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1,210 records · Page 41

Adapting High-Resolution X-Ray Microcalorimeter Spectrometers to Transform MFE Plasma Diagnostics

The aim of this project was to begin the transformation of magnetic fusion energy (MFE) X-ray diagnostics by applying detector technology developed over the past several decades by the astrophysics community. We installed and operated an X-ray microcalorimeter detector system under fusion-relevant plasma conditions at the Madison Symmetric Torus (MST). X-ray microcalorimeter spectrometers combine the best characteristics of instrumentation currently available on fusion devices: the high spectral resolution of crystal spectrometers (2 eV) and broadband coverage provided by pulse-height analysis systems. These spectrometers have small port-access requirements, a key advantage for future MFE experiments. This new plasma diagnostic technique will satisfy the need for multispecies impurity ion data by providing absolute measurements of impurity core accumulation, and it will provide the core impurity ion temperature. This project was a joint effort between Lawrence Livermore National Laboratory (LLNL) and researchers at the Wisconsin Plasma Physics Laboratory (WiPPl) at the University of Wisconsin–Madison (UW–Madison). Megan E. Eckart is the principal investigator at LLNL, which is funded separately from UW–Madison. This final report fulfills the reporting obligation of the UW–Madison effort.

Den Hartog, Daniel J. [Department of Physics, Univ

Surface deposition of nanometer scale carbon structures on Bi 2 Sr 2 CaCu 2 O 8+δ using a low-cost scanning electron microscope

In this work, we investigate optically active nanostructures on Bi 2 Sr 2 CaCu 2 O 8+δ (BSCCO). The nanostructures are constructed from carbon nanocrystals formed using the electron beam of a scanning electron microscope to locally decompose residual hydrocarbons at the BSCCO surface. Atomic force microscopy is used to characterize the dimensions of these structures as a function of beam exposure time. This technique has been used to induce localized intercalation to form carbon nanoparticles up to tens of nanometers into a variety of 2D materials. Cross-sectional scanning transmission electron microscopy in BSCCO shows the presence of these carbon deposits on the surface, but there is no evidence they penetrate into the BSCCO substrate. Therefore, this technique is not suitable for localized intercalation in BSCCO, and it does have promise as a cost-effective approach to pattern nanometer scale etch stops.

2D materials

Visualization of the surface distribution of photocatalytic activity at the anatase/rutile TiO2 interface using X-ray photoelectron emission microscopy

We applied X-ray photoelectron emission microscopy (XPEEM) to visualize the surface distribution of photocatalytic activity at the anatase/rutile (A/R) interface of titanium dioxide. Acetic acid was adsorbed on the surface, and its decomposition and desorption reactions under ultraviolet light irradiation were monitored by observing C 1s spectra, enabling direct observation of the spatial distribution of photocatalytic activity. Complementary crystal structure information was obtained using spatially resolved low-energy electron diffraction, low-energy electron microscopy, X-ray absorption spectroscopy, and micro-focused Raman spectroscopy. Comparison with these structural data allowed for the evaluation of the photocatalytic activity as a function of the distance from the A/R interface. The activity is enhanced in the vicinity of the interface and gradually decreases toward both the anatase and rutile regions. These results demonstrate that XPEEM is an effective technique for spatially resolved mapping of photocatalytic activity, which has\\r\\npreviously been inaccessible using conventional characterization techniques.

25 ENERGY STORAGE

Exciton Transport in Perovskite Materials

Halide perovskites have emerged as promising materials for a wide variety of optoelectronic applications, including solar cells, light‐emitting devices, photodetectors, and quantum information applications. In addition to their desirable optical and electronic properties, halide perovskites provide tremendous synthetic flexibility through variation of not only their chemical composition but also their structure and morphology. At the heart of their use in optoelectronic technologies is the interaction of light with electronic excitations in the form of excitons. This review discusses the properties and behavior of excitons in halide perovskite materials, with a particular emphasis on low‐dimensional perovskites and the effects of nanoscale morphology on excitonic behavior. The basic theory of excitonic energy migration in semiconductor nanomaterials is introduced, and novel observations in halide perovskite nanomaterials that have evolved our current understanding are explored. Lastly, many important questions that remain unanswered are presented and exciting emerging directions in low‐dimensional perovskite exciton physics are discussed.

2D materials

Environmental drivers of spatial variation in tropical forest canopy height: Insights from NASA’s GEDI spaceborne LiDAR

Forest canopy height is a fundamental ecosystem property—influencing patterns of forest carbon storage and forest ecosystem responses to climate variability and change. Previous studies have analyzed environmental drivers influencing spatial variation in canopy height at landscape-to-regional scales; however, far less is known about the environmental determinants underlying regional and global scale variation in forest canopy height. Using the canopy height metrics products from Global Ecosystem Dynamics Investigation (GEDI), a space-borne Light Detection and Ranging (LiDAR) instrument specifically designed to characterize forest structure, we analyze the environmental correlates of spatial variation of global tropical forest canopy height. Our study demonstrates that climate, topography, and soil properties account for 75% of the variation in tropical forest canopy height. Elevation, dry season length, and solar radiation are the most important drivers in determining canopy height both locally and regionally. These results emphasize the vulnerability of tropical forest structure to ongoing changes in the earth’s climate and provide a valuable empirical baseline for tropical forest management.

Science & Technology - Other Topics

Operando microscopy for neuromorphic hardware

Microscopy techniques can uncover the physical properties and dynamic behaviours of materials, driving the discovery of emergent phenomena and guiding the design of next-generation computing hardware. As artificial intelligence becomes pervasive, the demand for high-performance materials to support sustainable information technologies is growing. Here, this Review highlights state-of-the-art imaging from electron and X-ray to optical techniques to probe the dynamics of neuromorphic materials, including operando characterization of devices. We examine design principles for neuromorphic materials, along with obstacles that hinder their development. Emphasis is placed on spatially and temporally resolved approaches that capture state changes including phase transitions, ferroic switching and spin-wave propagation that emulate biological components such as neurons, synapses and their connectivity. We discuss challenges in operando characterization and the integration of artificial intelligence-driven analysis for feedback-guided material discovery. Finally, we outline opportunities for real-time imaging of neuromorphic systems, paving the way towards adaptive, brain-inspired hardware.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Forensic characterization of surrogate nuclear explosion debris: radiochemical and spectroscopic strategies for method validation

Surrogate nuclear explosion debris (SNED) has emerged as a critical platform for advancing post-detonation nuclear forensic analysis in the absence of readily accessible historic materials. SNED enables controlled investigation and validation of analytical methodologies used to interrogate the chemical, isotopic, radiological, and microstructural signatures preserved in nuclear explosion debris. This review presents an integrated assessment of destructive and non-destructive analytical techniques commonly employed within decision-driven nuclear forensic workflows. Each technique is discussed individually while highlighting how it contributes to different stages of post-detonation analysis. Core methods – including gamma and alpha spectrometry, ICP-MS, TIMS, SIMS, SEM-EDS, XRF, LIBS, vibrational spectroscopy, and X-ray absorption spectroscopy – are critically evaluated with respect to forensic maturity, information content, and matrix limitations. Emphasis is placed on the role of SNED in benchmarking multi-modal workflows and identifying gaps in reproducing heterogeneity, fractionation, and radiation-driven evolution relevant to forensic attribution.

X-ray spectroscopic methods

Neuromorphic overparameterisation and few-shot learning in multilayer physical neural networks

Abstract Physical neuromorphic computing, exploiting the complex dynamics of physical systems, has seen rapid advancements in sophistication and performance. Physical reservoir computing, a subset of neuromorphic computing, faces limitations due to its reliance on single systems. This constrains output dimensionality and dynamic range, limiting performance to a narrow range of tasks. Here, we engineer a suite of nanomagnetic array physical reservoirs and interconnect them in parallel and series to create a multilayer neural network architecture. The output of one reservoir is recorded, scaled and virtually fed as input to the next reservoir. This networked approach increases output dimensionality, internal dynamics and computational performance. We demonstrate that a physical neuromorphic system can achieve an overparameterised state, facilitating meta-learning on small training sets and yielding strong performance across a wide range of tasks. Our approach’s efficacy is further demonstrated through few-shot learning, where the system rapidly adapts to new tasks.

Science & Technology - Other Topics

Quantum Circuits for the Preparation of Spin Eigenfunctions on Quantum Computers

The application of quantum algorithms to the study of many-particle quantum systems requires the ability to prepare wave functions that are relevant in the behavior of the system under study. Hamiltonian symmetries are important instruments used to classify relevant many-particle wave functions and to improve the efficiency of numerical simulations. In this work, quantum circuits for the exact and approximate preparation of total spin eigenfunctions on quantum computers are presented. Two different strategies are discussed and compared: exact recursive construction of total spin eigenfunctions based on the addition theorem of angular momentum, and heuristic approximation of total spin eigenfunctions based on the variational optimization of a suitable cost function. The construction of these quantum circuits is illustrated in detail, and the preparation of total spin eigenfunctions is demonstrated on IBM quantum devices, focusing on three- and five-spin systems on graphs with triangle connectivity.

97 MATHEMATICS AND COMPUTING

Time-Resolved Stochastic Dynamics of Quantum Thermal Machines

Steady-state quantum thermal machines are typically characterized by a continuous flow of heat between different reservoirs. However, at the level of discrete stochastic realizations, heat flow is unraveled as a series of abrupt quantum jumps, each representing an exchange of finite quanta with the environment. Here, in this work, we present a framework that resolves the dynamics of quantum thermal machines into cycles classified as enginelike, coolinglike, or idle. We analyze the statistics of individual cycle types and their durations, enabling us to determine both the fraction of cycles useful for thermodynamic tasks and the average waiting time between cycles of a given type. Central to our analysis is the notion of intermittency, which captures the operational consistency of the machine by assessing the frequency and distribution of idle cycles. Our framework offers a novel approach to characterizing thermal machines, with significant relevance to experiments involving mesoscopic transport through quantum dots.

full counting statistics

Solid neon as a noise-resilient host for electron qubits above 100 mK

Solid neon can be used as a solid host for single-electron qubits. At temperatures of around 10 mK, electron-on-solid-neon charge qubits exhibit long coherence times and high operation fidelities. However, a systematic characterization of the noise features of such systems is needed for the development of scalable quantum information architectures. Here, in this work, we show that solid neon can be used as a noise-resilient host for electron qubits above 100 mK. We examine the resilience of solid neon against charge and thermal noise when electron-on-solid-neon charge qubits are operated away from the charge-insensitive sweet spot and at elevated temperatures. We show that the extracted high-frequency charge noise density of electron-on-solid-neon qubits, projected as voltage fluctuations on nearby electrodes, is between 10 −4 μV 2 Hz −1 and 10 −6 μV 2 Hz −1 at 0.01 MHz to 1 MHz, which is comparable to common semiconductor hosts. We also show that the electron-on-solid-neon charge qubits operating at frequencies of around 5 GHz can maintain echo coherence times of over 1 μs at temperatures up to 400 mK.

42 ENGINEERING

Frontier Job-Centric Telemetry Dataset

Comprehensive analysis of high-performance computing (HPC) systems requires linking workload execution to system behavior. This kind of analysis is vital for diagnosing performance issues, managing capacity, detecting anomalous workloads, and understanding how applications interact with system hardware. This job-centric telemetry dataset unifies scheduler job records with node-level measurements, enabling direct association between workloads and their corresponding power, thermal, and performance characteristics. It contains sanitized, scheduler related metadata for 152,400 individual jobs that ran on the Frontier supercomputer and ended on selected days throughout 2024 and 2025, a subpopulation of ~6.8% of the total number of allocated jobs with non-zero run time on the system over that same period. Each is linked with files that contain telemetry time series records of the power utilization and temperature behavior of its allocated nodes and their processors during the run time of the job. Where available, a portion of the job files also contain network performance time series. Jobs are sampled from select days that reflect normal levels of user activity and possess job size distributions with large numbers of leadership class jobs (>20% of Frontier nodes). Jobs in this dataset attempt to best represent successful user workflows.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Intermodal microwave-to-optical transduction using silicon-on-sapphire optomechanical ring resonator

Optomechanical and electro-optomechanical systems have emerged as one of the most promising approaches for quantum microwave-to-optical transduction to interconnect distributed quantum modalities for scaling the quantum systems. These systems use suspended structures to increase mode overlap and mitigate loss to achieve high efficiency. However, the suspended design’s poor heat dissipation under strong drive limits the ultimate efficiency. Here, we demonstrate an unsuspended optomechanical ring resonator (OMR) based on the silicon-on-sapphire (SOS) platform for microwave-to-optical frequency conversion. The OMR achieves a triply resonant optical-to-optical conversion with an enhanced coupling rateG b = 3.6 gigahertz per square-root milliwatt at a peak conversion efficiency of 1.2% with 3.6-milliwatt microwave drive power and a microwave-to-optical conversion efficiency of 1.5 × 10 −5 at 10-milliwatt optical drive power. Our results show that the unsuspended SOS platform, which mitigates the thermal effect and is compatible with superconducting qubits, is a promising platform for optomechanical circuitry and quantum transduction.

Science & Technology - Other Topics

Integrated optical frequency division for microwave and mmWave generation

Abstract The generation of ultra-low-noise microwave and mmWave in miniaturized, chip-based platforms can transform communication, radar and sensing systems 1–3 . Optical frequency division that leverages optical references and optical frequency combs has emerged as a powerful technique to generate microwaves with superior spectral purity than any other approaches 4–7 . Here we demonstrate a miniaturized optical frequency division system that can potentially transfer the approach to a complementary metal-oxide-semiconductor-compatible integrated photonic platform. Phase stability is provided by a large mode volume, planar-waveguide-based optical reference coil cavity 8,9 and is divided down from optical to mmWave frequency by using soliton microcombs generated in a waveguide-coupled microresonator 10–12 . Besides achieving record-low phase noise for integrated photonic mmWave oscillators, these devices can be heterogeneously integrated with semiconductor lasers, amplifiers and photodiodes, holding the potential of large-volume, low-cost manufacturing for fundamental and mass-market applications 13 .

Science & Technology - Other Topics

Electron/hadron separation with the TRD based on GaAs pixel detectors

Transition Radiation Detectors (TRDs) are widely used for particle identification in both high-energy physics and astroparticle physics. They are typically equipped with gaseous detectors. The main limitation of these types of detectors is that TR photons and ionization losses cannot be decoupled, which significantly reduces the particle separation power. Recent advancements in the development of pixel detectors based on GaAs sensors offer a unique opportunity to effectively detect TR photons and separate them from ionization losses. Such detectors represent novel devices that combine precise tracking capabilities with particle identification (PID) properties. The present work is dedicated to an experimental study of particle identification properties of the TRD prototype based on 500 μ m-thick GaAs sensor bonded to a Timepix3 chip. Studies were performed at the CERN SPS and it was shown that at a particle momentum of 20 GeV/c, the probability of misidentifying a hadron as an electron is below 10 −2 for an electron detection efficiency of 98%–99%, and it is 1 . 6⋅10 −4 for electron detection efficiency of 90%. This performance surpasses the electron/hadron rejection power of all known TRDs by an order of magnitude for the same detector length.

GaAs detectors

Rapid Assessment of Sulfate Resistance in Mortar and Concrete

Extensive research has been conducted on the sulfate attack of concrete structures; however, the need to adopt the use of more sustainable materials is driving a need for a quicker test method to assess sulfate resistance. This work presents accelerated methods that can reduce the time required for assessing the sulfate resistance of mixtures by 70%. Class F fly ash has historically been used in concrete mixtures to improve sulfate resistance. However, environmental considerations and the evolving energy industry have decreased its availability, requiring the identification of economically viable and environmentally friendly alternatives to fly ash. Another challenge in addressing sulfate attack durability issues in concrete is that the standard sulfate attack test (ASTM C1012) is time-consuming and designed for only standard mortars (not concrete mixtures). To expedite the testing process, accelerated testing methods for both mortar and concrete mixtures were adopted from previous work to further the development of the accelerated tests and to assess the feasibility of testing the sulfate resistance of mortar and concrete mixtures rapidly. This study also established criteria for interpreting sulfate resistance for each of the test methods used in this work. A total of 14 mortar mixtures and four concrete mixtures using two types of Portland cement (Type I and Type I/II) and various supplementary cementitious materials (SCMs) were evaluated in this study. The accelerated testing methods significantly reduced the evaluation time from 12 months to 21 days for mortar mixtures and from 6 months to 56 days for concrete mixtures. The proposed interpretation method for mortar accelerated test results showed acceptable consistency with the ACI 318-19 interpretations for ASTM C1012 results. The interpretation methods proposed for the two concrete sulfate attack tests demonstrated excellent consistency with the ASTM C1012 results from mortar mixtures with the same cementitious materials combinations. Metakaolin was shown to improve sulfate resistance for both mortar and concrete mixtures, while silica fume and natural pozzolan had a limited impact. Using 15% metakaolin in mortar or concrete mixtures with Type I/II cement provided the best sulfate resistance.

Chemistry

Probing the atomic dynamics of ultrafast melting with femtosecond electron diffraction

Melting is an every-day phase transition that is determined by thermodynamic parameters like temperature and pressure. In contrast, ultra-fast melting is governed by the microscopic response to a rapid energy input and, thus, can reveal the strength and dynamics of atomic bonds as well as the energy flow rate to the lattice. Accurately describing these processes remains challenging and requires detailed insights into transient states encountered. Here, we present data from femtosecond electron diffraction measurements that capture the structural evolution of copper during the ultrafast solid-to-liquid phase transformations. At absorbed energy densities 2-4 times the melting threshold, melting begins at the surface slightly below the nominal melting point followed by rapid homogeneous melting throughout the volume. Molecular dynamics simulations reproduce these observations and reveal a weak electron-lattice energy transfer rate for the given experimental conditions. Both simulations and experiments show no indications of rapid lattice collapse when its temperature surpasses proposed limits of superheating, providing evidence that the inherent dynamics limits the speed of disordering in ultrafast melting of metals.

FOS: Physical sciences

In Situ Tracking of Nonthermal Plasma Etching of ZIF-8 Films

Surface characterization is critical for understanding the processes used for preparing catalysts, sorbents, and membranes. Nonthermal plasma (NTP) is a process that achieves high reactivity at low temperatures and is used to tailor the surface properties of materials. In this work, we combine the capabilities of infrared reflection absorption spectroscopy (IRRAS) with NTP for the in situ interrogation of zeolitic imidazolate framework-8 (ZIF-8) thin films to probe modifications in the material induced by oxygen and nitrogen plasmas. The IRRAS measurements in oxygen plasma reveal etching of organic ligands with sequential removal of the methyl group and imidazole ring and with the formation of carbonyl moieties (C═O). In contrast, nitrogen plasma induces mild etching and grafting of nitrile groups (−C≡N). Scanning electron microscopy imaging shows that oxygen plasma, at prolonged times, significantly degrades the ZIF-8 film at the grain boundaries. Treatment of ZIF-8 membranes using mild plasma conditions yields a fivefold enhancement for H 2 /N 2 and CO 2 /CH 4 ideal selectivities and an eightfold enhancement for CO 2 /N 2 ideal selectivity. Additionally, the new tools described here can be used for spectroscopic in situ tracking of plasma-induced chemistry on thin films in general.

IRRAS