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DOE OSTI2016

Entropic screening preserves non-equilibrium nature of nematic phase while enthalpic screening destroys it

The present manuscript describes the role of entropic and enthalpic forces mediated by organic non-polar (hexane) and polar (methanol) solvents on the bulk and microscopic phase transition of a well known nematic liquid crystalline material MBBA (N-(4-methoxybenzylidene)-4-butylaniline) through Differential Scanning calorimetry (DSC), UV-Visible (UV–Vis), and Fourier Transform Infrared (FTIR) spectroscopy. DSC study indicates continuous linear decreases in both nematic-isotropic (N-I) phase transition temperature and enthalpy of MBBA in presence of hexane while both these parameters show a saturation after an initial decay in methanol. These distinct transitional behaviours were explained in terms of the “depletion force” model for entropic screening in hexane and “screening-self-screening” model for methanol. Heating rate dependent DSC studies find that non-Arrhenius behaviour, characteristic of pristine MBBA and a manifestation of non-equilibrium nature [Dan et al., J. Chem. Phys. 143, 094501 (2015)], is preserved in presence of entropic screening in the hexane solution, while it changes to Arrhenius behaviour (signifying equilibrium behaviour) in presence of enthalpic screening in methanol solution. FTIR spectra show similar dependence on the solvent induced screening in the intensities of the imine (—C = N) stretch and the out-of-plane distortion vibrations of the benzene rings of MBBA with hexane and methanol as in DSC, further establishing our entropic and enthalpic screening models. UV–Vis spectra of the electronic transitions in MBBA as a function of temperature also exhibit different dependences of intensities on the solvent induced screening, and an exponential decrease is observed in presence of hexane while methanol completely changes the nature of interaction to follow a linear dependence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Generation of entangled-photons by a quantum dot cascade source in polarized cavities: Using cavity resonances to boost signals and preserve the entanglements

Motivated by recent advances in the development of single photon emitters for quantum information sciences, here we design and formulate a quantum cascade model that describes cascade emission by a quantum dot (QD) in a cavity structure while preserving entanglement that stores information needed for single photon emission. The theoretical approach is based on a photonic structure that consists of two orthogonal cavities in which resonance with either the first or second of the two emitted photons is possible, leading to amplification and rerouting of the entangled light. The cavity–QD scheme uses a four-level cascade emitter that involves three levels for each polarization, leading to two spatially entangled photons for each polarization. By solving the Schrodinger equation, we identify the characteristic properties of the system, which can be used in conjunction with optimization techniques to achieve the “best” design relative to a set of prioritized criteria or constraints in our optical system. The theoretical investigations include an analysis of emission spectra in addition to the joint spectral density profile, and the results demonstrate the ability of the cavities to act as frequency filters for the photons that make up the entanglements and to modify entanglement properties. The results provide new opportunities for the experimental design and engineering of on-demand single photon sources.

Chemistry↗

DOE OSTI2024

A self-consistent Hamiltonian model of the ponderomotive force and its structure preserving discretization

In the presence of an inhomogeneous oscillatory electric field, charged particles experience a net force, averaged over the oscillatory timescale, known as the ponderomotive force. We derive a one-dimensional Hamiltonian model which self-consistently couples the electromagnetic field to a plasma which experiences the ponderomotive force. We derive a family of structure preserving discretizations of the model of varying order in space and time using conforming and broken finite element exterior calculus spectral element methods. In all variants of our discretization framework, the method is found to conserve the Casimir invariants of the continuous model to machine precision and the energy to the order of the splitting method used.

Physics↗

DOE OSTI2024

Advanced fuel fusion, phase space engineering, and structure-preserving geometric algorithms

Non-thermal advanced fuel fusion trades the requirement of a large amount of recirculating tritium in the system for that of large recirculating power. Phase space engineering technologies utilizing externally injected electromagnetic fields can be applied to meet the challenge of maintaining non-thermal particle distributions at a reasonable cost. The physical processes of the phase space engineering are studied from a theoretical and algorithmic perspective. It is emphasized that the operational space of phase space engineering is limited by the underpinning symplectic dynamics of charged particles. The phase space incompressibility according to the Liouville theorem is just one of many constraints, and Gromov's non-squeezing theorem determines the minimum footprint of the charged particles on every conjugate phase space plane. In this sense and level of sophistication, the mathematical abstraction of phase space engineering is symplectic topology. To simulate the processes of phase space engineering, such as the Maxwell demon and electromagnetic energy extraction, and to accurately calculate the minimum footprints of charged particles, recently developed structure-preserving geometric algorithms can be used. The family of algorithms conserves exactly, on discretized spacetime, symplecticity and thus incompressibility, non-squeezability, and symplectic capacities. The algorithms apply to the dynamics of charged particles under the influence of external electromagnetic fields as well as the charged particle–electromagnetic field system governed by the Vlasov–Maxwell equations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

Potentially biogenic carbon preserved in a 4.1 billion-year-old zircon

Here, evidence of life on Earth is manifestly preserved in the rock record. However, the microfossil record only extends to ~3.5 billion years (Ga), the chemofossil record arguably to ~3.8 Ga, and the rock record to 4.0 Ga. Detrital zircons from Jack Hills, Western Australia range in age up to nearly 4.4 Ga. From a population of over 10,000 Jack Hills zircons, we identified one >3.8-Ga zircon that contains primary graphite inclusions. Here, we report carbon isotopic measurements on these inclusions in a concordant, 4.10 ± 0.01-Ga zircon. We interpret these inclusions as primary due to their enclosure in a crack-free host as shown by transmission X-ray microscopy and their crystal habit. Their δ 13 C PDB of –24 ± 5‰ is consistent with a biogenic origin and may be evidence that a terrestrial biosphere had emerged by 4.1 Ga, or ~300 My earlier than has been previously proposed.

58 GEOSCIENCES↗

DOE OSTI2021

A multimillion-year-old record of Greenland vegetation and glacial history preserved in sediment beneath 1.4 km of ice at Camp Century

Understanding the history of the Greenland Ice Sheet (GrIS) is critical for determining its sensitivity to warming and contribution to sea level; however, that history is poorly known before the last interglacial. Most knowledge comes from interpretation of marine sediment, an indirect record of past ice-sheet extent and behavior. Subglacial sediment and rock, retrieved at the base of ice cores, provide terrestrial evidence for GrIS behavior during the Pleistocene. Here, we use multiple methods to determine GrIS history from subglacial sediment at the base of the Camp Century ice core collected in 1966. This material contains a stratigraphic record of glaciation and vegetation in northwestern Greenland spanning the Pleistocene. Enriched stable isotopes of pore-ice suggest precipitation at lower elevations implying ice-sheet absence. Plant macrofossils and biomarkers in the sediment indicate that paleo-ecosystems from previous interglacial periods are preserved beneath the GrIS. Cosmogenic 26 Al/ 10 Be and luminescence data bracket the burial of the lower-most sediment between <3.2 ± 0.4 Ma and >0.7 to 1.4 Ma. In the upper-most sediment, cosmogenic 26 Al/ 10 Be data require exposure within the last 1.0 ± 0.1 My. The unique subglacial sedimentary record from Camp Century documents at least two episodes of ice-free, vegetated conditions, each followed by glaciation. The lower sediment derives from an Early Pleistocene GrIS advance. 26 Al/ 10 Be ratios in the upper-most sediment match those in subglacial bedrock from central Greenland, suggesting similar ice-cover histories across the GrIS. We conclude that the GrIS persisted through much of the Pleistocene but melted and reformed at least once since 1.1 Ma.

58 GEOSCIENCES↗

DOE OSTI2024

Extraordinary preservation of gene collinearity over three hundred million years revealed in homosporous lycophytes

Homosporous lycophytes (Lycopodiaceae) are a deeply diverged lineage in the plant tree of life, having split from heterosporous lycophytes ( Selaginella and Isoetes ) ~400 Mya. Compared to the heterosporous lineage, Lycopodiaceae has markedly larger genome sizes and remains the last major plant clade for which no chromosome-level assembly has been available. Here, we present chromosomal genome assemblies for two homosporous lycophyte species, the allotetraploid Huperzia asiatica and the diploid Diphasiastrum complanatum . Remarkably, despite that the two species diverged ~350 Mya, around 30% of the genes are still in syntenic blocks. Furthermore, both genomes had undergone independent whole genome duplications, and the resulting intragenomic syntenies have likewise been preserved relatively well. Such slow genome evolution over deep time is in stark contrast to heterosporous lycophytes and is correlated with a decelerated rate of nucleotide substitution. Together, the genomes of H. asiatica and D. complanatum not only fill a crucial gap in the plant genomic landscape but also highlight a potentially meaningful genomic contrast between homosporous and heterosporous species.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

Reduced Insulin/Insulin-like Growth Factor-1 Signaling and Dietary Restriction Inhibit Translation but Preserve Muscle Mass in Caenorhabditis elegans

Reduced signaling through the C. elegans insulin/IGF1 like tyrosine kinase receptor daf2 and dietary restriction via bacterial dilution are two well-characterized lifespan-extending interventions that operate in parallel or through (partially) independent mechanisms. Using accurate mass and time tag LCMS/MS quantitative proteomics we detected that the abundance of a large number of ribosomal subunits is decreased in response to dietary restriction as well as in the daf2(e1370) insulin/IGF1 receptor mutant. In addition, general protein synthesis levels in these long-lived worms are repressed. Surprisingly, ribosomal transcript levels were not correlated to actual protein abundance, suggesting that posttranscriptional regulation determines ribosome content. Proteomics also revealed increased presence of many structural muscle cell components in long-lived worms, which appears to result from prioritized preservation of muscle cell volume in nutrient-poor conditions or low insulin-like signaling. Activation of DAF16, but not diet-restriction, stimulates mRNA expression of muscle-related genes to prevent muscle atrophy. Important daf2 specific proteome changes include overexpression of aerobic metabolism enzymes and a general activation of stress responsive and immune defense systems, while increased abundance of many protein subunits of the proteasome core complex is a DR-specific characteristic.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Wavefront Preservation in Soft X-Ray Beamlines for the Advanced Light Source Upgrade

In the 4th generation of X-ray light sources, including Free-Electron Lasers (FEL) and Diffraction-Limited Storage Rings (DLSR), the emittance of the electron beam is small or negligible compared to the emittance of the photon beam produced by insertion devices, thus generating coherent beams of light. Over the next few years, several lightsource facilities will be built or upgraded to produce X-ray beams of unprecedented coherent flux. Delivering these exceptional beams to the sample chambers requires beamline optical systems that are designed to preserve the wavefront properties. Our goal in the Advanced Light Source upgrade project (ALS-U) is to create a new class of beamlines that reach diffraction-limited X-ray optical quality through tightly integrated, efficient optical systems, diagnostics, and adaptive mirrors, thus providing users with new scientific capabilities offered by coherent X-ray light interactions with matter. Herein we describe aspects of the beamlines’ design as they enter the project’s final design phase.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

The structural and functional integrities of porcine myocardium are mostly preserved by cryopreservation

Structural and functional studies of heart muscle are important to gain insights into the physiological bases of cardiac muscle contraction and the pathological bases of heart disease. While fresh muscle tissue works best for these kinds of studies, this is not always practical to obtain, especially for heart tissue from large animal models and humans. Conversely, tissue banks of frozen human hearts are available and could be a tremendous resource for translational research. It is not well understood, however, how liquid nitrogen freezing and cryostorage may impact the structural integrity of myocardium from large mammals. In this study, we directly compared the structural and functional integrity of never-frozen to previously frozen porcine myocardium to investigate the consequences of freezing and cryostorage. X-ray diffraction measurements from hydrated tissue under near-physiological conditions and electron microscope images from chemically fixed porcine myocardium showed that prior freezing has only minor effects on structural integrity of the muscle. Furthermore, mechanical studies similarly showed no significant differences in contractile capabilities of porcine myocardium with and without freezing and cryostorage. These results demonstrate that liquid nitrogen preservation is a practical approach for structural and functional studies of myocardium.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Data and Analysis Preservation in the PHENIX Experiment at RHIC

The PHENIX experiment (the Pioneering High Energy Nuclear Interaction eXperiment) is the largest of the four experiments that have operated at the Relativistic Heavy Ion Collider (RHIC), taking data in 2000-2016. PHENIX has made fundamental contributions to the discovery and study of the Quark-Gluon Plasma, advancement of spin physics and other areas. Currently, the PHENIX Collaboration is analyzing large data samples previously collected, while facing challenges in the area of Data and Analysis Preservation. We describe the strategy and practices employed by the PHENIX Collaboration to meet these challenges by leveraging state-of-the-art platforms and tools created and maintained by the High Energy and Nuclear Physics communities, including Zenodo, HEPData, OpenData, REANA and others.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

EXFOR-NSR PDF database: a system for nuclear knowledge preservation and data curation

Current needs of nuclear science and technology include complete, well-documented, and easily verifiable nuclear data. The complete data records require supporting nuclear bibliography, presently stored in dedicated libraries, in addition, to actual data. Additionally, experimental nuclear reaction data (EXFOR) and Nuclear Science References (NSR) databases contain compilations based on primary (journals) and secondary (conference proceedings, theses, preprints, etc.) publications, and data received from authors via private communications. The secondary library materials and private communications often represent a bottleneck for nuclear data verification, compilation, evaluation, and dissemination activities. To address this issue, bibliographic materials were scanned into PDF (Portable Document Format) files and uploaded in a relational database. The traditional scope of nuclear databases that includes meta-data and numbers derived from data in specialized formats was broadened to accommodate the large volumes of original nuclear data publications. The complete PDF publication files were stored in a relational database as Binary Large OBjects (BLOB). This unique collection of nuclear data compilations and supporting publications generate many opportunities for machine learning applications. The Web interfaces for authorized and public access to the EXFOR-NSR nuclear publications database were implemented at the U.S. National Nuclear Data Center, https://www.nndc.bnl.gov/ and IAEA Nuclear Data Section, https://www-nds.iaea.org/ . The current system is complementary to major nuclear libraries and narrowly focused on nuclear data compilation and evaluation procedures. The contents of the PDF database, details of implementation, and Web interface are described. New capabilities for data curation, knowledge preservation, worldwide dissemination, and natural language processing (NLP) applications are given.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Uncovering interpretable relationships in high-dimensional scientific data through function preserving projections

Abstract In many fields of science and engineering, we frequently encounter experiments or simulations datasets that describe the behavior of complex systems and uncovering human interpretable patterns between their inputs and outputs via exploratory data analysis is essential for building intuition and facilitating discovery. Often, we resort to 2D embeddings for examining these high-dimensional relationships (e.g. dimensionality reduction). However, most existing embedding methods treat the dimensions as coordinates for samples in a high-dimensional space, which fail to capture the potential functional relationships, and the few methods that do take function into consideration either only focus on linear patterns or produce non-linear embeddings that are hard to interpret. To address these challenges, we proposed function preserving projections (FPP), which construct 2D linear embeddings optimized to reveal interpretable yet potentially non-linear patterns between the domain and the range of a high-dimensional function. The intuition here is that humans are good at understanding potentially non-linear patterns in 2D but unable to interpret non-linear mapping from high-dimensional space to 2D. Therefore, we should restrict the projection to linear but not the pattern we are seeking. Using FPP on real-world datasets, one can obtain fundamentally new insights about high-dimensional relationships in extremely large datasets that could not be processed with existing dimension reduction methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Distance preserving machine learning for uncertainty aware accelerator capacitance predictions

Abstract Accurate uncertainty estimations are essential for producing reliable machine learning models, especially in safety-critical applications such as accelerator systems. Gaussian process models are generally regarded as the gold standard for this task; however, they can struggle with large, high-dimensional datasets. Combining deep neural networks with Gaussian process approximation techniques has shown promising results, but dimensionality reduction through standard deep neural network layers is not guaranteed to maintain the distance information necessary for Gaussian process models. We build on previous work by comparing the use of the singular value decomposition against a spectral-normalized dense layer as a feature extractor for a deep neural Gaussian process approximation model and apply it to a capacitance prediction problem for the High Voltage Converter Modulators in the Oak Ridge Spallation Neutron Source. Our model shows improved distance preservation and predicts in-distribution capacitance values with less than 1% error.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Preserving isohydricity: vertical environmental variability explains Amazon forest water-use strategies

Abstract Increases in hydrological extremes, including drought, are expected for Amazon forests. A fundamental challenge for predicting forest responses lies in identifying ecological strategies which underlie such responses. Characterization of species-specific hydraulic strategies for regulating water-use, thought to be arrayed along an ‘isohydric–anisohydric’ spectrum, is a widely used approach. However, recent studies have questioned the usefulness of this classification scheme, because its metrics are strongly influenced by environments, and hence can lead to divergent classifications even within the same species. Here, we propose an alternative approach positing that individual hydraulic regulation strategies emerge from the interaction of environments with traits. Specifically, we hypothesize that the vertical forest profile represents a key gradient in drought-related environments (atmospheric vapor pressure deficit, soil water availability) that drives divergent tree water-use strategies for coordinated regulation of stomatal conductance (gs) and leaf water potentials (ΨL) with tree rooting depth, a proxy for water availability. Testing this hypothesis in a seasonal eastern Amazon forest in Brazil, we found that hydraulic strategies indeed depend on height-associated environments. Upper canopy trees, experiencing high vapor pressure deficit (VPD), but stable soil water access through deep rooting, exhibited isohydric strategies, defined by little seasonal change in the diurnal pattern of gs and steady seasonal minimum ΨL. In contrast, understory trees, exposed to less variable VPD but highly variable soil water availability, exhibited anisohydric strategies, with fluctuations in diurnal gs that increased in the dry season along with increasing variation in ΨL. Our finding that canopy height structures the coordination between drought-related environmental stressors and hydraulic traits provides a basis for preserving the applicability of the isohydric-to-anisohydric spectrum, which we show here may consistently emerge from environmental context. Our work highlights the importance of understanding how environmental heterogeneity structures forest responses to climate change, providing a mechanistic basis for improving models of tropical ecosystems.

Forestry↗

DOE OSTI2025

Signal-preserving CMB component separation with machine learning

Analysis of microwave sky signals, such as the cosmic microwave background, often requires component separation using multifrequency methods, whereby different signals are isolated according to their different frequency behaviors. Many so-called blind methods, such as the internal linear combination (ILC), make minimal assumptions about the spatial distribution of the signal or contaminants, and only assume knowledge of the frequency dependence of the signal. The ILC produces a minimum-variance linear combination of the measured frequency maps. In the case of Gaussian, statistically isotropic fields, this is the optimal linear combination, as the variance is the only statistic of interest. However, in many cases the signal we wish to isolate, or the foregrounds we wish to remove, are non-Gaussian and/or statistically anisotropic (in particular for the case of Galactic foregrounds). In such cases, it is possible that machine learning (ML) techniques can be used to exploit the non-Gaussian features of the foregrounds and thereby improve component separation. However, many ML techniques require the use of complex, difficult-to-interpret operations on the data. We propose a hybrid method whereby we train an ML model using only combinations of the data that , and combine the resulting ML-predicted foreground estimate with the ILC solution to reduce the error from the ILC. We demonstrate our methods on simulations of extragalactic temperature and Galactic polarization foregrounds and show that our ML model can exploit non-Gaussian features, such as point sources and spatially varying spectral indices, to produce lower-variance maps than ILC—e.g., reducing the variance of the B-mode residual by factors of up to 5—while preserving the signal of interest in an unbiased manner. Moreover, we often find improved performance even when applying our ML technique to foreground models on which it was not trained. Published by the American Physical Society 2025

McCarthy, Fiona (ORCID:0000000253893565)↗

DOE OSTI2025

Classical Non-Markovian Noise in Symmetry-Preserving Quantum Dynamics

In quantum dynamics, symmetries are vital for identifying and assessing conserved quantities that govern the evolution of a quantum system. When promoted to the open quantum system setting, dynamical symmetries can be negatively altered by system-environment interactions, thus, complicating their analysis. Previous work on noisy symmetric quantum dynamics has focused on the Markovian setting, despite the ubiquity of non-Markovian noise in a number of widely used quantum technologies. Here, in this Letter, we develop a framework for quantifying the impact of non-Markovian noise on symmetric quantum evolution via root space decompositions and the filter function formalism. We demonstrate analytically that symmetry-preserving noise maintains the symmetric subspace, while nonsymmetric noise leads to highly specific leakage errors that are block diagonal in the symmetry representation. We support our findings with numerical studies of a transverse-field Ising model and a quantum error detecting code subject to spatiotemporally correlated multiaxis noise. Our results are broadly applicable, providing new analytic insights into the control and characterization of open quantum system dynamics.

decoherence↗

DOE OSTI2019

Adversarial Training for Privacy-Preserving Deep Learning Model Distribution

Collaboration among cancer registries is essential to develop accurate, robust, and generalizable deep learning models for automated information extraction from cancer pathology reports. Sharing data presents a serious privacy issue, especially in biomedical research and healthcare delivery domains. Distributing pretrained deep learning (DL) models has been proposed to avoid critical data sharing. However, there is growing recognition that collaboration among clinical institutes through DL model distribution exposes new security and privacy vulnerabilities. These vulnerabilities increase in natural language processing (NLP) applications, in which the dataset vocabulary with word vector representations needs to be associated with the other model parameters. In this paper, we propose a novel privacy-preserving DL model distribution across cancer registries for information extraction from cancer pathology reports with privacy and confidentiality considerations. The proposed approach exploits the adversarial training framework to distinguish private features from shared features among different datasets. It only shares registry-invariant model parameters, without sharing raw data nor registry-specific model parameters among cancer registries. Thus, it protects both the data and the trained model simultaneously. We compare our proposed approach to single-registry models, and a model trained on centrally hosted data from different cancer registries. The results show that the proposed approach significantly outperforms the single-registry models and achieves statistically indistinguishable micro and macro F1-score as compared to the centralized model.

Alawad, Mohammed↗