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DOE OSTI2024

A bioactive supramolecular and covalent polymer scaffold for cartilage repair in a sheep model

Regeneration of hyaline cartilage in human-sized joints remains a clinical challenge, and it is a critical unmet need that would contribute to longer healthspans. Injectable scaffolds for cartilage repair that integrate both bioactivity and sufficiently robust physical properties to withstand joint stresses offer a promising strategy. We report here on a hybrid biomaterial that combines a bioactive peptide amphiphile supramolecular polymer that specifically binds the chondrogenic cytokine transforming growth factor β-1 (TGFβ-1) and crosslinked hyaluronic acid microgels that drive formation of filament bundles, a hierarchical motif common in natural musculoskeletal tissues. The scaffold is an injectable slurry that generates a porous rubbery material when exposed to calcium ions once placed in cartilage defects. The hybrid material was found to support in vitro chondrogenic differentiation of encapsulated stem cells in response to sustained delivery of TGFβ-1. Using a sheep model, we implanted the scaffold in shallow osteochondral defects and found it can remain localized in mechanically active joints. Evaluation of resected joints showed significantly improved repair of hyaline cartilage in osteochondral defects injected with the scaffold relative to defects injected with the growth factor alone, including implantation in the load-bearing femoral condyle. These results demonstrate the potential of the hybrid biomimetic scaffold as a niche to favor cartilage repair in mechanically active joints using a clinically relevant large-animal model.

Science & Technology - Other Topics↗

DOE OSTI2024

Deterministic fabrication of graphene hexagonal boron nitride moiré superlattices

The electronic properties of moiré heterostructures depend sensitively on the relative orientation between layers of the stack. For example, near-magic-angle twisted bilayer graphene (TBG) commonly shows superconductivity, yet a TBG sample with one of the graphene layers rotationally aligned to a hexagonal Boron Nitride (hBN) cladding layer provided experimental observation of orbital ferromagnetism. To create samples with aligned graphene/hBN, researchers often align edges of exfoliated flakes that appear straight in optical micrographs. However, graphene or hBN can cleave along either zig-zag or armchair lattice directions, introducing a 30° ambiguity in the relative orientation of two flakes. By characterizing the crystal lattice orientation of exfoliated flakes prior to stacking using Raman and second-harmonic generation for graphene and hBN, respectively, we unambiguously align monolayer graphene to hBN at a near-0°, not 30°, relative twist angle. We confirm this alignment by torsional force microscopy of the graphene/hBN moiré on an open-face stack, and then by cryogenic transport measurements, after full encapsulation with a second, nonaligned hBN layer. This work demonstrates a key step toward systematically exploring the effects of the relative twist angle between dissimilar materials within moiré heterostructures.

boron nitride↗

DOE OSTI2024

Mechanism-guided engineering of a minimal biological particle for genome editing

The widespread application of genome editing to treat and cure disease requires the delivery of genome editors into the nucleus of target cells. Enveloped delivery vehicles (EDVs) are engineered virally derived particles capable of packaging and delivering CRISPR-Cas9 ribonucleoproteins (RNPs). However, the presence of lentiviral genome encapsulation and replication proteins in EDVs has obscured the underlying delivery mechanism and precluded particle optimization. Here, we show that Cas9 RNP nuclear delivery is independent of the native lentiviral capsid structure. Instead, EDV-mediated genome editing activity corresponds directly to the number of nuclear localization sequences on the Cas9 enzyme. EDV structural analysis using cryo-electron tomography and small molecule inhibitors guided the removal of ~80% of viral residues, creating a minimal EDV (miniEDV) that retains full RNP delivery capability. MiniEDVs are 25% smaller yet package equivalent amounts of Cas9 RNPs relative to the original EDVs and demonstrated increased editing in cell lines and therapeutically relevant primary human T cells. These results show that virally derived particles can be streamlined to create efficacious genome editing delivery vehicles with simpler production and manufacturing.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Electrochemical cofactor recycling of bacterial microcompartments

Bacterial microcompartments (BMCs) are prokaryotic organelles that consist of a protein shell which sequesters metabolic reactions in its interior. While most of the substrates and products are relatively small and can permeate the shell, many of the encapsulated enzymes require cofactors that must be regenerated inside. We have analyzed the occurrence of an enzyme previously assigned as a cobalamin (vitamin B 12 ) reductase and, curiously, found it in many unrelated BMC types that do not employ B 12 cofactors. We propose Nicotinamide adenine dinucleotide (NAD+) regeneration as the function of this enzyme and name it Metabolosome Nicotinamide Adenine Dinucleotide Hydrogen (NADH) dehydrogenase (MNdh). Its partner shell protein BMC-T SE (tandem domain BMC shell protein of the single layer type for electron transfer) assists in passing the generated electrons to the outside. We support this hypothesis with bioinformatic analysis, functional assays, Electron Paramagnetic Resonance spectroscopy, protein voltammetry, and structural modeling verified with X-ray footprinting. This finding represents a paradigm for the BMC field, identifying a new, widely occurring route for cofactor recycling and a new function for the shell as separating redox environments.

bacterial microcompartment↗

DOE OSTI2025

Engineering spin coherence in core-shell diamond nanocrystals

Fluorescent diamond nanocrystals can host spin qubit sensors capable of probing the physical properties of biological systems with nanoscale spatial resolution. Sub-100 nm diamond nanosensors can readily be delivered into intact cells and even living organisms. However, applications beyond current proof-of-principle experiments require a substantial increase in sensitivity, which is limited by surface induced charge instability and electron-spin dephasing. In this work, we utilize engineered core-shell structures to achieve a drastic increase in qubit coherence times (T 2 ) from 1.1 to 35 μs in bare nanodiamonds to upward of 52 to 87 μs. We use electron-paramagnetic-resonance results to present a band bending model and connect silica encapsulation to the removal of deleterious mid-gap surface states that are negatively affecting the qubit’s spin properties. Combined with a 1.9-fold increase in particle luminescence these advances correspond to up to two-order-of-magnitude reduction in integration time. Probing qubit dynamics at a single particle level further reveals that the noise characteristics fundamentally change from a bath with spins that rearrange their spatial configuration during the course of an experiment to a more dilute static bath. The observed results shed light on the underlying mechanisms governing fluorescence and spin properties in diamond nanocrystals and offer an effective noise mitigation strategy based on engineered core-shell structures.

core-shell↗

DOE OSTI2025

Estimating an executive summary of a time series: the tendency

In this paper, we revisit the problem of decomposing a signal into a tendency and a residual. The tendency describes an executive summary of a signal that encapsulates its notable characteristics while disregarding seemingly random, less interesting aspects. Building upon the Intrinsic Time Decomposition (ITD) and information-theoretical analysis, we introduce two alternative procedures for selecting the tendency from the ITD baselines. The first is based on the maximum extrema prominence, namely the maximum difference between extrema within each baseline. Specifically this method selects the tendency as the baseline from which an ITD step would produce the largest decline of the maximum prominence. The second method uses the rotations from the ITD and selects the tendency as the last baseline for which the associated rotation is statistically stationary. We delve into a comparative analysis of the information content and interpretability of the tendencies obtained by our proposed methods and those obtained through conventional low-pass filtering schemes, particularly the Hodrik–Prescott (HP) filter. Our findings underscore a fundamental distinction in the nature and interpretability of these tendencies, highlighting their context-dependent utility with emphasis in multi-scale signals. Through a series of real-world applications, we demonstrate the computational robustness and practical utility of our proposed tendencies, emphasizing their adaptability and relevance in diverse time series contexts.

Time series analysis↗

DOE OSTI2025

Derivative-free stochastic optimization via adaptive sampling strategies

In this paper, we present a novel derivative-free framework for solving unconstrained stochastic optimization problems. Many problems in fields ranging from simulation optimization to reinforcement learning to quantum computing involve settings where only stochastic function values are obtained via a zeroth-order oracle, which has no available gradient information and necessitates the usage of derivative-free optimization methodologies. Our approach includes estimating gradients using stochastic function evaluations and integrating adaptive sampling techniques to control the accuracy in these stochastic approximations. Our framework encapsulates several gradient estimation techniques, including standard finite-difference, Gaussian smoothing, sphere smoothing, randomized coordinate finite-difference, and randomized subspace finite-difference methods. We provide theoretical convergence guarantees for our framework and analyze the worst-case iteration and sample complexities associated with each gradient estimation method. Finally, we demonstrate the empirical performance of the methods on logistic regression and nonlinear least squares problems.

Adaptive sampling↗

DOE OSTI2025

Plumbene: a comprehensive review of theoretical and experimental advances

Plumbene, a two-dimensional (2D) material consisting of a single layer of lead (Pb) atoms in a honeycomb lattice, stands as a pioneering addition to the elemental 2D material family. Here, this comprehensive review encapsulates the theoretical predictions and experimental advancements that underscore its potential. With properties shaped by significant spin-orbit coupling and structural buckling, plumbene offers a playground for phenomena like the quantum spin Hall effect, superconductivity, and topological phase transitions. Despite promising theoretical insights, experimental realization has encountered challenges, primarily due to high reactivity of Pb and the need for precise fabrication conditions. This paper critically examines the electronic, thermal, mechanical, and topological attributes of plumbene, alongside synthesis methods, functionalization techniques, and substrate effects. It further proposes directions for addressing synthesis challenges and integrating plumbene into advanced technologies, particularly in electronic, spintronic, and quantum computing applications. This review aims to bridge the gap between theoretical potential and experimental progress, fostering a deeper understanding of this intriguing material.

2D materials↗

DOE OSTI2024

Growth of metal nanoparticles in hydrocarbon atmosphere of arc discharge

A direct current (DC) arc discharge is a widely used method for large-scale production of metal nanoparticles, core–shell particles, and carbon nanotubes. Here, the growth of iron nanoparticles is explored in a modified DC arc discharge. Iron particles are produced by the evaporation of an anode, made from low-carbon steel. Methane admixture into argon gas serves as a carbon source. Electron microscopy and elemental analysis suggest that methane and/or products of its decomposition adhere to iron clusters forming a carbon shell, which inhibits iron particle growth until its full encapsulation, at which point the iron core growth is ceased. Experimental observations are explained using an aerosol growth model. The results demonstrate the path to manipulate metal particle size in a hydrocarbon arc environment.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2025

Exploring HOD-dependent systematics for the DESI 2024 Full-Shape galaxy clustering analysis

We analyze the robustness of the DESI 2024 cosmological inference from the full shape of the galaxy power spectrum to uncertainties in the Halo Occupation Distribution (HOD) model of the galaxy-halo connection and the choice of priors on nuisance parameters. We assess variations in the recovered cosmological parameters across a range of mocks populated with different HOD models and find that shifts are often greater than 20% of the expected statistical uncertainties from the DESI data. We encapsulate the effect of such shifts in terms of a systematic covariance term, C HOD , and an additional diagonal contribution quantifying the impact of our choice of nuisance parameter priors on the ability of the effective field theory (EFT) model to correctly recover the cosmological parameters of the simulations. These two covariance contributions are designed to be added to the usual covariance term, C stat , describing the statistical uncertainty in the power spectrum measurement, in order to fairly represent these sources of systematic uncertainty. This novel approach should be more general and robust to the choice of model or additional external datasets used in cosmological fits than the alternative approach of adding systematic uncertainties to the recovered marginalised parameter posteriors. We compare the approaches within the context of a fixed ΛCDM model and demonstrate that our method gives conservative estimates of the systematic uncertainty that nevertheless have little impact on the final posteriors obtained from DESI data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Universality of Rényi Entropy in Conformal Field Theory

We use the thermal effective theory to prove that, for the vacuum state in any conformal field theory in 𝑑 dimensions, the 𝑛th Rényi entropy 𝑆$^{(𝑛)}_{𝐴}$ behaves as 𝑆$^{(𝑛)}_{𝐴}$ = [𝑓⁡/(2⁢𝜋⁢𝑛) 𝑑−1 ]⁢[Area⁡(∂𝐴)/(𝑑−2)⁢𝜀 𝑑−2 ]⁢(1+𝑂⁡(𝑛)) in the 𝑛 → 0 limit when the boundary of the entanglement domain 𝐴 is spherical with the UV cutoff 𝜀. The theory dependence is encapsulated in the cosmological constant 𝑓 in the thermal effective action. Using this result, we estimate the density of states for large eigenvalues of the modular Hamiltonian for the domain 𝐴. In two dimensions, we can use the hot spot idea, which describes the effective action in the high-temperature limit when the temperature is position-dependent, to derive more powerful formulas valid for arbitrary positive 𝑛. We discuss the difference between two and higher dimensions and clarify the applicability of the hot spot idea. We also use the thermal effective theory to derive an analog of the Cardy formula for boundary operators in higher dimensions.

Conformal field theory↗

DOE OSTI2025

Bayesian quantification of observability and equation of state of twin stars

The possibility of discovering twin stars, two neutron stars (NSs) with the same mass but different radii, is usually studied in forward modelings by using a restricted number of NS matter equations of state (EOSs) encapsulating a first-order phase transition from hadronic to quark matter (QM). Informing our likelihood function with the NS radius data from GW170817 and using a metamodel with nine parameters capable of mimicking most NS EOSs available in the literature, we conduct a Bayesian quantification of the observability and underlying EOSs of twin stars. Of the accepted EOSs, between 12 and 18% yield twin stars, depending on the restrictions we place on the second branch. The possibility of twin stars remains robust even under recent observational constraints. Here, we show that many of these twin star scenarios are observable with currently available levels of accuracy in measuring NS radii. We also present the marginalized posterior probability density functions (PDFs) of every EOS parameter for each of four mass-radius correlation topologies. We find that the inferred EOS depends sensitively on not only whether twin stars are present, but also the category of twin stars, indicating that the observation of twin stars would provide a strong constraint on the underlying EOS. In particular, for two coexisting hybrid stars having QM cores at different densities, the PDF for QM speed of sound squared 𝑐$^2_{qm}$ has two peaks, one below and another above the conformal limit 𝑐$^2_{qm}$ = 1/3 predicted by perturbative QCD.

QCD in nuclear reactions↗

DOE OSTI2026

Measurement of the 75 As ⁢(𝑛, 2⁢𝑛) cross section at 14.1 MeV at the National Ignition Facility

Here, a new measurement of the 75 As (𝑛, 2⁢𝑛) measurement was performed using the 14.1 MeV neutron pulse produced by fusion experiments at the National Ignition Facility (NIF). The target material consisted of GaAs foils encapsulated in aluminum irradiation containers, along with Au monitor foils, and positioned in the NIF chamber during high neutron yield shots. After irradiation, the GaAs and Au foils were counted with high purity germanium detectors to assess the production of (𝑛, 2⁢𝑛) activation products to determine the flux and the cross section of interest. The measured cross section was 966 ± 71 mb at 14.1 ± 0.37 MeV. This work provides a proof of concept for a platform for performing “ride-along” cross section measurements at NIF to contribute to existing nuclear data as well as measure new cross sections in the future.

and nuclear chemistry↗

DOE OSTI2025

QCD factorization with multihadron fragmentation functions

Important aspects of quantum chromodynamics (QCD) factorization theorems are the properties of the objects involved that can be identified as universal. One example is that the definitions of parton densities and fragmentation functions for different types of hadrons differ only in the identity of the nonperturbative states that form the matrix elements, but are otherwise the same. This leads to independence of perturbative calculations on nonperturbative details of external states. It also lends support to interpretations of correlation functions as encapsulations of intrinsic nonperturbative properties. These characteristics have usually been presumed to still hold true in fragmentation functions even when the observed nonperturbative state is a small-mass cluster of n hadrons rather than simply a single isolated hadron. However, the multidifferential aspect of cross sections that rely on these latter types of fragmentation functions complicates the treatment of kinematical approximations in factorization derivations. That has led to recent claims that the operator definitions for fragmentation functions need to be modified from the single hadron case with nonuniversal prefactors. With such concerns as our motivation, we retrace the steps for factorizing the unpolarized semi-inclusive e + e − annihilation cross section and confirm that they do apply without modification to the case of a small-mass multihadron observed in the final state. In particular, we verify that the standard operator definition from single hadron fragmentation, with its usual prefactor, remains equally valid for the small-mass n -hadron case with the same hard parts and evolution kernels, whereas the more recently proposed definitions with nonuniversal prefactors do not. Our results reaffirm the reliability of most past phenomenological applications of dihadron fragmentation functions. Published by the American Physical Society 2025

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Structure Factors for Hot Neutron Matter from Ab Initio Lattice Simulations with High-Fidelity Chiral Interactions

We present the first ab initio lattice calculations of spin and density correlations in hot neutron matter using high-fidelity interactions at next-to-next-to-next-to-leading order in chiral effective field theory. These correlations have a large impact on neutrino heating and shock revival in core-collapse supernovae and are encapsulated in functions called structure factors. Unfortunately, calculations of structure factors using high-fidelity chiral interactions were well out of reach using existing computational methods. In this Letter, we solve the problem using a computational approach called the rank-one operator (RO) method. The RO method is a general technique with broad applications to simulations of fermionic many-body systems. It solves the problem of exponential scaling of computational effort when using perturbation theory for higher-body operators and higher-order corrections. Using the RO method, we compute the vector and axial static structure factors for hot neutron matter as a function of temperature and density. Here, the ab initio lattice results are in good agreement with virial expansion calculations at low densities but are more reliable at higher densities. Random phase approximation codes used to estimate neutrino opacity in core-collapse supernovae simulations can now be calibrated with ab initio lattice calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Effective many-body interactions in reduced-dimensionality spaces through neural network models

Accurately describing properties of challenging problems in physical sciences often requires complex mathematical models that are unmanageable to tackle head on. Therefore, developing reduced-dimensionality representations that encapsulate complex correlation effects in many-body systems is crucial to advance the understanding of these complicated problems. However, a numerical evaluation of these predictive models can still be associated with a significant computational overhead. To address this challenge, in this paper we discuss a combined framework that integrates recent advances in the development of active-space representations of coupled cluster (CC) downfolded Hamiltonians with neural network approaches. The primary objective of this effort is to train neural networks to eliminate the computationally expensive steps required for evaluating hundreds or thousands of Hugenholtz diagrams, which correspond to multidimensional tensor contractions necessary for evaluating a many-body form of downfolded effective Hamiltonians. Using small molecular systems (the H 2 O and HF molecules) as examples, we demonstrate that training neural networks employing effective Hamiltonians for a few nuclear geometries of molecules can accurately interpolate or extrapolate their forms to other geometrical configurations characterized by different intensities of correlation effects. We also discuss differences between effective interactions that define CC downfolded Hamiltonians with those of bare Hamiltonians defined by Coulomb interactions in the active spaces. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Collective Modes in Multilayer Graphene/𝛼−RuCl 3 Heterostructures

Collective modes in multilayer graphene, such as plasmons and phonons, exhibit sensitivity to displacement fields and interlayer coupling, distinguishing them from their counterparts in single-layer graphene. Here, we engineer collective modes in charge-transfer heterostructures composed of multilayer graphene and 𝛼−RuCl 3 . In heterostructures with a single 𝛼−RuCl 3 interface, the charge transfer generates displacement fields up to 7 V/nm at the interface between 𝛼−RuCl 3 and the adjacent graphene layer—the highest value achieved through charge-transfer methods. As a result of the broken inversion symmetry, we discover enhanced nonlinear optical response and modified phonon selection rules. Conversely, we find that multilayer graphene sandwiched between two 𝛼−RuCl 3 flakes causes displacement fields to cancel. There, we achieve carrier densities as high as 8 ×10 13 cm −2 in multilayer graphene and restore the phonon selection rules to their unperturbed state. Meanwhile, we demonstrate that plasmonic properties derive from the depletion of multiple valence bands. As a result of the quasilinear band dispersion, these “Dirac multiband plasmons” are relatively unaffected by displacement fields. On the other hand, the inverted heterostructure sequence—two multilayer graphene sheets encapsulating 𝛼−RuCl 3 —activates significant alteration of the plasmons via interlayer plasmon-plasmon coupling. Hence, multilayer graphene and 𝛼−RuCl 3 heterostructures offer a gate-free platform for engineering collective modes derived from inversion symmetry and interlayer coupling.

Moore, Samuel L. [Columbia University, New York, N↗

DOE OSTI2024

X-ray-based technologies in emerging fuel cell research

The workshop titled `X-ray-based technologies in emerging fuel cell research', organized by Vivian Stojanoff from Brookhaven National Laboratory (BNL) and Narayanasami Sukumar from Cornell University/Advanced Photon Source-Northeastern Collaborative Access Team, was a notable segment of the National Synchrotron Light Source II and Center for Functional Nanomaterials Users' Meeting held 13–17 May 2024. This one-day event, on 13 May 2024, at BNL in New York, aimed to bring together researchers, beamline scientists, management and developers to propel fuel cell technology forward using model systems inspired by natural photosynthesis and redox enzymes. Furthermore, this summary encapsulates the key discussions, advancements and future implications of the workshop.

Xray↗