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Results for “memorial lighting”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Deep learning-assisted modeling for χ (2) nonlinear optics

Modeling second-order (χ(2)) nonlinear optical processes remains computationally expensive due to the need to resolve fast field oscillations and simulate wave propagation using methods such as the split-step Fourier method (SSFM). This can become a bottleneck in real-time applications, such as high-repetition-rate laser systems requiring rapid feedback and control. We present a long short-term memory-based surrogate model trained on SSFM simulations generated from a start-to-end model of the photocathode drive laser at SLAC National Accelerator Laboratory’s Linac Coherent Light Source II. The model achieves over 250× speedup while maintaining high fidelity, enabling future real-time optimization and laying the foundation for data-integrated modeling frameworks and digital twins of laser systems.

Accelerator Physics (physics.acc-ph)↗
DOE OSTI2024

3D Printing ofThermally Responsive Shape Memory LiquidCrystalline Epoxy Networks

Abstract A two-component liquid crystalline epoxy network (LCEN) with shape memory behavior was developed and evaluated as a candidate material for 3D printing. The cure kinetics of the uncured material and the shape memory properties of the cured LCEN were investigated by using parallel plate rheology and dynamic mechanical analysis, respectively. A commercially available fumed silica additive was introduced to the neat, uncured material to improve the rheological properties for 3D printing. The addition of fumed silica was found to increase the yield stress, shear-thinning behavior, and toughness of the uncured epoxy ink. Polarized light microscopy, differential scanning calorimetry, and wide-angle X-ray scattering measurements between the neat and additive-modified LCEN suggested a reduction in liquid crystalline alignment in the modified LCEN, owing to interactions between crystalline domains and fumed silica, which in turn influenced the mechanical behavior. Overall, the additive was found to be successful in preserving the shape memory properties of LCEN while improving its printability.

Chemistry↗
DOE OSTI2025

Content-aware foveated camera for multi-target tracking

Modern image sensors deliver substantial space-time bandwidth, yet indiscriminate acquisition often overwhelms memory, computation, and downstream perception. We present a content-aware, multi-foveated camera that dynamically reallocates sensing and magnification to multiple regions of interest (ROIs). A phase-only spatial light modulator (SLM) serves as a solid-state, inertia-free beam-steering and lens element, enabling per-frame field-of-view (FOV) reconfiguration and content-aware target tracking. By interleaving frames across foveae, our system preserves a wide-FOV situational context while refreshing each ROI at high rates, thereby reducing data volume without degrading task performance. We constructed a prototype employing a single-SLM, single-sensor architecture and demonstrated its application in real-time multi-object tracking with dynamic ROI maintenance across multiple viewpoints. The approach offers a general pathway to integrate detection, tracking, and segmentation algorithms in the acquisition loop, shifting workload from post hoc processing to intelligent capture.

Zang, Zihan [Univ. of California, Los Angeles, CA ↗
DOE OSTI2025

Convergence study of wakefield simulations with GdfidL and ECHO3D

The interaction of charged particle beams with vacuum chamber components gives rise to electromagnetic wakefields, whose frequency-domain representation is known as beam coupling impedance. Geometric impedance arising from discontinuities and transitions in the vacuum chamber is the focus of this study. Minimizing this impedance is essential to mitigate adverse collective effects in modern storage rings operating with high-intensity particle beams. Accurate and reliable impedance simulations is a key factor of the vacuum chamber design. This paper presents the results of a convergence study of two widely used electromagnetic solvers, GdfidL and ECHO3D, applied to key vacuum-chamber components of the National Synchrotron Light Source II (NSLS-II) storage ring. Detailed comparisons are performed for several geometries, including flange absorbers, RF bellows, button-type beam position monitors, and an in-vacuum undulator (IVU). The results show notable differences in convergence and computational efficiency between the two codes. While GdfidL provides highly resolved results and serves as a common benchmark tool, ECHO3D yields consistent results with coarser meshes, significantly reducing simulation time and memory demands. Simulations with a full-geometry IVU model demonstrate that simplified taper-transition models can miss important impedance contributions. In conclusion, these findings provide practical guidelines for efficient and accurate impedance modeling to optimize design of vacuum chamber components for accelerators.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Black hole explosions as probes of new physics

The final stage of black hole evaporation is a potent probe of physics beyond the Standard Model: Hawking-Bekenstein radiation may be affected by quantum gravity “memory burden effects,” or by the presence of “dark,” beyond-the-Standard-Model degrees of freedom in ways that are testable with high-energy gamma-ray observations. We argue that information on either scenario can best be inferred from measurements of the evaporation’s light curve and by correlating observations at complementary energies. We offer several new analytical insights in how such observations map on the fundamental properties of the evaporating black holes and of the possible exotic particles they can evaporate into. Published by the American Physical Society 2025

Federico, Kevin (ORCID:0009000708441977)↗
DOE OSTI2024

Voltage-induced magnetic domain evolution in a phase-change material

Applying voltage to metal–insulator transition (MIT) materials allows electrical actuation of the local electronic phase state. In MIT systems that have the electronic order coupled with the magnetic order, voltage switching of the electronic phase state can also enable the electrical manipulation of magnetic properties. In this work, we utilized x-ray magnetic circular dichroism photoemission electron microscopy (XMCD-PEEM) to investigate the control of magnetic domain configurations in ferromagnetic MIT electrical switches. For applied voltages above a threshold value, the XMCD-PEEM images show that the magnetic domains separate into two distinct regions: one with a high contrast (white/black), indicating well-defined micrometer-scale magnetic domains with a component of their magnetization aligned parallel/antiparallel to the x-ray helicity, and the other with different shades of intermediate contrast (gray). Significant changes in magnetic domain configurations upon voltage biasing were only observed in these gray regions. Furthermore, the voltage-induced magnetic domain separation was found to be bias polarity-dependent, with the gray regions expanding from the opposite sample edge when the applied voltage polarity was reversed. This polarity-dependent electrical control of magnetic domain configurations during the MIT switching opens alternative opportunities in memory applications for magnetic MIT switching materials.

42 ENGINEERING↗
DOE OSTI2026

Gaia: segmented germanium detector for high-energy X-ray fluorescence and spectroscopic imaging

We present Gaia, a monolithic array of 96 high-purity germanium pixel detectors integrated with a custom low-noise application-specific integrated circuit (ASIC) and a field-programmable gate array (FPGA)-based data acquisition system. The sensor operates at ∼100 K using a commercial closed-cycle cryocooler, with the in-vacuum electronics thermally isolated from the cold finger to ensure thermal stability. The system demonstrates an average energy resolution of 711 eV at 122 keV, measured using a 57 Co source, and 253 eV at 5.89 keV, measured with 55 Fe across all channels. The readout architecture incorporates a high-performance FPGA paired with a dual-core ARM processor, forming a complete embedded Linux-based computing platform. Communication between the processor and FPGA is handled via memory-mapped I/O, and data are streamed over high-speed gigabit Ethernet. A full-scale 384-pixel Gaia detector, based on this 96-element module, is currently under fabrication.

36 MATERIALS SCIENCE↗
DOE OSTI2024

In-situ TEM EELS analysis of memristive thin films for neuromorphic computing

Neuromorphic computing stands as a promising frontier for advancing AI algorithms and applications like ChatGBT, offering significant energy efficiency gains. This paper delves into the hardware design intricacies of memristive thin films and their elementary switching mechanisms, including anion migration, electron migration, and phase transitions. Through comprehensive analysis of electron energy loss spectroscopy (EELS) data via in-situ transmission electron microscopy (TEM), we will deduce the primary memristive switching mechanisms vital for optimizing thin film fabrication parameters and achieving desired film thickness, conductivity, and memory retention. A single crystal ptype Si substrate was used with TiN as the bottom metal electrode, TiO x as the insulating dielectric layer, and Pt as the top metal electrode. In-situ TEM was able to tell us the thin film didn’t behave like a filamentary or phase transition material. EELS data deduced that electron trapping/detrapping was one of the primary switching mechanisms. By shedding light on these elementary mechanisms, our study aims to catalyze the development of more 2 efficient and effective neuromorphic computing systems to be deployed into mainstream technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Energy transfer between localized emitters in photonic cavities from first principles

Radiative and nonradiative resonant couplings between defects are ubiquitous phenomena in photonic devices used in classical and quantum information technology applications. In this work, we present a first-principles approach to enable quantitative predictions of the energy transfer between defects in photonic cavities, beyond the dipole-dipole approximation and including the many-body nature of the electronic states. As an example, we discuss the energy transfer from a dipolelike emitter to an 𝐹 center in MgO in a spherical cavity. We show that the cavity can be used to controllably enhance or suppress specific spin-flip and spin-conserving transitions. Specifically, we predict that an ∼10–100 enhancement in the resonant energy transfer rate can be gained in the case of the 𝐹 center in MgO at ∼10 nm distances from a dipolar source, using rather moderate cavity with quality factor 𝑄 ∼ 400. We also show that a similar suppression in the transfer rate can be achieved by off-tuning the cavity resonance relative to the emitter transition energy. The framework presented here is general and readily applicable to a wide range of devices where localized emitters are embedded in microspheres, core-shell nanoparticles, and dielectric Mie resonators. Hence, our approach paves the way to predict how to control energy transfer in quantum memories and in ultrahigh-density optical memories, and in a variety of quantum information platforms.

First-principles calculations↗
DOE OSTI2025

Towards AI Based Data Classification for Decision Making During Testing

During the development of high-consequence items, test systems should be capable of differentiating between test failures resulting from narrowly missing requirements versus those indicating potentially catastrophic faults. In many instances, classifying the data corresponds to simply identifying whether measured waveforms have approximately the anticipated shape. Cast in this light, the problem reduces to converting raw data into a form optimal for use with neural network classifiers. This manuscript investigates different means of representing raw data for image classification. Raw data plots and Short Time Fourier Transform (STFT) spectrograms are classified by both custom built, small-scale, Convolution Neural Networks (CNN) and open-source, multi-million parameter, pre-trained deep CNNs. In the case of time varying frequency content, the STFTs provide images with greater detail and can be accurately classified with simpler networks. This requires less memory and runs faster than classifying the raw data using the more sophisticated options—making STFTs optimal for applications with memory constraints. STFTs are not a panacea. In some cases the time-domain signal contains useful information that should not be discarded. Rather than using raw data or STFTs, the images can be constructed from both by using red and green channels of an RGB image to visualize the real and imaginary components of the transform, with the raw data occupying the blue channel.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Exploring transport-enabled gates with integrated optical addressing to demonstrate high fidelity control of trapped ion qubits in a scalable quantum computer

In recent years, experiments involving micofabricated surface ion traps have grown in complexity, and as this complexity grows, a common design has emerged in the form of quantum charge-coupled device architecture. This architecture, already utilized on multiple systems, supports multiple zones on a device for areas such as memory or computation. The shutting process between these zones is a process often seen to be minimized. An additional component to scalable surface trapped-ion experiments includes some form of integrated photonics, as free space lasers have difficulty scaling to many ions. Here, we discuss recent results in utilizing the shuttling process with integrated photonics to perform a specific type of gate, as well as demonstrating state preparation. Furthermore, we show that these gates can be utilized as a type of optical modulator as the Doppler shift that occurs during shuttling will make the light seen by shuttled ions different than that seen by stationary ions. Furthermore, we show that the shuttling operation can be utilized as an optical modulator, where the Doppler shift changes the frequency from that of a stationary ion.

42 ENGINEERING↗
DOE OSTI2025

Anomalous elastic softening in ferroelectric hafnia under pressure

his study employs first-principles density-functional theory (DFT) calculations to explore the elastic and mechanical properties of ferroelectric hafnia (HfO 2 ) in its polar orthorhombic 𝑃⁢𝑐⁢𝑎⁢2 1 phase under varying hydrostatic pressure conditions up to 30 GPa. Utilizing a plane-wave basis set and Perdew-Burke-Ernzerhof generalized-gradient approximation for solids in our DFT calculations, we investigate both pure and yttrium-substituted HfO 2 . Our findings reveal an anomalous reduction in the 𝐶 33 component of the elastic tensor with increasing pressure, which becomes significant above 15 GPa and signals a potential pressure-driven structural phase transition at higher pressure. The analysis of atomic displacements under pressure sheds light on the unusual mechanical behavior and phase stability of this material. Additionally, we observe a transition from an indirect band gap to a direct band gap with increasing pressure, which could have significant implications for optical applications. Here, the effects of yttrium substitution on the mechanical and electronic properties are further examined, revealing that yttrium substitution softens the elastic response of this material and reduces the electronic band gap. These results enhance our understanding of elastic and mechanical responses of ferroelectric hafnia and its potential for applications in microelectronics, piezoelectric devices, and nonvolatile ferroelectric random-access memories. Further experimental validation is recommended to confirm our predictions and explore the practical implications of the observed phase transitions and electronic behavior of the ferroelectric hafnia under high-pressure conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Homomorphic data compression for real time photon correlation analysis

The construction of highly coherent X-ray sources, combined with next-generation detectors that are larger and faster, has enabled new research opportunities across the scientific landscape. Among the techniques that benefit most from these advancements is X-ray photon correlation spectroscopy (XPCS), where faster acquisition unlocks the ability to study faster dynamics within samples. However, faster acquisition on larger detectors also introduces unprecedented challenges for online data processing and offline data storage. Such challenges are particularly prominent for XPCS, where real time analyses require simultaneous calculation of all the previously acquired data in the time series. We present a homomorphic compression scheme to effectively reduce the computational time and memory space required for XPCS analysis. Leveraging similarities in the mathematical expression between a matrix-based compression algorithm and the correlation calculation, our approach allows direct operation on the compressed data without their decompression. The offline compression scheme extends storage capacity by a factor of 40 while preserving key features in the lossy compressed data. Meanwhile, the online compression scheme reduces the computational time to below 1 ms, enabling real time calculation of the correlation functions at kHz framerate. Our demonstration of a homomorphic compression of scientific data provides an effective solution to the big data challenge at coherent light sources. Beyond the example shown in this work, the framework can be extended to facilitate real-time operations directly on a compressed data stream for other techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2025

NLR HPC Eagle Jobs Data and Additional Energy Metrics

Overview: Anonymized job-level records from the Eagle high-performance computing (HPC) system at the National Laboratory of the Rockies (NLR). Each record represents a Slurm batch job with scheduling metadata, resource requests, resource utilization, CPU/GPU energy consumption, and efficiency metrics. Sensitive fields (user, account, job name) are replaced with cryptographic hashes. System & Timeframe: Eagle was a 2,000-node, 8-petaflop system operated at NLR from 2019–2024. Data covers the full operational lifetime of the system. Slurm data was processed nightly; timestamps are in Mountain Time. Funding provided by the U.S. Department of Energy, EERE. Files: esif.hpc.eagle.job-anon.zip — Core anonymized job records (Hive-partitioned Parquet) esif.hpc.eagle.job-anon-energy-metrics.zip — Same records with additional iLO and Ganglia energy metrics datacard.md — Full dataset documentation ~13.8 million rows, 62 variables. Readable with PyArrow, pandas, DuckDB, Apache Spark, or any Parquet-compatible tool. Data Collection: Jobs collected via sacct through a pipeline: Eagle Jobs API → Redpanda → StreamSets → HPCMON API → PostgreSQL. Node-level power from iLO (HP Integrated Lights-Out); GPU power from Ganglia monitoring, joined to jobs via node lists and time ranges. Preprocessing: Anonymization of name, user, and account fields via cryptographic hashing Derived columns: queue_wait, cpu_eff, max_mem_eff Simplified job state mapping (e.g., "CANCELLED BY 12345" → "CANCELLED") QoS accounting rules (buy-in, standby, or Slurm QoS value) CPU energy estimated from TDP (200W, Intel Xeon Gold 6154, 18 cores) Timezone-aware columns (_tz) sourced from LEX accounting database to correctly handle DST transitions Key Variables: Scheduling: job_id, partition, state_simple, submit_time_tz, start_time_tz, end_time_tz, queue_waitResources: nodes_req/used, processors_req/used, memory_req, wallclock_req/used, gpus_requested Efficiency: cpu_eff, max_mem_eff Energy: cpu_energy_tdp_estimated_max/used_watt_hours, node_energy_total_watt_hours (iLO), gpu0/1_energy_total_watt_hours (Ganglia) Partitions: bigmem, bigmem-8600, bigscratch, csc, dav, ddn, debug, gpu, haswell, long, mono, short, standard Job States: CANCELLED, COMPLETED, FAILED, NODE_FAIL, OUT_OF_MEMORY, PENDING, RUNNING, TIMEOUT QoS Levels: Unknown, normal, buy-in, debug, penalty, high, standby Important Notes: Non-_tz timestamp columns may be off by one hour across DST boundaries; use _tz columns for time difference calculations Energy fields are null for jobs without monitoring coverage Job step records and raw Slurm JSONB fields are excluded from this extract Do not attempt to re-identify individuals from hashed fields

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Compact fiber-coupled narrowband two-mode squeezed light source

Quantum correlated states of light, such as squeezed states, are a fundamental resource for the development of quantum technologies, as they are needed for applications in quantum metrology, quantum computation, and quantum communications. It is thus critical to develop compact, efficient, and robust sources to generate such states. Here, we report on a compact, narrowband, fiber-coupled source of two-mode squeezed states of light at 795 nm based on four-wave mixing (FWM) in an 85 Rb atomic vapor. The source is designed in a small modular form factor, with two input fiber-coupled beams, the seed and pump beams required for the FWM, and two output fibers, one for each of the modes of the squeezed state. The system is optimized for low pump power (135 mW) to achieve a maximum intensity-difference squeezing of 4.4 dB after the output of fibers at an analysis frequency of 1 MHz. Furthermore, the narrowband nature of the source makes it ideal for atomic-based quantum sensing and quantum networking configurations that rely on atomic quantum memories. Such a source paves the way for a versatile and portable platform for applications in quantum information science.

Jain, Umang [University of Oklahoma, Norman, OK (U↗
DOE OSTI2025

Intrinsic optical bistability of photon avalanching nanocrystals

Optically bistable materials respond to a single input with two possible optical outputs, contingent on excitation history. Such materials would be ideal for optical switching and memory, but the limited understanding of intrinsic optical bistability (IOB) prevents the development of nanoscale IOB materials suitable for devices. Here we demonstrate IOB in Nd 3+ -doped KPb 2 Cl 5 avalanching nanoparticles, which switch with high contrast between luminescent and non-luminescent states, with hysteresis characteristic of bistability. Here we elucidate a non-thermal mechanism in which IOB originates from suppressed non-radiative relaxation in Nd 3+ ions and from the positive feedback of photon avalanching, resulting in extreme, >200th-order optical nonlinearities. The modulation of laser pulsing tunes the hysteresis widths, and dual-laser excitation enables transistor-like optical switching. This control over nanoscale IOB establishes avalanching nanoparticles for photonic devices in which light is used to manipulate light.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Phase transition in two-dimensional monolayer (1L)-molybdenum disulfide induced by atomic S-basal plane gliding via synchrotron X-ray monochromatic beam radiation for superior electronic performance

Here, in this work, we report a novel approach to reduce the channel resistance by inducing a phase transition behavior from 2H to 1T in a monolayer MoS 2 (1L-MoS 2 ) by a synchrotron X-ray monochromatic beam (mono-beam) radiation. The effects of the biphase structure by the mono-beam on the 1L-MoS2 film were investigated using Raman spectra, photoluminescence (PL) spectra, scanning tunneling microscopy, and scanning tunneling spectroscopy, respectively. Through material characterization, we identified that the lateral sliding of S-vacancies along the S-plane in the 1L-MoS 2 is the key reason for the origin of unidirectional phase transition. The precise phase engineering triggered by the mono-beam radiation process allows the realization of field-effect transistors (FET) with 2X improvement in mobility toward a high on/off ratio (~10 8 ) and a near-ideal subthreshold swing of ~88 mV per decade. The validity of the phase engineering could be further extended for its application as a memory device, exhibiting a gate tunable conduction modulation behavior and a high resistance ratio of ~10 2 at a gate bias of 5 V with endurance of ~100 cycles. Furthermore, an artificial neural network using the synaptic weight update with accuracy of ~93 % was achieved.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Coherent Control over Nuclear Hyperpolarization Using an Optically Initializable Chromophore-Radical System

Chromophore radicals (CR) are emerging as important components for molecular quantum information science (QIS), especially in the context of quantum sensing. Here, we demonstrate that the optically hyperpolarized electrons in a 1,6,7,12-tetrakis(4-tert-butylphenoxy)-perylene-3,4,9,10-bis(dicarboximide) (tpPDI) covalently linked to a partially deuterated 1,3-bis(diphenylene)-d 16 -2-phenylallyl radical (BDPA-d 16 ) can be coherently manipulated via pulsed dynamic nuclear polarization (DNP) methods to transfer polarization to nuclear spins and back. Under light illumination at 85 K, electron hyperpolarization in BDPA is enhanced 2.1- to 2.4-fold over thermal polarization and lasts for more than 100 ms. By applying nuclear orientation via electron spin-locking (NOVEL) DNP, this optically amplified electron hyperpolarization was successfully transferred to a 1 H nuclear spin within the CR system and efficiently returned to the electron spin for readout via reverse-NOVEL. The NOVEL transfer efficiency of 65% amounts to a 688-fold nuclear spin hyperpolarization of the target nuclear spin, considering the 2.1-fold electron spin hyperpolarization. This reversible coherent manipulation of hyperpolarization transfer highlights the utility of CR systems to initialize and read out nuclear spin states in a disordered matrix at moderate cryogenic temperatures. Coupled with CRs’ environmental compatibility, tunability, and precise state initialization, these results highlight the promising role of nuclear spins in CRs for QIS applications, including quantum sensing and memory.

charge transfer↗