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DOE OSTI2020

Determination of the Maturation Status of Dendritic Cells by Applying Pattern Recognition to High-Resolution Images

The maturation or activation status of dendritic cells (DCs) directly correlates with their behavior and immunofunction. A common means to determine the maturity of dendritic cells is from high-resolution images acquired via scanning electron microscopy (SEM) or atomic force microscopy (AFM). While direct and visual, the determination has been made by directly looking at the images by researchers. Here we report a machine learning approach using pattern recognition in conjunction with cellular biophysical knowledge of dendritic cells to determine the maturation status of dendritic cells automatically. The determination from AFM images reaches 100% accuracy. The results from SEM images reaches 94.9%. The results demonstrate the accuracy of using machine learning for accelerating data analysis, extracting information, and drawing conclusions from high-resolution cellular images, paving the way for future applications requiring high-throughput and automation, such as cellular sorting and selection based on morphology, quantification of cellular structure, and DC-based immunotherapy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Accelerating Structure–Property Relationship Discovery with Multimodal Machine Learning and Self-Driving Microscopy

Microscopy combined with local spectroscopy is widely used to correlate nanoscale structure with functional properties in materials, but conventional measurements rely heavily on human-selected sampling locations and predefined targets, limiting data set diversity and the potential for discovery. Here, we present a framework that integrates autonomous microscopy with dual-novelty deep kernel learning (DN-DKL) for adaptive data acquisition and a dual variational autoencoder (VAE) for representation learning. DN-DKL actively guides the microscopy toward structurally and spectroscopically novel regions, enabling efficient collection of large spectral data sets. Dual-VAE embeds local structures and spectroscopic responses into a shared latent manifold that serves as a structure–property relationship map. We applied this framework for the investigation of halide perovskite films by using conductive atomic force microscopy. The results reveal distinct hysteresis behaviors that are linked to specific nanoscale structural motifs, including grain boundary junction points that show hysteresis under different bias conditions and asymmetric grain boundaries that suppress the charge transport. This framework establishes a general strategy that leverages the complementary strengths of self-driving microscopy, machine learning, and human expertise to accelerate scientific discovery in functional materials.

atomic force microscopy↗

DOE OSTI2021

Recovery of Cathode Materials and Aluminum Foil Using a Green Solvent

Effective separation of cathode materials and current collectors is one of the most enabling steps, yet a very challenging step, in recycling electrode scraps and spent Li-ion cells. Here, a green solvent, triethyl phosphate, was used to recover invaluable cobalt-containing cathodes, such as NMC622, by dissolving the polymeric binder of poly(vinylidene fluoride). Electrochemically active materials were separated from cathode scraps collected at the manufacturing step of electrodes through a solvent-based separation method without jeopardizing their physical characteristics, crystalline structure, and electrochemical performance. In this work, we found that the recovered aluminum foils were clean without any sign of corrosion and that the polymeric binder could be recovered via a non-solvent-induced phase separation. Additionally, recovery of cathode materials from spent cells was achieved using refined separation parameters based on the recycling of cathode scraps. It is anticipated that this green solvent-based separation for cathode recovery will attract significant interest by the lithium-ion battery manufacturing and recycling communities.

25 ENERGY STORAGE↗

DOE OSTI2022

The FastEddy® Resident-GPU Accelerated Large-Eddy Simulation Framework: Moist Dynamics Extension, Validation and Sensitivities of Modeling Non-Precipitating Shallow Cumulus Clouds

Herein we describe the moist dynamics formulation implemented within the graphics processing unit-resident large-eddy simulation FastEddy® model, which includes a simple saturation adjustment scheme for condensation and evaporation processes. Two LES model intercomparison exercises for non-precipitating shallow cumulus clouds are simulated in order to validate this model extension, including a static forcing and a time-dependent forcing case. Overall, we find our dynamical, thermodynamical and microphysical quantities, along with turbulence variability and fluxes, to be commensurate with the corresponding model intercomparison results. In addition, sensitivities to specific model settings are investigated. Among these settings, it is shown that boundary layer and cloud layer structure and characteristics are sensitive to use of higher-order advection schemes impacting the vertical distribution of cloud content and associated turbulence statistics. Increasing the timescale of the saturation scheme leads to enhanced liquid water presence and decreases vertical velocity variance within the cloud deck. In some cases, these sensitivities agree with the model-to-model variability reported in the intercomparison exercises, highlighting the important role of specific model implementation choices in the context of shallow cumulus convection simulations. These analyses and findings also provide the basis for future extensions and applications of FastEddy® for modeling moist convection and precipitation scenarios.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Identifying the Growth Phase of Magnetic Reconnection Using Pressure‐Strain Interaction

Abstract Magnetic reconnection often initiates abruptly and then rapidly progresses to a nonlinear quasi‐steady state. While satellites frequently detect reconnection events, ascertaining whether the system has achieved steady‐state or is still evolving in time remains challenging. Here, we propose that the relatively rapid opening of the reconnection separatrices within the electron diffusion region serves as an indicator of the growth phase of reconnection. The opening of the separatrices is produced by electron flows diverging away from the neutral line downstream of the X‐line and flowing around a dipolarization front. This flow pattern leads to characteristic spatial structures in the electron pressure‐strain interaction that could be a useful indicator for the growth phase of a reconnection event. We employ two‐dimensional particle‐in‐cell numerical simulations of anti‐parallel magnetic reconnection to validate this prediction. We find that the signature discussed here, alongside traditional reconnection indicators, can serve as a marker of the growth phase. This signature is potentially accessible using multi‐spacecraft single‐point measurements, such as with NASA's Magnetospheric Multiscale satellites in Earth's magnetotail. Applications to other settings where reconnection occurs are also discussed.

Barbhuiya, M. Hasan [Department of Physics and Ast↗

DOE OSTI2026

An Optimized Parameterization of Sub‐Grid Scale Advection for Convection Permitting Models

Convection‐permitting models (CPMs) explicitly resolve deep convection yet under‐resolve the organized lateral exchanges among drafts and their environment that control entrainment/detrainment, precipitation efficiency, and mesoscale structure. In this work, we introduce the Optimized Advection Scheme (OAS), which introduces a small rotation of the Cartesian frame of reference for the horizontal winds relative to other variables used in advection that induces cross‐gradient transport to mimic under‐resolved convective mixing. The rotation angle is selected to minimize the Kullback–Leibler divergence between the simulated and satellite observed precipitation intensity distributions, yielding a physically consistent perturbation that is computationally inexpensive and portable. Optimized Advection Scheme is implemented in WRF and evaluated over Amazon (April 2014). It shifts precipitation–precipitable‐water joint distributions toward lighter rain, reduces overly intense rates, and improves mesoscale convective system (MCS) lifetime and propagation. Mechanistically, the added cross‐gradient transport promotes convective detrainment and environmental mixing, which cools and moistens the mid‐troposphere, weakens downward momentum transport, alleviates excessive downwelling shortwave biases, and warms the surface temperature. The optimized rotation angle yields comparable improvements at 4‐km and 1‐km grid spacing, demonstrating resolution‐independent benefits across the CPM gray zone. By targeting the dynamical root of under‐mixed convective circulations, rather than tuning model microphysics or closures, OAS delivers robust, scale‐aware improvements in precipitation statistics, cloud vertical structure, and characteristics of MCS (MCSs), offering a practical pathway to more reliable CPM simulations for weather and climate applications.

CPM↗

DOE OSTI2020

Interfacial stabilization for epitaxial CuCrO 2 delafossites

AB O 2 delafossites are fascinating materials that exhibit a wide range of physical properties, including giant Rashba spin splitting and anomalous Hall effects, because of their characteristic layered structures composed of noble metal A and strongly correlated B O 2 sublayers. However, thin film synthesis is known to be extremely challenging owing to their low symmetry rhombohedral structures, which limit the selection of substrates for thin film epitaxy. Hexagonal lattices, such as those provided by Al 2 O 3 (0001) and (111) oriented cubic perovskites, are promising candidates for epitaxy of delafossites. However, the formation of twin domains and impurity phases is hard to suppress, and the nucleation and growth mechanisms thereon have not been studied for the growth of epitaxial delafossites. In this study, we report the epitaxial stabilization of a new interfacial phase formed during pulsed-laser epitaxy of (0001)-oriented CuCrO 2 epitaxial thin films on Al 2 O 3 substrates. Through a combined study using scanning transmission electron microscopy/electron-energy loss spectroscopy and density functional theory calculations, we report that the nucleation of a thermodynamically stable, atomically thick CuCr 1-x Al x O 2 interfacial layer is the critical element for the epitaxy of CuCrO 2 delafossites on Al 2 O 3 substrates. This finding provides key insights into the thermodynamic mechanism for the nucleation of intermixing-induced buffer layers that can be used for the growth of other noble-metal-based delafossites, which are known to be challenging due to the difficulty in initial nucleation.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Structural relaxation of water during rapid cooling from ambient temperatures

Experiments investigating the properties of deeply supercooled liquid water are needed to develop a comprehensive understanding of water’s anomalous properties. One approach involves transiently heating nanoscale water films into the supercooled region for several nanoseconds at a time and then interrogating the water films after they have quenched to cryogenic temperatures. To relate the results obtained with this approach to other experiments and simulations on supercooled water, it is important to understand how closely the quenched structure tracks the (metastable) equilibrium structure of water as a function of the transient heating temperature. A key step involves quantifying the extent to which water that is transiently heated to ambient temperatures [hyperquenched water (HQW)] subsequently relaxes toward the structure of low-density amorphous (LDA) ice as it cools. We analyzed the infrared reflection–absorption spectra of LDA, HQW, and crystalline ice films to determine their complex indices of refraction. With this information, we estimate that HQW retains ~50%–60% of a structural motif characteristic of water at high temperatures with the balance comprised of a low-temperature motif. This result, along with results from x-ray diffraction experiments on water and amorphous ices, allows one to quantify the fraction of the high-temperature motif at approximately zero pressure as a function of temperature from 150 to 350 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Time-resolved turbulent dynamo in a laser plasma

Understanding magnetic-field generation and amplification in turbulent plasma is essential to account for observations of magnetic fields in the universe. A theoretical framework attributing the origin and sustainment of these fields to the so-called fluctuation dynamo was recently validated by experiments on laser facilities in low-magnetic-Prandtl-number plasmas (Pm < 1). However, the same framework proposes that the fluctuation dynamo should operate differently when Pm ≳ 1, the regime relevant to many astrophysical environments such as the intracluster medium of galaxy clusters. This paper reports an experiment that creates a laboratory Pm ≳ 1 plasma dynamo. We provide a time-resolved characterization of the plasma’s evolution, measuring temperatures, densities, flow velocities, and magnetic fields, which allows us to explore various stages of the fluctuation dynamo’s operation on seed magnetic fields generated by the action of the Biermann-battery mechanism during the initial drive-laser target interaction. The magnetic energy in structures with characteristic scales close to the driving scale of the stochastic motions is found to increase by almost three orders of magnitude and saturate dynamically. It is shown that the initial growth of these fields occurs at a much greater rate than the turnover rate of the driving-scale stochastic motions. Here, our results point to the possibility that plasma turbulence produced by strong shear can generate fields more efficiently at the driving scale than anticipated by idealized magnetohydrodynamics (MHD) simulations of the nonhelical fluctuation dynamo; this finding could help explain the large-scale fields inferred from observations of astrophysical systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Strong and almost strong modes of Floquet spin chains in Krylov subspaces

Integrable Floquet spin chains are known to host strong zero and π modes which are boundary operators that respectively commute and anticommute with the Floquet unitary generating stroboscopic time evolution, in addition to anticommuting with a discrete symmetry of the Floquet unitary. Thus the existence of strong modes implies a characteristic pairing structure of the full spectrum. Weak interactions modify the strong modes to almost strong modes that almost commute or anticommute with the Floquet unitary. Manifestations of strong and almost strong modes are presented in two different Krylov subspaces. One is a Krylov subspace obtained from a Lanczos iteration that maps the time evolution generated by the Floquet Hamiltonian onto dynamics of a single particle on a fictitious chain with nearest-neighbor hopping. The second is a Krylov subspace obtained from the Arnoldi iteration that maps the time evolution generated directly by the Floquet unitary onto dynamics of a single particle on a fictitious chain with longer-range hopping. While the former Krylov subspace is sensitive to the branch of the logarithm of the Floquet unitary, the latter obtained from the Arnoldi scheme is not. In this work, the effective single-particle models in the Krylov subspace are discussed, and the topological properties of the Krylov chain that ensure stable zero and π modes at the boundaries are highlighted. The role of interactions is discussed. Expressions for the lifetime of the almost strong modes are derived in terms of the parameters of the Krylov subspace, and are compared with exact diagonalization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Interfacial electron-phonon coupling and quantum confinement in ultrathin Yb films on graphite

Interfacial electron-phonon coupling in ultrathin films has attracted much interest recently. Here, by combining angle-resolved photoemission spectroscopy and scanning tunneling microscopy, we report quantized electronic states and strong interfacial electron-phonon coupling in ultrathin Yb films on graphite. We observed clear kinks in the energy-momentum dispersion of quantum well states, and the kink positions agree well with the energies of optical phonons of graphite. The extracted coupling strength λ is largest for the thinnest film with a preferred (“magic”) thickness of four monolayers and exhibits a strong band dependence, which can be qualitatively accounted for by a simple model. The interfacial electron-phonon coupling also gives rise to characteristic steplike structures in the $dI/dV$ spectra, implying dominant coupling with the phonons with zero in-plane momentum. A Lifshitz transition occurs at higher coverage, where quantum well states derived mainly from 5d electrons dominate near the Fermi level and possess large effective mass (up to ~ 19 m e ). Here our results highlight the potentially important role of interfacial electron-phonon interaction for ultrathin films and provide spectroscopic insight to understand this cross-interface fermion-boson interaction.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Fingerprints of composite fermion Lambda levels in scanning tunneling microscopy

A composite fermion (CF) is a topological quasiparticle that emerges from a nonperturbative attachment of vortices to electrons in strongly correlated two-dimensional materials. Similar to noninteracting fermions that form Landau levels in a magnetic field, CFs can fill analogous “Lambda” levels, giving rise to the fractional quantum Hall (FQH) effect of electrons. Here, we show that Lambda levels can be directly visualized through the characteristic peak structure in the signal obtained via spectroscopy with scanning tunneling microscopy (STM) on a FQH state. Complementary to transport, which probes the low-energy properties of CFs, we show that high-energy features in STM spectra can be interpreted in terms of Lambda levels. We numerically demonstrate that STM spectra can be accurately modeled using Jain's CF theory. Our results show that STM provides a powerful tool for revealing the anatomy of FQH states and identifying physics beyond the noninteracting CF paradigm.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Multifield ultralight dark matter

Ultralight dark matter (ULDM) is usually taken to be a single scalar field. Here we explore the possibility that ULDM consists of N light scalar fields with only gravitational interactions. This configuration is more consistent with the underlying particle physics motivations for these scenarios than a single ultralight field. ULDM halos have a characteristic granular structure that increases stellar velocity dispersion and can be used as observational constraints on ULDM models. In multifield simulations, we find that inside a halo the amplitude of the total density fluctuations decreases as $1/\sqrt{N}$ and that the fields do not become significantly correlated over cosmological timescales. Smoother halos heat stellar orbits less efficiently, reducing the velocity dispersion relative to the single field case and thus weakening the observational constraints on the field mass. Analytically, we show that for N equal-mass fields with mass m the ULDM contribution to the stellar velocity dispersion scales as 1/(Nm 3 ). Finally, lighter fields heat the most efficiently and if the smallest mass mL is significantly below the other field masses the dispersion scales as $1/(N^{2}m^3_L$).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Neural Networks-Based Inverter Control: Modeling and Adaptive Optimization for Smart Distribution Networks

The optimal voltage control of inverter-based resources, especially under the high penetration of solar photovoltaics, is critical to the stability of the distribution power system. However, the computational complexity as well as the coordinated operation performance of the voltage control optimization in the distribution power system limits the real-time applications. To mitigate this issue, a model-free based adaptive optimal control scheme for the smart inverter is proposed to maximize the active power generation, minimize the power loss, and maintain the bus voltages in smart distribution networks. An inverter-based optimization model for coordinated operation is first established, considering the uncertainties of renewable power generation. Subsequently, by collecting the data and control strategies, the neural networks (NNs) based algorithm is proposed to efficiently predict the best possible control strategy. The main objective of this scheme is to accurately predict candidate optimal solutions with near-negligible feasibility and optimization gaps, with the advantage of avoiding complicated iteration-based numerical algorithms. Thereafter, the co-simulation among OpenDSS, MATLAB, and Python is set up to fully take advantage of the three individual software. Experiments are conducted based on different control parameter characteristics and structures of NNs. Finally, the results reveal that an average mean squared error of 0.013 and 1 ms response time are achieved, which is lower than some state-of-the-art methods.

42 ENGINEERING↗

DOE OSTI2025

Measurements of differential two-particle number and transverse momentum correlation functions in pp collisions at $\sqrt{\textit{s}}$ = 13 TeV

Differential two-particle normalized cumulants (R 2 ) and transverse momentum correlations (P 2 ) are measured as a function of the relative pseudorapidity and azimuthal angle difference (Δη, Δφ) of charged particle pairs in minimum bias pp collisions at $\sqrt{s}$ = 13 TeV. The measurements use charged hadrons in the pseudorapidity region of |η| < 0.8 and the transverse momentum range 0.2 < p T < 2.0 in order to focus on soft multiparticle interactions and to complement prior measurements of these correlation functions in p–Pb and Pb–Pb collisions. The correlation functions are reported for both unlike-sign and like-sign pairs and their charge-independent and charge-dependent combinations. Both the R 2 and P 2 measured in pp collisions exhibit features qualitatively similar to those observed in p–Pb and Pb–Pb collisions. The Δη and Δφ root mean square widths of the near-side peak of the correlation functions are evaluated and compared with those observed in p–Pb and Pb–Pb collisions and show smooth evolution with the multiplicity of charged particles produced in the collision. The comparison of the measured correlation functions with predictions from PYTHIA8 shows that this model qualitatively captures their basic structure and characteristics but feature important differences. In addition, the R$^{CD}_{2}$ is used to determine the charge balance function of hadrons produced within the detector acceptance of the measurements. The integral of the balance function is found to be compatible with those reported by a previous measurement in Pb–Pb collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Complex radius in the R-matrix algorithm for inclusion of direct capture component [Slides]

In the low-energy range there are two possible physical mechanisms for γ-ray emissions. While both mechanisms emit γ-rays, the compound radiative capture (CRC) process is generated by the formation of a compound nucleus state before γ-emission. CRC has a characteristic resonance structure in the cross section, The direct radiative capture (DRC) process goes to the final state by the electromagnetic radiation of the incident neutron. DRC has a smooth behavior in the cross section. For light nuclei, a non-negligible component of the neutron capture process can be often associated to DRC process. Although these two mechanisms should be described by a unified theoretical formalism, in the nuclear data libraries, the CRC and DRC components are evaluated and reported separately. The updated R-matrix algorithm will allow the ability to implicitly include correlations between CRC and DRC mechanisms, to improve the quality of nuclear data evaluations, and to facilitate simple large-scale applicability to current nuclear data evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

An Advanced Machine Learning and Artificial Intelligence System for Demonstrating Radiation Regulatory Compliance in DOE Accelerator Facilities

In this Phase II proposal, Applied Research LLC (ARLLC), Thomas Jefferson National Accelerator Facility (Jefferson Lab), and Old Dominion University (ODU) propose the combination of domain knowledge (beam characteristics, fixed structural shielding, earthen burden (the soil and foliage added to the dome of the experimental halls as additional shielding), etc.), machine learning (ML) and/or artificial intelligence (AI) to correlate a variety of multi-modal onsite signals and the radiation fields seen in accessible areas of the accelerator site and the site boundary. The ML/AI will consider the complex influence of environmental parameters affecting the radon contribution of the measurements, focusing on actual data obtained from Jefferson Lab. In Phase I, the coded beam and location data were fed into a deep learning model to predict doses at several designated locations in Jefferson Lab’s facility. Moreover, a dense radiation map was generated using only a sparse collection of the samples in a facility. In Phase II, we will develop a software prototype containing a radiation prediction algorithm, dense radiation map algorithms, and background noise prediction algorithms, with actual data used to evaluate the prototype. This work will provide a framework for evaluation of radiation measurement results around the site based on learned responses. In addition, the proposed approach allows more granular mapping of radiation levels. Better understanding and communication of these levels is related to the overall approach in keeping doses to personnel ALARA.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Time-resolved turbulent dynamo in a laser plasma

Understanding magnetic-field generation and amplification in turbulent plasma is essential to account for observations of magnetic fields in the universe. A theoretical framework attributing the origin and sustainment of these fields to the so-called fluctuation dynamo was recently validated by experiments on laser facilities in low-magnetic-Prandtl-number plasmas (Pm<1). However, the same framework proposes that the fluctuation dynamo should operate differently when Pm≳1, the regime relevant to many astrophysical environments such as the intracluster medium of galaxy clusters. This paper reports an experiment that creates a laboratory Pm≳1 plasma dynamo. We provide a time-resolved characterization of the plasma’s evolution, measuring temperatures, densities, flow velocities, and magnetic fields, which allows us to explore various stages of the fluctuation dynamo’s operation on seed magnetic fields generated by the action of the Biermann-battery mechanism during the initial drive-laser target interaction. The magnetic energy in structures with characteristic scales close to the driving scale of the stochastic motions is found to increase by almost three orders of magnitude and saturate dynamically. It is shown that the initial growth of these fields occurs at a much greater rate than the turnover rate of the driving-scale stochastic motions. Our results point to the possibility that plasma turbulence produced by strong shear can generate fields more efficiently at the driving scale than anticipated by idealized magnetohydrodynamics (MHD) simulations of the nonhelical fluctuation dynamo; this finding could help explain the large-scale fields inferred from observations of astrophysical systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗