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DOE OSTI2025

Sensitive detection of structural dynamics using a statistical framework for comparative crystallography

Chemical and conformational changes are crucial to protein function and its pharmacological control. X-ray crystallography can reveal these changes in atomic detail, but standard analysis methods, which refine separate datasets, often overlook differences that are subtle or arise in only a subset of molecules. Direct comparison of crystallographic datasets is, in principle, more powerful, but systematic errors (“scales”) often mask changes in the crystallographic observables (“structure factors”). Machine learning algorithms that jointly estimate scales and structure factors can address this limitation. Here, we augment this approach with multivariate, structured priors derived from crystallographic theory, implemented in the variational deep learning framework Careless. Doing so strongly improves the detection of protein dynamics, element-specific anomalous signals, and the binding of drug candidates, offering a robust approach to comparative crystallography and, potentially, to detection of protein dynamics by other structure determination methods.

Hekstra, Doeke R. [Harvard Univ., Cambridge, MA (U↗

DOE OSTI2025

High-repetition rate, CEP-stable shortwave infrared source with two-cycle pulses for field-resolved spectroscopy

We report on a passively carrier-envelope phase (CEP)-stable optical parametric amplifier generating two-cycle pulses at 2060 nm with energies of up to 2.25 µJ operating at a repetition rate of 400 kHz, specifically designed for applications in field-resolved spectroscopy. The measured pulse duration is 13.6 fs, resulting in two cycles of the carrier wave. Due to the robust CEP-stable front-end design, we achieve an open-loop CEP stability of 250 mrad (rms) and the capability for fast CEP modulation.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Third-order photon correlations extract single-nanocrystal multiexciton properties in solution

Colloidal semiconductor nanocrystals are considered promising materials for high-flux optical applications, including lasing, light-emitting diodes, biological imaging, and quantum optics. In high-flux applications, multiexcitons can significantly contribute to emission, influencing its brightness, spectral purity, and kinetics. As a result, understanding and controlling multiexciton emission in colloidal nanocrystal materials is of the utmost importance. In the past, single-nanocrystal photon correlation methods have been applied to understand biexciton and triexciton efficiencies, lifetimes, and spectra. While powerful, such methods suffer from user selection bias and require stable emission from single nanocrystals. To compensate for this shortcoming, second-order correlation methods were developed to extract sample-averaged biexciton properties from a solution of nanocrystals. Until now, however, the analogous third-order solution photon correlation methods remained unexplored. In this work, we present a pair of third-order photon correlation techniques to obtain the sample-averaged single-nanocrystal triexciton quantum yield and lifetime in a solution-phase experiment. These techniques derive from the relationship between the Poisson probability of nanocrystal photon absorption and the intrinsic probability of nanocrystal photon emission. We validate the theoretical background of these techniques by creating a numerical model to simulate the diffusion and emission of many nanocrystals in solution. Our simulations confirm that the average triexciton quantum yield and triexciton lifetime can be extracted from a solution of nanocrystals. These techniques will enable researchers to gain a better understanding of the fundamental multiexciton properties of colloidal nanocrystals.

Horowitz, Jonah R. [Massachusetts Institute of Tec↗

DOE OSTI2025

Creating and Probing Large Gap 2D Topological Insulators for Quantum Computing (Final Report)

Research under this award focused on experimental and theoretical efforts in developing and characterizing 2D topological insulators (TIs). Key areas of investigation included materials synthesis, device fabrication and characterization, and theoretical advancements. The team synthesized ZrTe 5 , a material with potential for TI phases. Additionally, the team pursued the synthesis of elemental thin films like Indene and Bismuthene, known for their large TI gaps. Indene was successfully stabilized on SiC. Another approach involved stacking and twisting transition metal dichalcogenides (TMDs) to engineer desired TI band structures. On the theoretical front, advancements made under this award predicted remarkable topological properties in twisted WSe2 bilayers, motivating experimental efforts to realize these states. Regarding device fabrication and characterization, significant progress was made in reducing contact resistance, crucial for reliable transport measurements. Contactless Pulsed Tunneling Spectroscopy (CPTS) was employed to study the electronic properties of WTe 2 and WSe 2 . However, challenges in device fabrication and electrode material selection hampered efforts to obtain desired spectra. Ancillary work, utilizing pulsed electrical methods, on the study of sliding ferroelectrics yielded impactful results demonstrating high speed operation and lack of degradation of devices after many billions of cycles.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2026

The Atacama Cosmology Telescope: DR6 Sunyaev-Zel'dovich Selected Galaxy Clusters Catalog

We present the results of a search for galaxy clusters in the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) microwave sky maps covering 16293 square degrees in three frequency bands, using data obtained over the lifetime of the project (2008-2022). We report redshifts and mass estimates for 10040 clusters detected via their Sunyaev-Zel'dovich (SZ) effect with signal-to-noise greater than 4 at a 2.4 arcminute filter scale. The catalog includes 1180 clusters at redshifts greater than 1, and 124 clusters at redshifts greater than 1.5. Using a relation between cluster SZ signal and mass that is consistent with recent weak-lensing measurements, we estimate that clusters detected with signal-to-noise greater than 5 form a sample which is 90% complete for clusters with masses greater than $5 \times 10^{14}$ MSun (measured within a spherical volume with mean density 500 times the critical density). El Gordo, a cluster found in an initial ACT survey of 755 square degrees, remains the most extreme cluster in mass and redshift; we find no cluster with a mass and redshift combination high enough to falsify the standard LCDM cosmology with Gaussian initial perturbations. We make public a variety of data products, including the full cluster candidate list, noise maps, and sky masks, along with our software for cluster detection and instructions for reproducing our cluster catalogs from the public ACT maps.

Aguena, M. [Trieste Observ.; LIneA, Rio de Janeiro↗

DOE OSTI2025

Hubble Space Telescope Observations within the Sphere of Influence of the Powerful Supermassive Black Hole in PKS 0745-191

We present Space Telescope Imaging Spectrograph observations from the Hubble Space Telescope of the supermassive black hole (SMBH) at the center of PKS 0745-191, a brightest cluster galaxy (BCG) undergoing powerful radio-mode active galactic nucleus (AGN) feedback (P cav ~ 5 × 10 45 erg s -1 ). These high-resolution data offer the first spatially resolved map of gas dynamics within an SMBH's sphere of influence under such powerful feedback. Our results reveal the presence of highly chaotic, nondrotational ionized gas flows on subkiloparsec scales, in contrast to the more coherent flows observed on larger scales. While radio-mode feedback effectively thermalizes hot gas in galaxy clusters on kiloparsec scales, within the core, the hot gas flow may decouple, leading to a reduction in angular momentum and supplying ionized gas through cooling, which could enhance accretion onto the SMBH. This process could, in turn, lead to a self-regulating feedback loop. Compared to other BCGs with weaker radio-mode feedback, where rotation is more stable, intense feedback may lead to more chaotic flows, indicating a stronger coupling between jet activity and gas dynamics. Additionally, we observe a sharp increase in velocity dispersion near the nucleus, consistent with a very massive M BH ~ 1.5 × 10 10 M ⊙ SMBH. The density profile of the ionized gas is also notably flat, paralleling the profiles observed in X-ray gas around galaxies where the Bondi radius is resolved. These results provide valuable insights into the complex mechanisms driving galaxy evolution, highlighting the intricate relationship between SMBH fueling and AGN feedback within the host galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Cosmological Simulations of Stellar Halos with Gaia Sausage–Enceladus Analogs: Two Sausages, One Bun?

Observations of the Milky Way’s stellar halo find that it is predominantly comprised of a radially biased population of stars, dubbed the Gaia Sausage–Enceladus, or GSE. These stars are thought to be debris from dwarf galaxy accretion early in the Milky Way’s history. Though typically considered to be from a single merger, it is possible that the GSE debris has multiple sources. To investigate this possibility, we use the IllustrisTNG50 simulation to identify stellar accretion histories in 98 Milky Way analogs—the largest sample for which such an identification has been performed—and find GSE-like debris in 32, with two-merger GSEs accounting for a third of these cases. Distinguishing single-merger GSEs from two-merger GSEs is difficult in common kinematic spaces, but differences are more evident through chemical abundances and star formation histories. This is because single-merger GSEs are typically accreted more recently than the galaxies in two-merger GSEs: the median infall times (with 16th and 84th percentiles) are $5.{9}_{-2.0}^{+3.3}$ and $10.{7}_{-3.7}^{+1.2}$ Gyr ago for single- and two-merger scenarios, respectively. The systematic shifts in abundances and ages that occur as a result suggest that efforts in modeling these aspects of the stellar halo prove ever-important in understanding its assembly.

galactic archaeology↗

DOE OSTI2026

The DREAMS Project: Disentangling the Impact of Halo-to-Halo Variance and Baryonic Feedback on Milky Way Dark Matter Speed Distributions

Dark matter direct detection experiments require information about the local dark matter speed distribution to produce constraints on dark matter candidates, or infer their properties in the event of a discovery. In this paper, we analyze how the uncertainty in the dark matter speed distribution near the Sun is affected by baryonic feedback, halo-to-halo variance, and halo mass. To do so, we harness the statistical power of the new DREAMS cold dark matter simulation suite, which is comprised of 1024 zoom-in Milky Way–mass halos with varied initial conditions as well as cosmological and astrophysical parameters. Applying a normalizing flows emulator to these simulations, we find that the uncertainty in the local dark matter speed distribution is dominated by halo-to-halo variance and, to a lesser extent, uncertainty in host halo mass. Uncertainties in supernova and black hole feedback (from the IllustrisTNG model in this case) are negligible in comparison. Using the DREAMS suite, we present a state-of-the-art prediction for the dark matter speed distribution in the Milky Way. Although the standard halo model is contained within the uncertainty of this prediction, individual galaxies may have distributions that differ from it. Lastly, we apply our DREAMS results to the XENON1T experiment and demonstrate that the astrophysical uncertainties are comparable to the experimental ones, solidifying previous results in the literature obtained with a smaller sample of simulated Milky Way–mass halos.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

exoALMA. XI. ALMA Observations and Hydrodynamic Models of LkCa 15: Implications for Planetary Mass Companions in the Dust Continuum Cavity

In the past decade, the Atacama Large Millimeter/submillimeter Array (ALMA) has revealed a plethora of substructures in the disks surrounding young stars. These substructures have several proposed formation mechanisms, with one leading theory being the interaction between the disk and newly formed planets. In this Letter, we present high angular resolution ALMA observations of LkCa 15’s disk that reveal a striking difference in dust and CO emission morphology. The dust continuum emission shows a ringlike structure characterized by a dust-depleted inner region of ~40 au in radius. Conversely, the CO emission is radially smoother and shows no sign of gas depletion within the dust cavity. We compare the observations with models for the disk–planet interaction, including radiative transfer calculation in the dust and CO emission. This source is particularly interesting, as the presence of massive planets within the dust cavity has been suggested based on previous near-IR observations. We find that the level of CO emission observed within the dust cavity is inconsistent with the presence of planets more massive than Jupiter orbiting between 10 and 40 au. Instead, we argue that the LkCa 15 innermost dust cavity might be created either by a chain of low-mass planets or by other processes that do not require the presence of planets.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Calibration and Performance of Germanium High Voltage Detectors for SuperCDMS SNOLAB

As SuperCDMS SNOLAB is getting ready to search for low mass dark matter particles, using cryogenic Ge and Si detectors, a set of six of the new SuperCDMS High Voltage (HV) detectors (four Ge and two Si) were tested in the Cryogenic Underground TEst facility (CUTE) at SNOLAB. This provided the first opportunity to gain experience with this new detector type and assess their performance thoroughly under low background conditions. Here we describe the SuperCDMS HV detector concept and discuss some of the newly developed analysis methods and approaches. Focusing on the Ge detectors, we investigate the detector performance under voltage bias (up to 90 V), exercise the low energy (keV to sub-keV range) calibration based on the electron capture peaks generated by the decay of $^{71}$Ge, assess the detector resolution, and demonstrate the unexpected (and encouraging) ability of these detectors to also measure high energy interactions in the hundreds of keV range with good resolution (better than 3% at 356 keV).

Albakry, M. F. [British Columbia U.; TRIUMF]↗

DOE OSTI2025

High‐Concentration Antibody Formulation via Solvent‐Based Dehydration

Abstract Although subcutaneous (SC) delivery is the preferred administration route for immunotherapies and other biologics for improved patient compliance and lower healthcare costs, it necessitates high‐concentration antibody formulations. However, high‐concentration antibody solutions face significant instabilities and prohibitively high viscosities. Other approaches for high‐concentration formulations have been developed, including non‐aqueous solutions, which can be irritating or painful, and antibody‐laden hydrogel microparticles, which require centrifugation and are limited to concentrations <300 mg mL −1 . This work presents a new formulation process wherein the antibody is concentrated and encapsulated into hydrogel microparticles via solvent‐based dehydration. The final dosage form is an aqueous particle suspension with a formulation concentration of 360 mg mL −1 . In this process, microparticles are synthesized continuously, and antibody precipitation is realized simultaneously to dehydration, which allows for higher antibody concentrations. Antibody phase behavior and precipitation–dehydration kinetics are analyzed. The antibody is structurally and functionally stable in the microparticle post‐processing and after 4 months. Injectability of the suspension meets clinical standards with glide force <20 N. For the first time, an aqueous antibody formulation at high concentrations comparable to non‐aqueous formulations is presented, ideal for subcutaneous administration. The process is envisioned to be generalizable as a platform for SC delivery in multiple clinical applications.

Zheng, Talia [Department of Chemical Engineering M↗

DOE OSTI2025

Linking Lattice Strain and Fractal Dimensions to Non‐monotonic Volume Changes in Irradiated Nuclear Graphite

Graphite's resilience to high temperatures and neutron damage makes it vital for nuclear reactors, yet irradiation alters its microstructure, degrading key properties. We used small- and wide-angle X-ray scattering to study neutron-irradiated fine-grain nuclear graphite (Grade G347A) across varied temperatures and fluences. Results show significant shifts in internal strain and porosity, correlating with radiation-induced volume changes. Notably, porosity volume distribution (fractal dimensions) follows non-monotonic volume changes, suggesting a link to the Weibull distribution of fracture stress.

X-ray scattering↗

DOE OSTI2024

Imaging the wakes of jets with energy-energy-energy correlators

As the partons in a high energy jet propagate through the droplet of quark-gluon plasma (QGP) produced in a heavy-ion collision they lose energy to, kick, and are kicked by the medium. The resulting modifications to the parton shower encode information about the microscopic nature of QGP. A direct consequence, however, is that the momentum and energy lost by the parton shower are gained by the medium and, since QGP is a strongly coupled liquid, this means that the jet excites a wake in the droplet of QGP. After freezeout, this wake becomes soft hadrons with net momentum in the jet direction meaning that what an experimentalist later reconstructs as a jet includes hadrons originating from both the modified parton shower and its wake. This has made it challenging to find experimental observables that provide an unambiguous view of the dynamical response of a droplet of QGP to a jet shooting through it. Recent years have seen significant substantial advances in the theoretical and experimental understanding of the substructure of jets, in particular, using correlation functions, $\langle$ ($\vec{n}$ 1 )•••$\mathcal{E}$($\vec{n}$ k ) $\rangle$, of the energy flux operator in proton-proton collisions and, recently, in heavy-ion collisions. So far, such studies have focused primarily on the two-point correlator, which allows for the identification of the angular scale of the underlying dynamics. Higher-point correlators hold the promise of mapping out the dynamics themselves. In this paper we perform the first study of the shape-dependent three-point energy-energy-energy correlator in heavy-ion collisions. Using the Hybrid Model to simulate the interactions of high energy jets with the QGP medium, we show that the three-point correlator presents us with a striking new opportunity. We find that hadrons originating from wakes are the dominant contribution to the three-point correlator in the kinematic regime in which the three points are well-separated in angle, forming a roughly equilateral triangle. This equilateral region of the correlator is far from the region populated by collinear vacuum emissions, making it a canvas on which jet wakes are laid out, where experimentalists can map their shapes. Our work provides a key step towards the systematic use of energy correlators to image and unravel the dynamical response of a droplet of QGP that has been probed by a passing jet, and motivates numerous experimental and theoretical studies.

Jets and Jet Substructure↗

DOE OSTI2024

SPECTER: efficient evaluation of the spectral EMD

The Energy Mover’s Distance (EMD) has seen use in collider physics as a metric between events and as a geometric method of defining infrared and collinear safe observables. Recently, the Spectral Energy Mover’s Distance (SEMD) has been proposed as a more analytically tractable alternative to the EMD. In this work, we obtain a closed-form expression for the Riemannian-like p = 2 SEMD metric between events, eliminating the need to numerically solve an optimal transport problem. Additionally, we show how the SEMD can be used to define event and jet shape observables by minimizing the distance between events and parameterized energy flows (similar to the EMD), and we obtain closed-form expressions for several of these observables. We also present the Specter framework, an efficient and highly parallelized implementation of the SEMD metric and SEMD-derived shape observables as an analogue of the previously-introduced Shaper for EMD-based computations. We demonstrate that computing the SEMD with Specter can be up to a thousand times faster than computing the EMD with standard optimal transport libraries.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

SymbolFit: Automatic Parametric Modeling with Symbolic Regression

We introduce SymbolFit (API: https://github.com/hftsoi/symbolfit), a framework that automates parametric modeling by using symbolic regression to perform a machine-search for functions that fit the data while simultaneously providing uncertainty estimates in a single run. Traditionally, constructing a parametric model to accurately describe binned data has been a manual and iterative process, requiring an adequate functional form to be determined before the fit can be performed. The main challenge arises when the appropriate functional forms cannot be derived from first principles, especially when there is no underlying true closed-form function for the distribution. In this work, we develop a framework that automates and streamlines the process by utilizing symbolic regression, a machine learning technique that explores a vast space of candidate functions without requiring a predefined functional form because the functional form itself is treated as a trainable parameter, making the process far more efficient and effortless than traditional regression methods. We demonstrate the framework in high-energy physics experiments at the CERN Large Hadron Collider (LHC) using five real proton-proton collision datasets from new physics searches, including background modeling in resonance searches for high-mass dijet, trijet, paired-dijet, diphoton, and dimuon events. We show that our framework can flexibly and efficiently generate a wide range of candidate functions that fit a nontrivial distribution well using a simple fit configuration that varies only by random seed, and that the same fit configuration, which defines a vast function space, can also be applied to distributions of different shapes, whereas achieving a comparable result with traditional methods would have required extensive manual effort.

Tsoi, Ho Fung [Univ. of Pennsylvania, Philadelphia↗

DOE OSTI2025

Grain boundary segregation in BCC vanadium-based alloys: Quantum-accurate computed segregation spectra and targeted experimental validations

Grain boundaries are critically important to the material performance of fusion reactor materials such as vanadium, particularly mechanical properties and irradiation resistance. A key challenge to the design and control of grain boundaries in vanadium alloys is the lack of quantitative data on grain boundary segregation. In this study, we combine computational and experimental methods to address this gap. Furthermore, using a machine learning-accelerated quantum mechanics/molecular mechanics approach, we calculated the segregation spectra for 28 transition metal elements in polycrystalline vanadium, and validated these predictions experimentally for a subset of solutes that sample a range of segregation behavior, specifically zirconium, titanium, and tungsten, using analytical transmission electron microscopy. Furthermore, the agreement between experiment and theory highlights the predictive capability of our approach. Critically, this work provides a comprehensive database of quantum-accurate solute segregation enthalpies in vanadium, enabling the development of advanced alloys for fusion reactors applications.

Fusion materials↗

DOE OSTI2026

Elastic strain engineering of lattice thermal conductivity of silicon: An ab-initio study

Silicon (Si) is the most essential material in the semiconductor industry. It is important to manage the thermal properties of crystalline Si. Elastic strain engineering (ESE) has proven to be an effective tool in controlling the electrical conductivity of Si in strained-silicon technology; its effects on the thermal conductivity of silicon, therefore, warrants careful investigation. The ESE effect is much more pronounced for nanostructured materials due to the ultralarge elastic strains (on the order of 10%) achievable at the nanoscale. In this work, the lattice thermal conductivity (κ L ) of Si under hydrostatic, biaxial, and uniaxial strain states is studied with ab-initio simulations, and the values of strain-dependent κ L compare well with experimental results and existing molecular dynamics simulations. To understand the mechanisms of strain-modulated κ L , the phonon bands, scattering rate, and Grüneisen parameters of phonon modes are computed. It is shown that strain can significantly change the anharmonicity of the crystal system, thus changing phonon scattering rates and κ L . Our results demonstrate that ESE can reduce silicon κ L by up to approximately 90%. Furthermore, uniaxial and biaxial strains can induce highly anisotropic thermal conductivity in Si, with relative variations up to 58.5% and 14.5%, respectively.

Anisotropy in Thermal Conductivity↗

DOE OSTI2025

Automated design of an additive manufactured compact broadband antenna for plasma reflectometry

Broadband antennas operating in the gigahertz frequency range are regularly used for plasma reflectometry diagnostics. Due to a lack of space and unique diagnostic constraints, these antennas are often custom in design and frequency range. Recent advances in additive manufacturing of high temperature copper alloys allow for expanded freedom in design of these diagnostic antennas. In this work, a heuristic simulated annealing algorithm is used alongside 3-D finite element simulation to automate the design of a double ridged rectangular horn antenna for a reflectometry diagnostic on the DIII-D tokamak. Optimization of antenna performance given the design constraints results in a compact broadband (6-20+ GHz) antenna design. Measured transmission from the additively manufactured antenna matches simulation within reasonable error, and experimental plasma electron density profiles from the DIII-D high-field side scrape-off layer are shown.

Additive manufacturing↗