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At least 955 records · Page 53

Time-domain theory of transient heat conduction in the local limit

Ultrafast and nanoscale heat conduction demands a unified theoretical framework that rigorously bridges macroscopic transport equations with microscopic material properties derived from statistical physics. Existing empirical generalizations of Fourier's law often lack a solid microscopic foundation, failing to connect observed non-Fourier behavior with underlying atomic-scale mechanisms. In this work, we present a time-domain theory of transient heat conduction rooted in Zwanzig's statistical theory of irreversible processes. Central to this framework is the time-domain transport function $\overleftrightarrow{𝑍}$⁡(𝑡) defined through equilibrium time-correlation functions of heat fluxes. This function generalizes the conventional concept of steady-state thermal conductivity, governing the transition of conduction dynamics from onset second sound type wave propagation at finite speeds to diffusion-dominated behavior across broad temporal and spatial scales. Unlike phonon hydrodynamic models that rely on mesoscopic constructs such as phonon drift velocity, our approach provides a quantitative and microscopic description of intrinsic memory effects in transient heat fluxes and applies universally to bulk materials at any temperature or length scale. By integrating atomistic-scale first-principles calculations with continuum-level macroscopic equations, this framework offers a robust foundation for numerical simulations of transient temperature fields. Furthermore, it facilitates the interpretation and design of transient thermal grating experiments using nanometer-scale heat sources and ultrafast laser systems in the extreme ultraviolet and x-ray wavelength ranges, advancing our understanding of heat dissipation dynamics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Emergent anomalies and generalized Luttinger theorems in metals and semimetals

Luttinger's theorem connects a basic microscopic property of a given metallic crystalline material, the number of electrons per unit cell, to the volume, enclosed by its Fermi surface, which defines its low-energy observable properties. Such statements are valuable since, in general, deducing a low-energy description from microscopics, which may perhaps be regarded as the main problem of condensed matter theory, is far from easy. In this paper, we present a unified framework which allows one to discuss Luttinger theorems for ordinary metals as well as closely analogous exact statements for topological (semi)metals, whose low-energy description contains either discrete points or continuous line nodes. This framework is based on the 't Hooft anomaly of the emergent charge conservation symmetry at each point on the Fermi surface, a concept recently proposed by Else et al. Here we find that the Fermi surface codimension p plays a crucial role for the emergent anomaly. For odd p, such as ordinary metals (p = 1) and magnetic Weyl semimetals (p = 3), the emergent symmetry has a generalized chiral anomaly. For even p, such as graphene and nodal line semimetals (both with p = 2), the emergent symmetry has a generalized parity anomaly. When restricted to microscopic symmetries, such as U(1) and lattice symmetries, the emergent anomalies imply (generalized) Luttinger theorems, relating Fermi surface volume to various topological responses. The corresponding topological responses are the charge density for p = 1, Hall conductivity for p = 3, and polarization for p = 2. As a by-product of our results, we clarify exactly what is anomalous about the surface states of nodal line semimetals.

36 MATERIALS SCIENCE↗

Fluctuating intertwined stripes in the strange metal regime of the Hubbard model

Strongly correlated electron systems host a variety of poorly understood correlations in their high-temperature normal state. Unlike ordered phases defined by order parameters, regions of the normal state are often defined through unconventional properties such as strange metallic transport or spectroscopic pseudogaps. Characterizing the microscopic correlations in the normal state is necessary to elucidate mechanisms that lead to these properties and their connection to ground-state orders. Here, in this paper, we establish the presence of intertwined charge and spin stripes in the strange metal normal state of the Hubbard model using determinant quantum Monte Carlo calculations. The charge and spin density waves constituting the stripes are fluctuating and short ranged; yet they obey a mutual commensurability relation and remain microscopically interlocked, as evidenced through measurements of three-point spin-spin-hole correlation functions. Our findings demonstrate the ability of many-body numerical simulations to unravel the microscopic correlations that define quantum states of matter.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Kinetic-energy dissipation and fluctuations in strongly damped heavy-ion collisions within the stochastic mean-field approach

Microscopic mean-field approaches have been successful in describing the most probable reaction outcomes in low-energy heavy-ion reactions. However, those approaches are known to severely underestimate dispersions of observables around the average values that has limited their applicability. Recently it has been shown that a quantal transport approach based on the stochastic mean-field (SMF) theory significantly improves the description, while its application has been limited so far to fragment mass and charge dispersions. In this work, we extend the quantal transport approach based on the SMF theory for relative kinetic energy dissipation and angular momentum transfer in low-energy heavy-ion reactions. Based on the SMF concept, analytical expressions are derived for the radial and tangential friction and associated diffusion coefficients. Those quantal transport coefficients are calculated microscopically in terms of single-particle orbitals within the time-dependent Hartree-Fock (TDHF) approach. As the first application of the proposed formalism, we consider the radial linear momentum dispersion, neglecting the coupling between radial and angular momenta. We analyze the total kinetic energy (TKE) distribution of binary reaction products in the 136 Xe + 208 Pb reaction at E c.m. =526 MeV and compare with experimental data. From time evolution of single-particle orbitals in TDHF, the radial diffusion coefficient is computed on a microscopic basis, while a phenomenological treatment is introduced for the radial friction coefficient. By solving the quantal diffusion equation for the radial linear momentum, the dispersion of the radial linear momentum is obtained, from which one can construct the TKE distribution. We find that the calculations provide a good description of the TKE distribution for strongly damped events with large energy losses, TKEL ≳ 150 MeV. However, the calculations underestimate the TKE distribution for smaller energy losses. Further studies are needed to improve the technical details of calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Controlling phonon lifetimes via sublattice disordering in AgBiSe 2

Understanding and controlling microscopic heat transfer mechanisms in solids is critical to material design in numerous technological applications. Yet, the current understanding of thermal transport in semiconductors and insulators is limited by the difficulty in directly measuring individual phonon lifetimes and mean free paths, and studying their dependence on the microscopic state of the material. Here in this paper, we report our measurements of microscopic phonon scattering rates in AgBiSe 2 , which exhibits a controllable, reversible change directly linked to microstructure evolution near a reversible structural phase transition, that directly impacts the thermal conductivity. We demonstrate a steplike doubling of phonon scattering rates resultant from the cation disordering at the structural transition. To rationalize the neutron scattering data, we leverage a stepwise approach to account for alterations to the thermal conductivity that are imparted by distinct scattering mechanisms. These results highlight the potential of tunable microstructures housed in a stable crystal matrix to provide a practical route to tailor phonon scattering to optimize thermal transport properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Enabling Autonomous Electron Microscopy for Networked Computation and Steering

Advanced electron microscopy workflows require an ecosystem of microscope instruments and computing systems possibly located at different sites to conduct remotely steered and automated experiments. Current workflow executions involve manual operations for steering and measurement tasks, which are typically performed from control workstations co-located with microscopes; consequently, their operational tempo and effectiveness are limited. We propose an approach based on separate data and control channels for such an ecosystem of Scanning Transmission Electron Microscopes (STEM) and computing systems, for which no general solutions presently exist, unlike the neutron and light source instruments. We demonstrate automated measurement transfers and remote steering of Nion STEM physical instruments over site networks. We propose a Virtual Infrastructure Twin (VIT) of this ecosystem, which is used to develop and test our steering software modules without requiring access to the physical instrument infrastructure. Additionally, we develop a VIT for a multiple laboratory scenario, which illustrates the applicability of this approach to ecosystems connected over wide-area networks, for the development and testing of software modules and their later field deployment.

Al Najjar, Anees↗

Practical considerations in using a binary pseudorandom array for instrument transfer function calibration

Binary pseudo-random array (BPRA) artifacts are useful devices for calibrating the instrument transfer function (ITF) of interferometric microscopes and other optical and non-optical surface and wavefront measurement instruments. The intrinsic white noise character of the power spectral density function of the artifact simplifies the deconvolution of the ITF from the measured power spectral density (PSD). However, resampling of the BPRA intrinsic artifact features with the measurement tool's specific sampling pattern modifies the white noise character of the intrinsic spectrum and needs to be accounted for in the ITF-based data deconvolution process. We have developed an analytic solution to the spectrum of a resampled one- and two- dimensional BPRA. The resultant nominal PSD function is a simple twoparameter cosine function with a period equal to the resampled pixel width. A transfer function model for interferometric microscopes that incorporates this function, along with an ITF that includes aliasing effects and variable numerical aperture (NA), wavelength, and obscuration factor, is used to fit to the BPRA PSDs measured by an interference microscope for a range of objective and zoom lens magnification combinations.

Takacs, PZ↗

Binary pseudo-random array (BPRA) for inspection and calibration for cylindrical wavefront interferometry

High-accuracy metrology is vitally important in manufacturing ultra-high-quality free-form mirrors designed to manipulate X-ray light with nanometer-scale wavelengths. However, surface topography measurements are instrument dependent, and without the knowledge of how the instrument performs under the practical usage conditions, the measured data contain some degree of uncertainty. Binary Pseudo Random Array (BPRA) “white noise” artifact are effective and useful for characterizing the Instrument Transfer Function (ITF) of surface topography metrology tools and wavefront measurement instrument. BPRA artifact contains features with all spatial frequencies in the instrument bandpass with equal weight. As a result, power spectral density of the patterns has a deterministic white-noise-like character that allows direct determination of the ITF with uniform sensitivity over the entire spatial frequency range. The application examples include electron microscopes, x-ray microscopes, interferometric microscopes, and large field-of-view Fizeau Interferometers. Furthermore, we will introduce the application of BPRA method to characterizing the ITF of Cylindrical Wavefront Interferometry (CWI), by developing the BPRA artifact which matches the radius of curvature of the cylindrical wavefront. The data acquisition and analysis procedures for different applications of the ITF calibration technique developed are also discussed.

Munechika, K↗

KSpaceNavigator (KSN)

Intuitive GUI for manipulating microscope stages, allowing to align crystallographic data with stages, allowing to align crystallographic data with stage coordinates and microscope images. Simulates kinematic diffraction patterns and Kikuchi line patterns. Simulated patterns can be displayed as overlay to actually measured data, allowing manual fingerprinting and angular alignment. Crystallographic data is fed to the program in form of CIF (crystallographic information file) files, which are available from many databases and cover virtually all crystal structure ever reported in any journal. Actual goniometer scales can be linearized by lookup tables, program can be used with any microscope goniometer, double tilt and tilt-rotation type. Software requirements: Win32 platform (XP); Compiler/Version: Borland C++ Builder 5; Type of files: Executable modules; Hardware requirement: PC

Duden, Thomas↗

Super-resolution and segmentation deep learning for breast cancer histopathology image analysis

Traditionally, a high-performance microscope with a large numerical aperture is required to acquire high-resolution images. However, the images’ size is typically tremendous. Therefore, they are not conveniently managed and transferred across a computer network or stored in a limited computer storage system. As a result, image compression is commonly used to reduce image size resulting in poor image resolution. Here, we demonstrate custom convolution neural networks (CNNs) for both super-resolution image enhancement from low-resolution images and characterization of both cells and nuclei from hematoxylin and eosin (H&E) stained breast cancer histopathological images by using a combination of generator and discriminator networks so-called super-resolution generative adversarial network-based on aggregated residual transformation (SRGAN-ResNeXt) to facilitate cancer diagnosis in low resource settings. The results provide high enhancement in image quality where the peak signal-to-noise ratio and structural similarity of our network results are over 30 dB and 0.93, respectively. The derived performance is superior to the results obtained from both the bicubic interpolation and the well-known SRGAN deep-learning methods. In addition, another custom CNN is used to perform image segmentation from the generated high-resolution breast cancer images derived with our model with an average Intersection over Union of 0.869 and an average dice similarity coefficient of 0.893 for the H&E image segmentation results. Finally, we propose the jointly trained SRGAN-ResNeXt and Inception U-net Models, which applied the weights from the individually trained SRGAN-ResNeXt and inception U-net models as the pre-trained weights for transfer learning. The jointly trained model’s results are progressively improved and promising. We anticipate these custom CNNs can help resolve the inaccessibility of advanced microscopes or whole slide imaging (WSI) systems to acquire high-resolution images from low-performance microscopes located in remote-constraint settings.

60 APPLIED LIFE SCIENCES↗

Total internal reflection enabled wide-field coherent anti-Stokes Raman scattering microscopy

Wide-field coherent anti-Stokes Raman scattering (CARS) microscopy offers an attractive means for the rapid and simultaneous acquisition of vibrationally resolved images across a large field of view. A major challenge in the implementation lies in how to achieve sufficiently strong excitation fields necessary to drive the third-order optical responses over the large focal region. Here, we report a new wide-field CARS microscope enabled by a total internal reflection excitation scheme using a femtosecond Ti:Sapphire oscillator to generate pump and broadband near-infrared Stokes pulses. The spectrally broad Stokes pulse, in combination with its inherent chirp, offers not only access to a wide range of Raman modes spanning ∼ <#comment/> 1000 to ∼ <#comment/> 3500 c m − <#comment/> 1 but also a straightforward means to select vibrational transitions within this range by simply varying the time delay between the pulses. The unique capabilities of this wide-field CARS microscope were validated by acquiring high-quality CARS images from the model and complex biological samples on conventional microscope coverslips.

Doughty, Benjamin (ORCID:0000000164299329)↗

Total internal reflection enabled wide-field coherent anti-Stokes Raman scattering microscopy

Wide-field coherent anti-Stokes Raman scattering (CARS) microscopy offers an attractive means for the rapid and simultaneous acquisition of vibrationally resolved images across a large field of view. A major challenge in the implementation lies in how to achieve sufficiently strong excitation fields necessary to drive the third-order optical responses over the large focal region. Here, we report a new wide-field CARS microscope enabled by a total internal reflection excitation scheme using a femtosecond Ti:Sapphire oscillator to generate pump and broadband near-infrared Stokes pulses. The spectrally broad Stokes pulse, in combination with its inherent chirp, offers not only access to a wide range of Raman modes spanning ${\sim}{1000}$ to ${\sim}{3500}\;{{\rm cm}^{- 1}}$ but also a straightforward means to select vibrational transitions within this range by simply varying the time delay between the pulses. The unique capabilities of this wide-field CARS microscope were validated by acquiring high-quality CARS images from the model and complex biological samples on conventional microscope coverslips.

36 MATERIALS SCIENCE↗

Open Source Visualization and Analysis Platform for 3D Reconstructions of Materials by Transmission Electron Microscopy

Three-dimensional characterization of materials at the nano- and meso-scale has become possible with transmission and scanning transmission electron microscopes (S/TEM). Its importance has extended to a wide class of nanomaterials such as hydrogen fuel cells, solar cells, industrial catalysts, new battery materials and semiconductor devices, as well as spanning high-tech industry, universities, and national labs. While capable instrumentation is abundant, this rapidly expanding demand for high-resolution tomography is bottlenecked by software that is instead tailored for lower-dose, biological applications and not optimized for higher-resolution materials applications. Existing tomography fails to utilize the chemical information provided by S/TEM spectrometers. To address this problem, this project delivered a scalable, fully functional, freely-distributable, open Source materials tomography package with a modern user interface that enables automated acquisition, alignment, and real-time reconstruction of raw tomography data, and provides advanced segmentation, three-dimensional chemical visualization and analysis optimized for materials applications. It has established an extendable framework capable of automation for high-throughput for the tomography of materials from data acquisition to visualization. Phase I and II delivered a full-featured, cross-platform, clean and integrated application for S/TEM materials tomography. It can read projection data from the microscope, with graphical tools for alignment of data, tomographic reconstruction, segmentation, and visualization of the reconstructed 3D volume. The entire pipeline can be saved to an XML state file, enabling fully reproducible data processing and analysis with a full Python environment for the development of custom algorithms, processing, and analysis requirements. Phase IIB extended the application to provide real-time tomographic reconstruction, "live updates" as data is processed, analysis of big data, and multi-channel tomography. Here, quantitative assessment of nanomaterials can occur as data is being recorded on a 3D visualization platform that accommodates additional information from multiple channels. We provide unmatched high-throughput tomography, where the complete tomographic pipeline from measurement to 3D visualization can occur rapidly. The project was extended to offer capabilities for micro-CT, X-ray, neutron, focused ion beam, atomic electron tomography and atom probe tomography. With over 600 transmission electron microscopes worldwide and approximately 50 coming online each year, the demand and impact of an open-source tomography tool is large. Significant opportunities exist in high-tech industry, universities, and national labs to enable or enhance three-dimensional imaging at the nanoscale and bring automated high-throughput approaches that will accelerate progress in materials characterization and metrology. The project supports a service based business model by enabling lab-specific acquisition and processing customization and integration-support and development that will be provided into Phase III and beyond.

36 MATERIALS SCIENCE↗

Discovering the nature of neutrinos: How nuclear theory will advance this grand endeavor. Final report

Why is there more matter than antimatter in the visible universe? Are neutrinos their own antiparticles? These are some of the most profound questions in science. The detection of a (0vββ) neutrinoless doublebeta decay and the measurement of its half-life is one of the most important experimental endeavors in science because it will answer these questions. Paramount to these measurements are accurate predictions with quantified uncertainties of the 0vββ-decay nuclear transitions, especially for the germanium-76 and xeon-136 nuclei, two candidate materials for building the next generation of DOE funded 0vββ-decay experiments. These predictions will guide the Office of Science’s down selection of experiments as well as aid in determining how much material is needed by these experiments. We studied a specific difficult to assess source of uncertainty that will impact coming microscopic predictions, uncertainty which arises from an incomplete yet systematically improvable model of interactions between nucleons and of nucleons with the other particles involved in decay process, referred to as the theory uncertainty. We employed a surrogate model of the germanium-76 nucleus, and its decay products, just detailed enough to adequately mimic the decaying nucleons need for a reasonable measure of this uncertainty and nothing more, avoiding the immense computational expense required in quantifying uncertainties of the full calculation. We found that microscopic calculations of this process can be expected to achieve relative theory uncertainties around 30%, including an unconstrained contribution that had the potential to spoil microscopic calculations. This results in a nearly order of magnitude on previously estimated uncertainties for this rare decay process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Development of New Experimental Methods for Correlated Operando Surface/Gas Characterization

The predictive understanding of catalytic surface reactions requires accurate microkinetic models, and while decades of work has been devoted to the elucidation of the reaction steps in these models, many open questions remain. One key issue is a lack of approaches enabling the local spatially resolved assessment of catalytic activity over a surface. In this report, we detail efforts to develop a new diagnostic approach to solve this problem. The approach is based upon laser resonance enhanced multiphoton ionization of reaction products emitted into the gas phase followed by spatially resolved imaging of the resultant ions or electrons. Ion imaging is pursued with a velocity-selected spatially resolved ion imaging microscope, while electron imaging was attempted in a low energy electron microscope. Successful demonstration of the ion imaging microscope coupled with the development of transport simulations shows promise for a revolutionary new tool to assess local catalytic activity

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

2D IR Microscopy—Technology for Visualizing Chemical Dynamics in Heterogeneous Environments (Final Technical Report)

The primary focus of this project was the design, prototype, and demonstration of a 2D IR microscope. The start date of this project was July 15, 2016 and the project end date was July 14, 2022. In the early years of this project our team designed, prototyped, and completely integrated a homebuilt microscope head with our high-repetition rate 2D IR spectrometer. Once in place our research team focused on characterizing the 2D IR microscope and using it to investigate model systems relevant to energy technologies. As part of this process, we identified two initial chemical systems to use to further develop 2D IR imaging modalities. The first chemical system developed was a room temperature ionic liquid (RTIL) electrolyte system and the second chemical system was a mixture of carbonates and salts developed as a battery electrolyte system. The completion of this project resulted in the full characterization of chemical dynamics in a bulk RTIL system and the demonstration of 2D IR imaging across the RTIL cast as a microdroplet in silicon oil. In addition, we explored the liquid structures and dynamics of organic carbonate mixtures from the vantage point of the vibrational probe, methyl thiocyanate. By the end of the project, we had moved toward in-depth studies of the organic carbonate mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Identifying the Accuracy of Surface Roughness for Metal Additive Manufacturing Parts Captured with Computed Tomography Scanning

Conventional surface roughness measurement techniques require direct access to internal surfaces, often necessitating destructive sectioning of test articles. Computed tomography (CT) offers a non-destructive alternative for internal surface characterization, but its application in metrology remains unstandardized and sensitive to machine resolution and operator technique. This study investigates the feasibility of using CT scanning to quantify areal surface roughness in metal AM heat exchanger tubes with three distinct internal geometries: ribbed, discrete W, and featureless. CT-derived surface parameters were extracted using custom Python scripts and compared to measurements obtained from a focus variation microscope calibrated against a known standard. Results show that CT-based roughness measurements closely matched microscope values for the discrete W specimen, deviations between CT and microscope measurements were minimal—less than 1 µm—indicating reliable reconstruction. In contrast, the ribbed and featureless specimens, with lower roughness values showed greater discrepancies. The findings suggest that CT scanning can be a viable non-destructive metrology tool for AM parts with surface roughness above approximately 8 µm. For smoother surfaces, current CT capabilities may not provide sufficient accuracy, highlighting the need for resolution-aware workflows and further standardization in CT-based surface metrology.

36 MATERIALS SCIENCE↗

Machine Learning-Enabled Quantitative Analysis of Optically Obscure Scratches on Nickel-Plated Additively Manufactured (AM) Samples

Additively manufactured metal components often have rough and uneven surfaces, necessitating post-processing and surface polishing. Hardness is a critical characteristic that affects overall component properties, including wear. This study employed K-means unsupervised machine learning to explore the relationship between the relative surface hardness and scratch width of electroless nickel plating on additively manufactured composite components. The Taguchi design of experiment (TDOE) L9 orthogonal array facilitated experimentation with various factors and levels. Initially, a digital light microscope was used for 3D surface mapping and scratch width quantification. However, the microscope struggled with the reflections from the shiny Ni-plating and scatter from small scratches. To overcome this, a scanning electron microscope (SEM) generated grayscale images and 3D height maps of the scratched Ni-plating, thus enabling the precise characterization of scratch widths. Optical identification of the scratch regions and quantification were accomplished using Python code with a K-means machine-learning clustering algorithm. The TDOE yielded distinct Ni-plating hardness levels for the nine samples, while an increased scratch force showed a non-linear impact on scratch widths. The enhanced surface quality resulting from Ni coatings will have significant implications in various industrial applications, and it will play a pivotal role in future metal and alloy surface engineering.

36 MATERIALS SCIENCE↗