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DOE OSTI2021

Molecular structure retrieval directly from laboratory-frame photoelectron spectra in laser-induced electron diffraction

Ubiquitous to most molecular scattering methods is the challenge to retrieve bond distance and angle from the scattering signals since this requires convergence of pattern matching algorithms or fitting methods. This problem is typically exacerbated when imaging larger molecules or for dynamic systems with little a priori knowledge. Here, we employ laser-induced electron diffraction (LIED) which is a powerful means to determine the precise atomic configuration of an isolated gas-phase molecule with picometre spatial and attosecond temporal precision. We introduce a simple molecular retrieval method, which is based only on the identification of critical points in the oscillating molecular interference scattering signal that is extracted directly from the laboratory-frame photoelectron spectrum. The method is compared with a Fourier-based retrieval method, and we show that both methods correctly retrieve the asymmetrically stretched and bent field-dressed configuration of the asymmetric top molecule carbonyl sulfide (OCS), which is confirmed by our quantum-classical calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Photometric redshifts for the S-PLUS Survey: Is machine learning up to the task?

The Southern Photometric Local Universe Survey (S-PLUS) is a novel project that aims to map the Southern Hemisphere using a twelve filter system, comprising five broad-band SDSS-like filters and seven narrow-band filters optimized for important stellar features in the local universe. In this paper we use the photometry and morphological information from the first S-PLUS data release (S-PLUS DR1) cross-matched to unWISE data and spectroscopic redshifts from Sloan Digital Sky Survey DR15. We explore three different machine learning methods (Gaussian Processes with GPz and two Deep Learning models made with TensorFlow) and compare them with the currently used template-fitting method in the S-PLUS DR1 to address whether machine learning methods can take advantage of the twelve filter system for photometric redshift prediction. Using tests for accuracy for both single-point estimates such as the calculation of the scatter, bias, and outlier fraction, and probability distribution functions (PDFs) such as the Probability Integral Transform (PIT), the Continuous Ranked Probability Score (CRPS) and the Odds distribution, we conclude that a deep-learning method using a combination of a Bayesian Neural Network and a Mixture Density Network offers the most accurate photometric redshifts for the current test sample. In conclusion, it achieves single-point photometric redshifts with scatter (σ NMAD ) of 0.023, normalized bias of -0.001, and outlier fraction of 0.64% for galaxies with r_auto magnitudes between 16 and 21.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Moments of parton distribution functions of the pion from lattice QCD using gradient flow

We present a nonperturbative determination of the pion valence parton distribution function (PDF) moment ratios ⟨𝑥 𝑛−1 ⟩/⟨𝑥⟩ up to 𝑛 = 6, using the gradient flow in lattice quantum chromodynamics (QCD). As a testing ground, we employ SU(3) isosymmetric gauge configurations generated by the OpenLat initiative with a pseudoscalar mass of 𝑚 𝜋 ≃ 411 MeV. Our analysis uses four lattice spacings and a nonperturbatively improved action, enabling full control over the continuum extrapolation, and the limit of vanishing flow time, 𝑡 →0. The flowed ratios exhibit O(𝑎 2 ) scaling across the ensembles, and the continuum-extrapolated results, matched to the $\overline{MS}$ scheme at 𝜇 = 2 GeV using next-to-next-to-leading order matching coefficients, show only mild residual flow-time dependence. The resulting ratios, computed with a relatively small number of configurations, are consistent with phenomenological expectations for the pion’s valence distribution, with statistical uncertainties that are competitive with modern global fits. These findings demonstrate that the gradient flow provides an efficient and systematically improvable method to access partonic quantities from first principles. Future extensions of this work will target lighter pion masses toward the physical point, and applications to nucleon structure such as the proton PDFs and the gluon and sea-quark distributions.

lattice QCD↗

DOE OSTI2022

OPALCO - Decatur Island Solar and Energy Storage Project: An Assessment of Battery Technical Performance

Orcas Power & Light Cooperative (OPALCO) is a member-owned, nonprofit cooperative utility that provides energy services to approximately 11,200 customers across 20 islands in San Juan County, Washington. OPALCO’s mostly hydroelectric power is generated by Bonneville Power Administration and delivered to the islands by submarine cables. In 2016, as part of the second round of funding from the Washington state Clean Energy Fund, OPALCO received a $1 million matching grant to support a project that deployed a 504-kW LG community photovoltaic (PV) system in combination with a 1 MW/2 MWh lithium-iron-phosphate battery energy storage system (BESS) on Decatur Island, Washington. The Decatur Island Substation is essential to ensuring reliable energy for the residents of the San Juan Islands as it is the point of interconnection with the mainland transmission system. The BESS, in combination with the community solar array, will deliver an innovative method to both defer the costly upgrade of the transmission system and allow for other high-value applications intended to benefit the utility and its customers. In 2018, Pacific Northwest National Laboratory (PNNL) completed a preliminary economic assessment for several identified use cases in collaboration with OPALCO. Between August 2021 and May 2022, extensive testing was conducted, and the results were used to assess the technical performance of the BESS subjected to actual field operations. Both reference performance and use case tests were performed: (a) Reference performance tests assess the general technical capabilities of the BESS, such as energy capacity, round-trip efficiency (RTE), ramp rate, and signal tracking capability. These are the first tests performed (baseline) and are repeated after use case tests (post cycle). A standardized U.S. Department of Energy (DOE) energy storage performance protocol was used to characterize the BESS, including representative duty cycle profiles, test procedure guidance, and calculation guidance for determining key characteristics. (b) Use case tests examine the performance of the BESS for specific use cases using duty cycles developed by PNNL in collaboration with OPALCO. Four use cases were selected for testing: 1) demand charge reduction, 2) load shaping, 3) outage mitigation, and 4) transmission deferral. The use case duty cycles were developed based on utility and site-specific characteristics in addition to the technical characteristics and physical capabilities of the BESS. Use case tests were performed between the baseline and post cycle tests. This report describes the BESS and its components, presents testing and performance analysis results, and shares key insights and lessons learned from this project. Outcomes of the tests and analyses will help OPALCO understand the performance of the Decatur Island BESS in its current state and design appropriate operational strategies for this and other BESSs over the long term.

14 SOLAR ENERGY↗

DOE OSTI2022

Comparing variability in diagnosis of upper respiratory tract infections in patients using syndromic, next generation sequencing, and PCR-based methods

Early and accurate diagnosis of respiratory pathogens and associated outbreaks can allow for the control of spread, epidemiological modeling, targeted treatment, and decision making–as is evident with the current COVID-19 pandemic. Many respiratory infections share common symptoms, making them difficult to diagnose using only syndromic presentation. Yet, with delays in getting reference laboratory tests and limited availability and poor sensitivity of point-of-care tests, syndromic diagnosis is the most-relied upon method in clinical practice today. Here, we examine the variability in diagnostic identification of respiratory infections during the annual infection cycle in northern New Mexico, by comparing syndromic diagnostics with polymerase chain reaction (PCR) and sequencing-based methods, with the goal of assessing gaps in our current ability to identify respiratory pathogens. Of 97 individuals that presented with symptoms of respiratory infection, only 23 were positive for at least one RNA virus, as confirmed by sequencing. Whereas influenza virus (n = 7) was expected during this infection cycle, we also observed coronavirus (n = 7), respiratory syncytial virus (n = 8), parainfluenza virus (n = 4), and human metapneumovirus (n = 1) in individuals with respiratory infection symptoms. Four patients were coinfected with two viruses. In 21 individuals that tested positive using PCR, RNA sequencing completely matched in only 12 (57%) of these individuals. Few individuals (37.1%) were diagnosed to have an upper respiratory tract infection or viral syndrome by syndromic diagnostics, and the type of virus could only be distinguished in one patient. Thus, current syndromic diagnostic approaches fail to accurately identify respiratory pathogens associated with infection and are not suited to capture emerging threats in an accurate fashion. We conclude there is a critical and urgent need for layered agnostic diagnostics to track known and unknown pathogens at the point of care to control future outbreaks.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Adapting Optimal Velocity Tracking Control to Account for WEC Constraints and Power-Take-Off Efficiencies: Preprint

Wave energy converters (WECs) come in many different forms, from point absorbers, oscillating water columns, to bulge wave devices. This paper focuses on the control of point absorber WECs, which typically have a narrow-banded frequency response and, therefore, control is well placed to improve the energy capture of such WECs. The acausal nature of the control problem means that theoretically optimal control is almost impossible to achieve inpractice; however optimal velocity tracking (OVT) offers a simple and robust approximation to optimal control that can achieve better power capture than passive linear damping methods, albeit with necessarily higher force demands. OVT is a form of impedance matching and the magnitude of the power-take off (PTO) force demand is often not linearly proportional to the WEC velocity, which can lead to PTO force and speed combinations far from the optimalPTO efficiency. The highly non-linear PTO force and speed to efficiency mapping can, without remedial measures, severely diminish the effectiveness of OVT techniques. In this paper, limits to the movement and force of the PTO are demonstrated, allowing OVT to be more easily applied in practice. The effect of PTO efficiency is explored, and a potential solution to the problem of adapting control to account for efficiency is presented. Both aspects of the work presented highlight the requirement for co-design of the WEC, PTO, and controller.

conversion efficiency↗

DOE OSTI2023

An efficient protocol for excited states of large biochromophores

Efficient energy transport in photosynthetic antenna is a long-standing source of inspiration for artificial light harvesting materials. However, characterizing the excited states of the constituent chromophores poses a considerable challenge to mainstream quantum chemical and semiempirical excited state methods due to their size and complexity and the accuracy required to describe small but functionally important changes in their properties. In this paper, we explore an alternative approach to calculating the excited states of large biochromophores, exemplified by a specific method for calculating the Q y transition of bacteriochlorophyll a, which we name Chl-xTB. Using a diagonally dominant approximation to the Casida equation and a bespoke parameterization scheme, Chl-xTB can match time-dependent density functional theory’s accuracy and semiempirical speed for calculating the potential energy surfaces and absorption spectra of chlorophylls. We demonstrate that Chl-xTB (and other prospective realizations of our protocol) can be integrated into multiscale models, including concurrent excitonic and point-charge embedding frameworks, enabling the analysis of biochromophore networks in a native environment. We exploit this capability to probe the low-frequency spectral densities of excitonic energies and interchromophore interactions in the light harvesting antenna protein LH2 (light harvesting complex 2). The impact of low-frequency protein motion on interchromophore coupling and exciton transport has routinely been ignored due to the prohibitive costs of including it in simulations. Our results provide a more rigorous basis for continued use of this approximation by demonstrating that exciton transition energies are unaffected by low-frequency vibrational coupling to exciton interaction energies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Multiagent-Based Dynamic Voltage Support of Power Converters During Fault Ride-Through

Reference point of applicability (RPA) is a predefined point in a distribution network that performance requirements shall apply. As RPA is not directly controlled by a dedicated distributed energy resource (DER), it requires an aggregate response of multiple DERs over a complex meshed network. Here, this article presents a multiagent-based distributed dynamic voltage support (DDVS) method for coordinated aggregate response of multiple DER units to support RPA voltage profile during and after fault ride-through. DDVS implements a multiagent-based leader target tracking scheme with velocity matching and flock centering features to avoid uncoordinated current injections of cooperative DERs. The DDVS is an event-based approach based on RPA requirements. Two-dimensional voltage support objective is handled: 1) coordinated positive sequence current injection for voltage magnitude boosting and 2) coordinated negative sequence current injection for unbalance voltage mitigation. The results demonstrate that the proposed DDVS algorithm addresses emerging coordinated DVS requirement of DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Hamiltonian Truncation Effective Theory

Hamiltonian truncation is a non-perturbative numerical method for calculating observables of a quantum field theory. The starting point for this method is to truncate the interacting Hamiltonian to a finite-dimensional space of states spanned by the eigenvectors of the free Hamiltonian H_0 H 0 with eigenvalues below some energy cutoff E_\text{max} E max . In this work, we show how to treat Hamiltonian truncation systematically using effective field theory methodology. We define the finite-dimensional effective Hamiltonian by integrating out the states above E_\text{max} E max . The effective Hamiltonian can be computed by matching a transition amplitude to the full theory, and gives corrections order by order as an expansion in powers of 1/E_\text{max} 1 / E max . The effective Hamiltonian is non-local, with the non-locality controlled in an expansion in powers of H_0/E_\text{max} H 0 / E max . The effective Hamiltonian is also non-Hermitian, and we discuss whether this is a necessary feature or an artifact of our definition. We apply our formalism to 2D \lambda\phi^4 λ ϕ 4 theory, and compute the the leading 1/E_\text{max}^2 1 / E max 2 corrections to the effective Hamiltonian. We show that these corrections nontrivially satisfy the crucial property of separation of scales. Numerical diagonalization of the effective Hamiltonian gives residual errors of order 1/E_\text{max}^3 1 / E max 3 , as expected by our power counting. We also present the power counting for 3D \lambda \phi^4 λ ϕ 4 theory and perform calculations that demonstrate the separation of scales in this theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Abundance matching analysis of the emission-line galaxy sample in the extended Baryon Oscillation Spectroscopic Survey

We present the measurements of the small-scale clustering for the emission-line galaxy (ELG) sample from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) in the Sloan Digital Sky Survey IV (SDSS-IV). We use conditional abundance matching method to interpret the clustering measurements from 0.34 to 70 h -1 Mpc. In order to account for the correlation between properties of ELGs and their environment, we add a secondary connection between star formation rate of ELGs and halo accretion rate. Three parameters are introduced to model the ELG [O II ] luminosity and to mimic the target selection of eBOSS ELGs. The parameters in our models are optimized using Markov Chain Monte Carlo (MCMC) method. We find that by conditionally matching star formation rate of galaxies and the halo accretion rate, we are able to reproduce the eBOSS ELG small-scale clustering within 1σ error level. Our best-fitting model shows that the eBOSS ELG sample only consists of ~ 12 per cent of all star-forming galaxies, and the satellite fraction of eBOSS ELG sample is 19.3 per cent. We show that the effect of assembly bias is ~ 20 per cent on the two-point correlation function and ~ 5 per cent on the void probability function at scale of r ~ 20 h -1 Mpc.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Precision redshift-space galaxy power spectra using Zel'dovich control variates

Numerical simulations in cosmology require trade-offs between volume, resolution and run-time that limit the volume of the Universe that can be simulated, leading to sample variance in predictions of ensemble-average quantities such as the power spectrum or correlation function(s). Sample variance is particularly acute at large scales, which is also where analytic techniques can be highly reliable. This provides an opportunity to combine analytic and numerical techniques in a principled way to improve the dynamic range and reliability of predictions for clustering statistics. In this paper we extend the technique of Zel'dovich control variates, previously demonstrated for 2-point functions in real space, to reduce the sample variance in measurements of 2-point statistics of biased tracers in redshift space. We demonstrate that with this technique, we can reduce the sample variance of these statistics down to their shot-noise limit out to k ~ 0.2 h Mpc -1 . This allows a better matching with perturbative models and improved predictions for the clustering of e.g. quasars, galaxies and neutral Hydrogen measured in spectroscopic redshift surveys at very modest computational expense. We discuss the implementation of ZCV, give some examples and provide forecasts for the efficacy of the method under various conditions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Total metals, sulfur and organic carbon data; Slate River floodplain, Crested Butte, CO; March 2021-October 2021

This data package includes processed and undiluted measurements for metal, sulfur and organic carbon concentrations from pore water (groundwater) samples from the Slate River floodplain of Crested Butte, CO, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? Samples were collected between March and October of 2021. These measurements were all recorded at the Environmental Measurements Facility (EM-1) at Stanford University in Stanford, CA. Groundwater samples were extracted from a network of installed rhizon (Rhizosphere Research Products, part no. 19.60.21F, 0.6 micrometer mesh size) and piezometer wells within the river floodplain. All water samples were shaded from sun exposure during extraction from the subsurface and preserved at 2C until measured at EM-1.Analysis by ICP-MS:Measurements for total metals were performed on an inductively coupled plasma optical emission spectrometer (ICP-OES; iCAP 6300, Thermo Scientific, Cambridge, U.K.). Calibration standards were prepared from the mulit element stock solution (Sigma-Aldrich Multielement standard for ICP, St. Louis, MO) using matrix matched to sample solutions (2% HNO3). Calibration curves included 5 points with correlation coefficients of >0.99. The QC protocol includes a continuing calibration blank and quality control samples that are analyzed just after calibration and again every 20 samples and at the completion of the run. Acceptable QC responses must be between 90-110% of the certified value. Analysis by Total Organic Carbon:Dissolved organic carbon concentrations were quantified on a total organic carbon (TOC) analyzer (TOC-L, Shimadzu, Kyoto, Japan) running the NPOC method. Standard curves were developed using an Organic Carbon Standard from RICCA Chemical Company (Arlington,TX). A series of 4 to 6 standards were automatically diluted by the instrument in a concentration range that spans that of the samples. A blank sample was run just after the calibration curve and at the end of the run. A QC sample was run every 25 samples. Acceptable QC responses must be between 90-110% of the certified value.All files are in csv format.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Particle signal considerations for isotope ratio analysis with single particle multi-collector inductively coupled plasma mass spectrometry

Particle analysis has benefitted from the advent of single particle inductively coupled plasma-mass spectrometry (spICP-MS) due to its robustness, sensitivity, and high-throughput nature. Previous methods of spICP-MS have typically utilized quadrupole or time-of-flight mass analyzers and therefore employ electron multiplier-based detectors (such as secondary electron multipliers or microchannel plates). However, to obtain precise measurements on elemental or isotopic ratios within individual particles, multi-collector ICP-MS (MC-ICP-MS) can be used. Here, we investigate Ce isotope ratios, specifically 142 Ce/ 140 Ce, by spMC-ICP-MS using an all-Faraday cup collector array. Using 1 μm (diameter) cerium dioxide particles, integration times of the Faraday cup detectors were varied from 50–500 ms. The signal from the cerium isotopes in the particles was used to determine isotope ratios, which closely matched the expected natural isotopic abundances. Due to the signal decay response from the Faraday cups, the signal from particles lasts much longer than the expected 1–2 ms (up to 100 s of ms). To explore this effect on isotope ratio analysis, multiple ratio analysis methods were used to determine how to obtain optimal precision and accuracy. Relative differences were around 2% for methods that calculated isotope ratios from summing the total signal of an individual particle before calculating the ratio (rather than using every data point individually). It was found that summing all data points per particle, or integrating under the signal peak, yielded both accurate and precise isotope ratios within the particle population. Particles were also sampled off a solid substrate via microextraction, and isotope ratios were determined with relative differences of 0.13% to 9%. This demonstrates the ability to use spMC-ICP-MS to obtain isotope ratios on particles, with little to no relative difference in comparison to the expected ratio, even when operating Faraday detectors at fast 50 ms integration times.

Szakas, Sarah E. [Oak Ridge National Laboratory (O↗

DOE OSTI2021

Development of a Vibration Technique Based on Geometric Optimization for Fatigue Life Evaluation of Sandwich Composite Structures

A major obstacle to obtaining cost-effective experimental data on the fatigue life of sandwich panels is the prohibitive amount of time and cost required to carry out millions of cycles. On the other hand, vibration techniques applied to sandwich geometries fail to match the stress patterns that are obtained from standard flexural fatigue tests. To overcome such limitations, a vibration-based fatigue technique is proposed, which entails the use of sandwich specimens whose geometries are optimized to reproduce the stress distribution observed during three point bend loading while vibrating at the first resonant frequency. The proposed vibration technique was experimentally validated. The results, compared with the average number of cycles to failure at different stress ratios obtained via the Three-Point Bending test, showed high levels of accuracy. The proposed method is robust and time effective and indicates the possibility of attaining fatigue lifetime prediction of a wide class of composite elements, such as sandwich panels.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Superior Metal‐Organic Framework Activation with Dimethyl Ether

Abstract Metal–organic frameworks (MOFs) are demonstrated to be readily activated by treatment with the low surface tension, low boiling point solvent dimethyl ether (DME). The mildness of the method enables access to high surface areas by avoiding structural changes in the framework that often plague thermal activation methods. A distinction from previous methods is that DME activation succeeds for materials with coordinatively unsaturated sites (CUS) and non‐CUS MOFs as well. DME displaces solvent molecules occupying the pores of the MOF as well as those coordinated to metal centers; reducing evacuation temperature by using a coordinating, yet highly volatile guest enables low temperature activation with structural retention as demonstrated surface area measurements that match or exceed existing activation protocols.

Wright, Keenan R.↗

DOE OSTI2022

Superior Metal‐Organic Framework Activation with Dimethyl Ether

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Projecting Permafrost Thaw of Sub-Arctic Tundra With a Thermodynamic Model Calibrated to Site Measurements

Northern circumpolar permafrost thaw affects global carbon cycling, as large amounts of stored soil carbon becomes accessible to microbial breakdown under a warming climate. The magnitude of carbon release is linked to the extent of permafrost thaw, which is locally variable and controlled by soil thermodynamics. Soil thermodynamic properties, such as thermal diffusivity, govern the reactivity of the soil-atmosphere thermal gradient, and are controlled by soil composition and drainage. In order to project permafrost thaw for an Alaskan tundra experimental site, we used seven years of site data to calibrate a soil thermodynamic model using a data assimilation technique. The model reproduced seasonal and interannual temperature dynamics for shallow (5–40 cm) and deep soil layers (2–4 m), and simulations of seasonal thaw depth closely matched observed data. The model was then used to project permafrost thaw at the site to the year 2100 using climate forcing data for three future climate scenarios (RCP 4.5, 6.0, and 8.5). Minimal permafrost thawing occurred until mean annual air temperatures rose above the freezing point, after which we measured over a 1 m increase in thaw depth for every 1 °C rise in mean annual air temperature. Under no projected warming scenario was permafrost remaining in the upper 3 m of soil by 2100. We demonstrated an effective data assimilation method that optimizes parameterization of a soil thermodynamic model. The sensitivity of local permafrost to climate warming illustrates the vulnerability of sub-Arctic tundra ecosystems to significant and rapid soil thawing.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

An Evaluation of Representation Learning Methods in Particle Physics Foundation Models

We present a systematic evaluation of representation learning objectives for particle physics within a unified framework. Our study employs a shared transformer-based particle-cloud encoder with standardized preprocessing, matched sampling, and a consistent evaluation protocol on a jet classification dataset. We compare contrastive (supervised and self-supervised), masked particle modeling, and generative reconstruction objectives under a common training regimen. In addition, we introduce targeted supervised architectural modifications that achieve state-of-the-art performance on benchmark evaluations. This controlled comparison isolates the contributions of the learning objective, highlights their respective strengths and limitations, and provides reproducible baselines. We position this work as a reference point for the future development of foundation models in particle physics, enabling more transparent and robust progress across the community.

Chen, Michael [Caltech]↗