neutrino Facility (LBNF) at Fermi National Accelerator Laboratory (FNAL), where the neutrinos are produced. The experiment consists of two main parts, respectively the far and near detectors. The far site will comprise four detector modules. The first module is constituted by a vertical drift single-phase LArTPC, while the second module provides a horizontal drift single-phase LArTPC. The configurations of the other modules are still under definition. Neutrino detection in LArTPCs is achieved by identifying the charge and light generated from its interactions with liquid argon. The wire planes of the instrumented anode and the PDS detect these signals, respectively. The PDS in the first two modules, detailed in the present document, uses a modified version of the so-called ARAPUCA technology, named X-ARAPUCA. This system consisting of a highly reflecting box with an entrance window made by dichroic filters and wavelength shifters, creates a trap to detect the VUV (128 nm) scintillation photons. The X-ARAPUCA of the first module is called Supercell, and it has dimensions of 488×100 mm 2 , while Megacell is the second module version, with an active area of 60×60 cm 2 . This latter configuration also represents a significant technological advancement. Since half of the modules are placed on the cathode at high voltage, they are powered and read out using innovative power-over-fiber (PoF) and signal-over-fiber (SoF) technologies. Meanwhile, the other half are installed in a membrane behind the field cage, with a total transparency of around 70%.

Neutrino detectors↗
DOE OSTI2025

Long-Range Resonant Charge Transport through Open-Shell Donor–Acceptor Macromolecules

A grand challenge in molecular electronics is the development of molecular materials that can facilitate efficient longrange charge transport. Research spanning more than two decades has been fueled by the prospects of creating a new generation of miniaturized electronic technologies based on molecules whose synthetic tunability offers tailored electronic properties and functions unattainable with conventional electronic materials. However, current design paradigms produce molecules that exhibit off-resonant transport under low bias, which limits the conductance of molecular materials to unsatisfactorily low levels several orders of magnitude below the conductance quantum 1 G 0 and often results in an exponential decay in conductance with length. Here, we demonstrate a chemically robust, air-stable, and highly tunable molecular wire platform comprised of open-shell donor−acceptor macromolecules that exhibit remarkably high conductance close to 1 G 0 over a length surpassing 20 nm under low bias, with no discernible decay with length. Single-molecule transport measurements and ab initio calculations show that the ultralong-range resonant transport arises from extended π-conjugation, a narrow bandgap, and diradical character, which synergistically enables excellent alignment of frontier molecular orbitals with the electrode Fermi energy. The implementation of this long-sought-after transport regime within molecular materials offers new opportunities for the integration of manifold properties within emerging nanoelectronic technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Precision Labeling of Native Antibodies with Lock Coupling

The formation of stable protein complexes enables much of biotechnology, but even high-affinity complexes can dissociate, limiting potential applications in biomaterials, bioimaging, nanomedicine, and other protein-based technologies. Here, in this study, we describe lock coupling, a simple and selective one-step reaction between interfacial lysine and glutamate or aspartate side chains to form stable isopeptide bonds and be used for the precise labeling of native antibodies. We identify conditions in which short-lived activated esters formed by the aqueous carbodiimide EDC promote isopeptide bond formation specifically at preassociated amine-acid pairs. Indiscriminate cross-linking is minimized by formation of protein complexes before addition of catalyst, use of acidic pH to suppress exposed Lys reactivity, and limiting the aqueous stability of activated esters. For native antibody (Ab) labeling, we show that the small IgG-binding protein GB1 can be covalently attached to the Ab Fc domain and that introduction of Cys into GB1 loops allows for facile conjugation of fluorophores, micelles, or inorganic nanocrystals for imaging in live cells and animals. By varying Cys substituents and protein stoichiometry, a defined number of probes can be uniformly attached without the need for extensive purification. In live-cell confocal microscopy, labeled GB1 serves as a stable replacement for secondary Abs, enabling simple multicolor immunostaining and imaging. Lock coupling requires just a single reagent in aqueous buffer and leverages both the innate ability of proteins to form high-affinity complexes and the widespread presence of Lys-Glu/Asp pairs at their interfaces, with the potential for precision synthesis of protein-based probes for imaging, biomaterials, biophysics, and medicine.

antibody↗
DOE OSTI2025

Distinguishing isotropic and anisotropic signals for X-ray total scattering using machine learning

Understanding structure–property relationships is essential for advancing technologies based on thin films. X-ray pair distribution function (PDF) analysis can access relevant atomic structure details spanning local-, mid- and long-range structure. While X-ray PDF has been adapted for thin films on amorphous substrates, measurements on single-crystal substrates are necessary to accurately determine structure origins for some thin film materials, especially those for which the substrate changes the accessible structure and properties. However, when measuring films on single-crystal substrates, high-intensity anisotropic Bragg spots saturate 2D detector images, overshadowing the thin films' isotropic scattering signal. This renders previous data processing methods for films on amorphous substrates unsuitable for films on single-crystal substrates. To address this measurement need, we developed IsoDAT2D, an innovative data processing approach using unsupervised machine learning algorithms. The program combines dimensionality reduction and clustering algorithms to separate thin film and single-crystal substrate X-ray scattering signals. We use SimDAT2D , a program we developed to generate simulated thin film data, to validate IsoDAT2D . Here we also use IsoDAT2D to isolate X-ray total scattering signal from a thin film on a single-crystal substrate. The resulting PDF data are compared with similar data processed using previous methods, especially substrate subtraction for single-crystal and amorphous substrates. PDF data from IsoDAT2D -identified X-ray total scattering data are significantly better than from single-crystal substrate subtraction, but not as reliable as PDF data from amorphous substrate subtraction. With IsoDAT2D , there are new opportunities to expand PDF to a wider variety of thin films, including those on single-crystal substrates, with which new structure–property relationships can be elucidated to enable fundamental understanding and technological advances.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Coatings for CSP Lifetime

The feasibility and performance of tower-technology-based concentrated solar power (CSP) is highly dependent on the efficiency of the energy transformation from sun to heat at the receiver. The higher the solar absorptivity of the receiver coating, the higher the efficiency of the plant as a whole. BrightSource Energy (BSE) has developed a series of High-Performance Coating (HPC) systems in order to achieve high absorptivity over the plant lifetime (25-35 years). This requires stable coatings that are easily applicable on the large receiver surface and will maintain their optical properties under intense solar flux and thousands of heating and cooling cycles in desert conditions. Different coating formulations are required according to the differing plant conditions: receiver materials, operating conditions (temperatures, daily cycles, etc.), and environmental conditions. BSE also developed a coating for the next generation of CSP receivers, such as those being under DOE’s CSP Gen3 program, which will be operated with high temperature heat transfer fluids at temperatures of up to 800°C, which is significantly hotter than the operating temperature of current systems. Once the coating is formulated, the next challenge is evaluating its lifetime properties. BSE has found several independent failure modes that impact HPC absorptivity degradation: • Decrease in HPC optical properties due to oxidation in the receiver tubes surface below the HPC; • HPC film deterioration due to cycling of temperatures and humidity due to daily operation startup and shutdown as well as changing ambient conditions; • Mechanical degradation due to erosion by sand and wind. Existing test methods examine various aspects independently, but do not provide a combined accelerated lifetime result. Creating such a combined test suite, with a way to interpret the results to predict the coating’s projected lifetime, was the ultimate goal of this project. The project was divided into three major workstreams: lab testing (individual failure mode tests and combined failure mode tests); developing a theoretical model for aging; and validation of the test apparatus via on-sun testing in near real-world conditions at CIEMAT-PSA. Developing a test apparatus that accurately controlled the temperature while also introducing the desired solar flux proved more challenging than expected. While in the end we did succeed in creating a test apparatus that can control temperature, solar flux, and humidity, the results did not appear to accelerate the lifetime of the samples as desired. We suspect that to properly accelerate the samples we must also subject the samples to increased amounts of oxygen. Similarly, while we successfully created a combined model that is publicly available, we were unable to validate it sufficiently to feel comfortable recommending it as a general guideline.

14 SOLAR ENERGY↗
DOE OSTI2025

Thermally Activated Circularly Polarized Photoluminescence in a 2D Hybrid Perovskite with Giant Spin Splitting

Circularly polarized light generation and detection are critical for future spin-based technologies that inter-convert circularly polarized photons and electron spins. However, detailed mechanisms in such spin-photon interfaces are often either poorly understood or operate at cryogenic temperatures since typically small energies separating spin-split electronic bands facilitate thermally driven spin depolarization. Recently, several 2D hybrid perovskites with polar achiral cations were theoretically demonstrated to exhibit conduction and valence band spin-splitting energies greatly exceeding room-temperature thermal energy, suggesting their utility as spin-photon interfaces with practical operating temperatures. Here, a strong "spin memory" effect is reported in such a polar achiral layered perovskite that enables large room-temperature circularly polarized emission anisotropy following excitation with circularly polarized light. The polarization anisotropy depends strongly on temperature (thermally activated), excitation energy, and crystal orientation with respect to the excitation source. Temperature-dependent photoconductance measurements reveal similar thermally activated carrier generation. These observations suggest a mechanism whereby giant in-plane splitting of single-particle levels protects spin-polarization of photogenerated electrons and holes before recombination. Although polarized light emission is explored in greater detail in chiral perovskites, these results reveal that even without chirality, large spin memory in polar achiral perovskites can enable spin-photon interfaces that operate at elevated temperatures.

14 SOLAR ENERGY↗
DOE OSTI2025

Automated Programmable Logic Controller Memory Forensics Using RGB Image Analysis and Deep Learning

The introduction of Industry 4.0 and Internet-based technologies has enhanced industrial control system operations but have inadvertently increased their vulnerabilities to cyber attacks. When an industrial control system is compromised, security analysts need to identify the root cause quickly to start the recovery process and develop mitigation strategies. Memory forensics is critical in the incident analysis process to ascertain what occurred. Approaches for analyzing the persistent memory in industrial control devices are limited and almost nonexistent for volatile memory. This chapter proposes an automated methodology for programmable logic controller memory dump analysis using computer vision and deep learning techniques. The methodology converts the sequences of bytes in a programmable logic controller memory dump to red-green-blue pixels and employs a deep learning model that learns the underlying patterns and features of pre-labeled forensic artifacts in images and segments them into distinct regions. The trained model is employed to automatically segment new memory images and identify forensic artifacts. Evaluation of the methodology on a Schneider Electric Modicon M221 programmable logic controller under code injection and code modification attacks demonstrates its ability to detect attack artifacts in memory dumps.

Asmar Awad, Rima [ORNL] (ORCID:0000000233407742)↗
DOE OSTI2024

Performance and economic viability assessment of a novel CO 2 adsorbent for manufacturing and integration with coal power plants

Here, this study assesses the performance and economic feasibility of a novel CO 2 adsorbent for post-combustion capture in DOE/NETL’s 650 MWnet SubC PC power plant (case B11B). Bench-scale tests showed an initial adsorption capacity of 16.3 wt%, which decreased to 12.1 wt% after 41 adsorption–desorption cycles due to induced particle aggregation by over-humidification. With a conservative adsorption capacity of 8.8 wt% and 695 adsorption–desorption cycles, an adsorbent replenishment rate of 10 tonnes/h is necessary to capture 90% of CO 2 . The breakeven sale price of the adsorbent produced at this rate is $\$$1,293/tonne, which is 40 to 80 times lower than prices for K 2 CO 3 adsorbents reported in the literature (e.g., K 2 CO 3 /TiO 2 , K 2 CO 3 /ZrO 2 ) while providing better capture performances. Sensitivity analysis reveals that increasing the plant production rate from 10 to 40 tonnes/h reduces the sale price by 8%. The study also compares the CO 2 capture cost to Cansolv, an integrated solvent-based technology. The novel adsorbent requires 2.4 GJ/tonne of CO 2 for regeneration, lower than Cansolv’s 2.7 GJ/tonne. With conservative performance estimates, the capture cost is $\$$54/tonne of CO 2 , slightly higher than Cansolv’s $\$$45/tonne. To achieve lower or comparable capture costs to Cansolv, the adsorbent should meet one of the following conditions at a commercial scale: minimum 950 cycles, 16 wt% capture capacity, 50% of the adsorbent recovery, or a reduced cost to $\$$646/tonne by upscaling the manufactury to 75 tonnes/h.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Comparative assessment of new oxygen carrier materials for gas switching reforming of natural gas: Techno-economics assessment, life cycle analysis, and experimental insights

The increasing demand for hydrogen and the CO 2 intensity of natural gas (NG) reforming motivate the development of low-carbon-emission hydrogen production technologies. Gas Switching Reforming (GSR) with integrated CO 2 capture, a technology based on Chemical Looping Reforming (CLR), has been experimentally proven and shows potential for scale-up. In this study, select oxygen carriers (OC) (NiO/Al 2 O 3 , Fe 2 O 3 -CeO 2 /Al 2 O 3 , and magnetite) were tested in methane steam reforming in a fixed bed reactor to determine their relative reactivities under relevant conditions for GSR (800 °C, 7 bar total pressure). Process models were then developed to perform techno-economic analysis (TEA) of GSR for hydrogen production (GSR-H 2 ) and a combined cycle (GSR-CC) in which high-purity H 2 is fired in a gas turbine to produce electricity. Operating at 10 bar and 1100 °C and with the additional recovery steps implemented increased H 2 production by ∼ 30% and improved efficiency relative to prior studies. For GSR-H 2 , the levelized cost of hydrogen (LCOH) is 1.61–1.64 $/kg-H 2 , competitive with a reference SMR case, though operating and maintenance costs are higher due to increased electricity demand. GSR-CC has a significantly higher levelized cost of electricity (LCOE) than its reference NGCC (natural gas combined cycle) plant, suggesting it is less competitive; however, increasing production scale could make it more attractive. Life-cycle results for GSR-H 2 indicate NG consumption drives ∼ 75% of total global warming impacts (∼2.3 kg CO 2 eq/kg H 2 ). An environmental, health, and safety screening suggests iron-based carriers are comparatively safer, whereas NiO may pose greater risks. Overall, GSR-H 2 is a scalable, competitive option for hydrogen production using nickel and non-nickel OC.

03 NATURAL GAS↗
DOE OSTI2025

On the viability of stimulated hydrogen generation from iron-rich formations

Hydrogen-based technologies present a promising solution for the global energy transition. In addition to electrolytic production, subsurface geological formations provide a potential natural source of hydrogen. Iron-rich ultramafic rocks, in particular, are favorable for hydrogen generation through natural processes such as serpentinization. Naturally occurring reactions and migration can be enhanced through various types of stimulation, including thermal, hydraulic, and chemical treatment. Through numerical simulations, we analyzed the complex interplay of factors influencing the production and migration within the subsurface, emphasizing the importance of different stimulation techniques, catalysts, and conditions. Our findings indicate that key parameters, such as damage zone permeability and width, significantly impact producible hydrogen mass. Our results indicate that a combination of large damage zone widths, high permeability, and a stimulated reaction rate of 1 × 10 -9 can yield economically viable production rates of up to 1 kg s -1 at the wellhead. Moreover, the availability of ferrous iron, rather than the serpentinization rate itself, has been identified as the primary limiting factor in achieving economically sustainable hydrogen production. In conclusion, while an unstimulated rock volume of 0.165 km 3 yields only 45t of hydrogen in two years, various stimulation techniques can increase production to 18500t.

08 - HYDROGEN↗
DOE OSTI2025

Accurate and efficient predictions of keyhole dynamics in laser materials processing using machine learning-aided simulations

The keyhole phenomenon has been widely observed in laser materials processing, including laser welding, remelting, cladding, drilling, and additive manufacturing. Keyhole-induced defects, primarily pores, dramatically affect the performance of final products, impeding the broad use of these laser-based technologies. The formation of these pores is typically associated with the dynamic behavior of the keyhole. So far, the accurate characterization and prediction of keyhole features, particularly keyhole depth, as a function of time, has been a challenging task. In situ characterization of keyhole dynamic behavior using the synchrotron X-ray technique is informative but complicated and expensive. Current simulations are generally hindered by their poor accuracy and generalization abilities in predicting keyhole depths due to the lack of accurate laser absorptance data. In this study, we develop a machine learning-aided simulation method that accurately predicts keyhole dynamics, especially in keyhole depth fluctuations, over a wide range of processing parameters. In two case studies involving titanium and aluminum alloys, we achieve keyhole depth prediction with a mean absolute percentage error of 10 %, surpassing those simulated using the ray-tracing method with an error margin of 30 %, while also reducing computational time. This exceptional fidelity and efficiency empower our model to serve as a cost-effective alternative to synchrotron experiments. Our machine learning-aided simulation method is affordable and readily deployable for a large variety of materials, opening new doors to eliminate or reduce defects for a wide range of laser materials processing techniques.

Computational fluid dynamics↗
DOE OSTI2025

Theory of the photomolecular effect

It is well-known that water in liquid and vapor phases exhibits weak visible-light absorption. Recent experiments, however, show that at the liquid-air interface, absorption drastically increases, accelerating evaporation beyond thermal limits by 2–5 times. Strikingly, evaporation peaks at green wavelengths, despite no corresponding absorptance peak. The underlying mechanism of this observation, termed the photomolecular effect, remains puzzling, particularly as water molecules do not exhibit resonance peaks in the visible spectrum. Here, we present a theoretical model explaining the effect. We show that surface-bound water clusters undergo non-resonant photon-driven evaporation, with green light being particularly effective. Crucially, we do not expect green light to couple more strongly than other wavelengths to the molecules at the surface, rather the energy of green light is more effectively used to vaporize water. Our model accounts for why the evaporation peak does not align with absorptance and provides a quantum mechanical explanation of how a single photon can vaporize an entire molecular cluster. This model challenges conventional views on water-light interactions, revealing a fundamentally non-thermal evaporation mechanism. Furthermore, our findings have implications for water purification, energy-efficient drying, and climate modeling, opening new pathways for optimizing evaporation-based technologies.

Interfacial evaporation↗
DOE OSTI2025

Spontaneously formed phonon frequency combs in van der Waals solid CrGeTe 3 and CrSiTe 3

Optical phonon engineering through nonlinear effects has been utilized in ultrafast control of material properties. However, nonlinear optical phonons typically exhibit rapid decay due to strong mode-mode couplings, limiting their effectiveness in temperature or frequency sensitive applications. Here we report the observation of long-lived nonlinear optical phonons through the spontaneous formation of phonon frequency combs in the van der Waals material CrXTe 3 (X=Ge, Si) using high-resolution Raman scattering. Unlike conventional optical phonons, the highest A g mode in CrGeTe 3 splits into equidistant, sharp peaks forming a frequency comb that persists for hundreds of oscillations and survives up to 200K. These modes correspond to localized oscillations of Ge 2 Te 6 clusters, isolated from Cr hexagons, behaving as independent quantum oscillators. Introducing a cubic nonlinear term to the harmonic oscillator model, we simulate the phonon time evolution and successfully replicate the observed comb structure. Similar frequency comb behavior is observed in CrSiTe 3 , demonstrating the generalizability of this phenomenon. Our findings demonstrate that Raman scattering effectively probes high-frequency nonlinear phonon modes, offering insight into the generation of long-lived, tunable phonon frequency combs with potential applications in ultrafast material control and phonon-based technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The role of excitation vector fields and all-polarisation state control in cavity magnonics

Recently the field of cavity magnonics, a field focused on controlling the interaction between magnons and photons confined within microwave resonators, has drawn significant attention as it offers a platform for enabling advancements in quantum- and spin-based technologies. Here, we introduce excitation vector fields, whose polarisation and profile can be easily tuned in a two-port cavity setup, thus acting as an effective experimental dial to explore the coupled dynamics of cavity magnon-polaritons. Moreover, we develop theoretical models that accurately predict and reproduce the experimental results for any polarisation state and field profile within the cavity resonator. This versatile experimental platform offers a new avenue for controlling spin-photon interactions by manipulating the polarisation of excitation fields. By introducing real-time tunable parameters that control the polarisation state, our experiment delivers a mechanism to readily control the exchange of information between hybrid systems.

condensed-matter physics↗