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DOE OSTI2022

Technical and Economic Evaluation of the First Ever Polymer Flood Field Pilot to Enhance the Recovery of Heavy Oils on Alaska's North Slope via Machine Assisted History Matching

Polymer flooding has become globally established as a potential enhanced oil recovery method for heavy oils. To determine whether this technology may be useful in developing the substantial heavy oil resources on the Alaska North Slope, a polymer flood field pilot commenced at the Milne Point Unit in August 2018. This study seeks to evaluate the results of the field pilot on a technical and economic basis. A reservoir simulation model is constructed and calibrated to predict the oil recovery performance of the pilot through machine-assisted reservoir simulation techniques. To replicate the early water breakthrough observed during waterflooding, transmissibility contrasts are introduced into the simulation model, forcing viscous fingering effects. In the ensuing polymer flood, these transmissibility contrasts are reduced to replicate the restoration of injection conformance during polymer flooding. Transmissibility contrasts are later reinstated to replicate fracture overextension interpreted in one of the producing wells. The calibrated simulation models produced at each stage of the history matching process are used to forecast oil recovery. These forecasts are used as input for economic analysis, incremental to waterflooding expectations. The simulation forecasts indicate that polymer flooding significantly increases the heavy oil production for this field pilot compared to waterflooding alone, yielding attractive project economics. However, meaningful variations between simulation scenarios demonstrate that a simulation model is only valid for prediction if flow behavior in the reservoir remains consistent with that observed during the history matched period. Critically, this means that a simulation model calibrated for waterflooding may not fully capture the technical and economic benefits of an enhanced oil recovery process such as polymer flooding. Subsequently, the simulation model and economic model are used in conjunction to conduct a sensitivity analysis for polymer flood design parameters, from which recommendations are provided for both the continued operation of the current field pilot and future polymer flood designs. The results demonstrate that a higher polymer concentration can be injected due to the development of fractures in the reservoir. The throughput rate should remain high without exceeding operating constraints. A calculated point-forward polymer utilization parameter demonstrates the decreasing efficiency of the polymer flood at later times in the pattern life. Future projects will benefit from starting polymer injection earlier in the pattern life. A pattern with tighter horizontal well spacing will observe a greater incremental benefit from polymer flooding.

Keith, Cody↗

DOE OSTI2022

Herpes simplex virus and rates of cognitive decline or whole brain atrophy in the Dominantly Inherited Alzheimer Network

Abstract Objective To investigate whether herpes simplex virus type 1 (HSV‐1) infection was associated with rates of cognitive decline or whole brain atrophy among individuals from the Dominantly Inherited Alzheimer Network (DIAN). Methods Among two subsets of the DIAN cohort (age range 19.6–66.6 years; median follow‐up 3.0 years) we examined (i) rate of cognitive decline ( N = 164) using change in mini‐mental state examination (MMSE) score, (ii) rate of whole brain atrophy ( N = 149), derived from serial MR imaging, calculated using the boundary shift integral (BSI) method. HSV‐1 antibodies were assayed in baseline sera collected from 2009–2015. Linear mixed‐effects models were used to compare outcomes by HSV‐1 seropositivity and high HSV‐1 IgG titres/IgM status. Results There was no association between baseline HSV‐1 seropositivity and rates of cognitive decline or whole brain atrophy. Having high HSV‐1 IgG titres/IgM was associated with a slightly greater decline in MMSE points per year (difference in slope − 0.365, 95% CI: −0.958 to −0.072), but not with rate of whole brain atrophy. Symptomatic mutation carriers declined fastest on both MMSE and BSI measures, however, this was not influenced by HSV‐1. Among asymptomatic mutation carriers, rates of decline on MMSE and BSI were slightly greater among those who were HSV‐1 seronegative. Among mutation‐negative individuals, no differences were seen by HSV‐1. Stratifying by APOE4 status yielded inconsistent results. Interpretation We found no evidence for a major role of HSV‐1, measured by serum antibodies, in cognitive decline or whole brain atrophy among individuals at high risk of early‐onset AD.

Warren‐Gash, Charlotte↗

DOE OSTI2026

Techno-Economic Analysis of Recycling Strategies for Catalyst and Acid During Catalytic Graphitization

With the aim of meeting the urgent demand for active anode materials (AAM) in energy storage systems, bio-based graphite (biographite) emerges as an affordable solution to de-risk the turbulent supply chain of critical minerals. Anode grade biographite requires high crystallinity and purity, which can be achieved by catalytic graphitization with iron, followed by acid washing. Therefore, a well-conceived process integration that recycles catalyst can be the starting point to commercialization. This study evaluates closed-loop catalyst recovery, and byproducts valorization scenarios through a technoeconomic framework to help understand the scale-up potential of biographite. For the acid washing, three reactors in series meet the required biographite purity at 99.95%. Iron and acid recovery can reduce material consumption and waste generation by ~95%, albeit at the expense of ~80% increase in capital costs. Recovery scenarios present similar capital and operational expenses, yielding minimum selling prices (MSP) near $6 kg-1 of biographite. Monte Carlo methodology reveals that feedstock price accounts for ~60% of MSP variance, followed by plant capacity ~20%. The likelihood of reaching a competitive profit margin of 30% in the U.S. AAM market sits at 85% average for recovery scenarios, and 103% when iron oxide is sold as byproduct. Additionally, an IRR >= 15% can be achieved for half of Monte Carlo simulations, representing promising early-stage results. Biographite production offers a strategic pathway to stabilize the anode market beyond China by integrating established technologies for a scalable, economically viable, and sustainable process. The role of catalyst recovery and byproducts utilization is critical for advancing the biomaterials industry.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Impact of temperature on light yield and pulse shape discrimination of polysiloxane-based organic scintillators formulated with commercial resins

This work investigates how increased temperature affects neutron/ discrimination and light yield (LY) in several different polysiloxane-based scintillators doped with either 9,9-dimethyl-2-phenylflourene (PhF) or 2,5-diphenyloxazole (PPO) as a primary fluorophore and 9,9-dimethyl-2,7-di((E)-styryl) fluorene (SFS) as the secondary fluorophore. The polysiloxane matrices were prepared from the commercial resins Wacker Lumisil 579 or Shin-Etsu KER-6000. Control scintillators were prepared from poly(vinyltoluene) (PVT), the industry standard matrix, as a reference point for LY and pulse shape discrimination (PSD) measurements. Samples with PhF and PPO dopant concentrations of 1 wt% and 5 wt% in the polysiloxanes and 3 wt% and 5 wt% in the PVT samples were tested at 20 °C, 35 °C, and 50 °C. In the polysiloxane samples, the KER-6000 resin outperformed the Wacker 579 and PhF proved to be a better dopant than PPO in both LY and PSD capabilities. Polysiloxane scintillators showed slight decreases in LY and increases in neutron/discrimination at increased temperatures, while PVT scintillators showed a similar LY decrease with little to no improvement in neutron/discrimination at increased temperatures. Altogether, polysiloxane scintillators may not require recalibration in applications where temperatures increase up to 50 °C.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Role of effective mass and long-range interactions in the band-gap renormalization of photoexcited semiconductors

Understanding how to control changes in the electronic structure and related dynamical renormalizations by external driving fields is the key for understanding ultrafast spectroscopy and applications in electronics. Here, we focus on the band gap's modulation by external electric fields and uncover the effect of band dispersion on the gap renormalization. We employ the Green's function formalism using the real-time Dyson expansion to account for dynamical correlations induced by photodoping. The many-body formalism captures the dynamics of systems with long-range interactions, carrier mobility, and variable electron and hole effective mass. We also demonstrate that mean-field simulations based on the Hartree-Fock Hamiltonian, which lacks dynamical correlations, yields a qualitatively incorrect picture of band-gap renormalization. We find the trend that increasing effective mass, thus decreasing mobility, leads to as much as a 6% enhancement in band-gap renormalization. Further, the renormalization is strongly dependent on the degree of photodoping. As the screening induced by free electrons and holes effectively reduces any long-range and interband interactions for highly excited systems, we show that there is a specific turnover point with a minimal band gap. Here, we further demonstrate that the optical gap renormalization follows the same trend though its magnitude is altered by the Moss-Burstein effect.

Approximation methods for many-body systems↗

DOE OSTI2024

Determination of Vibrational Motions Driving Photoinduced Electron Transfer Reactions in Molecular Crystals and Organic Thin Films

The objective of this research is to develop an understanding of how nuclear motions can be used to drive and control photo-induced charge transfer and singlet fission reactions in molecular crystals and thin films. By following the structural evolution of reacting molecules and nanostructures on the timescale of their nuclear motion, we will determine what interplay of nuclear coordinates is most efficient in driving electron transfers, a necessary first step in most photovoltaic and photocatalytic processes. We will identify which nuclear coordinates effectively promote desirable electron transfer processes, or ineffectively dissipate photon energy into unwanted thermal energy, thus guiding the design and implementation of molecular systems tailored for high efficiency processes. Specifically, we aim to identify which nuclear coordinates are responsible for driving electron transfer and singlet fission reactions at different points along the reaction coordinate, particularly in regimes which deviate from Marcus theory predictions. We will do so by investigating systems with electron transfer and singlet fission occurring from non-thermalized states due to strong donor-acceptor electronic coupling. First, we will prove that specific vibrational modes are responsible for charge transfer processes in molecular crystals. Secondly, we will investigate how vibrational coherences and specific nuclear motions can be used to drive high yield singlet fission processes. Finally, we will determine how complex film morphology affects long-range charge transport, a key limiting factor in our ability to make gains in efficiency.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Multi-mechanistic Strategies for Novel Solid Electrolytes with Superior Properties

Despite a wide range of solid electrolyte phases, most of them only exist at high temperatures. The challenge is to tailor the chemical compositions of solid electrolyte materials that yield high ionic conductivities and low activation energies at ambient temperature. This is crucial for the development of all-solid-state batteries that are both powerful and safe. Here, we report our recent works to meet this challenge by utilizing multiple mechanistic principles and clusters as the building blocks. We show that the atomic-level interactions that govern the fast-ion conduction can be optimized by incorporating polyanion dynamics, non-stoichiometry, point defects and strong ionic correlations. Specifically, two case studies of Li/Na solid electrolytes will be covered, including lithium solid electrolytes (SE) with record-high ionic conductivities at room temperature (over 100 mS/cm) and sodium SE with record-low activation energies (< 0.1 eV).

Fang, Hong↗

DOE OSTI2026

Dark Energy Survey Year 3 results: optimized $w$CDM simulation-based inference with weak lensing map-level hybrid statistics

We present cosmological constraints from the Dark Energy Survey Year 3 (DES Y3) weak lensing data using hierarchical hybrid statistics within a Bayesian simulation-based inference framework that is based on the Gower Street simulations. To maximize the precision of the inference, we have developed a new, information-theory based, data compression of the weak lensing maps to just seven highly informative summary statistics. The hybrid scheme exploits the high information content of the power spectrum, compressing both the power spectrum and neural-based summaries that are designed to extract further information. Our simulation-based approach enables principled forward modelling of all major sources of systematic uncertainty and survey properties into realistic mock observations, including the survey mask, photometric redshift uncertainties, intrinsic galaxy alignments, multiplicative shear calibration bias, source galaxy clustering, non-Gaussian shape noise, and non-linear structure formation. The summary statistics are then used in a Bayesian simulation-based inference pipeline. The inference is validated through coverage tests and checks for robustness against baryonic feedback. Assuming a $w$CDM cosmology, our analysis yields $S_8 = 0.808 \pm 0.017$, $Ω_{\rm m} = 0.325 \pm 0.024$, and $w < -0.766$ (marginalized posterior 68 per cent credible intervals). This rigorous combination of information theory, physics- and neural network-based extreme data compression, and principled Bayesian analysis improves the figure of merit for $(Ω_{\rm m}, S_8, w)$ by 60 per cent over the previous state-of-the-art, and by almost a factor of 3 over two-point analyses of the same data. They are the most precise joint constraints on $(Ω_{\rm m}, S_8, w)$ from weak gravitational lensing data alone of any survey to date. We intend to apply this analysis to the more recent DES Y6 data.

Williamson, J. [University Coll. London]↗

DOE OSTI2024

Influence of pump laser fluence on ultrafast myoglobin structural dynamics

High-intensity femtosecond pulses from an X-ray free-electron laser enable pump–probe experiments for the investigation of electronic and nuclear changes during light-induced reactions. On timescales ranging from femtoseconds to milliseconds and for a variety of biological systems, time-resolved serial femtosecond crystallography (TR-SFX) has provided detailed structural data for light-induced isomerization, breakage or formation of chemical bonds and electron transfer. However, all ultrafast TR-SFX studies to date have employed such high pump laser energies that nominally several photons were absorbed per chromophore. As multiphoton absorption may force the protein response into non-physiological pathways, it is of great concern whether this experimental approach allows valid conclusions to be drawn vis-à-vis biologically relevant single-photon-induced reactions. Here we describe ultrafast pump–probe SFX experiments on the photodissociation of carboxymyoglobin, showing that different pump laser fluences yield markedly different results. In particular, the dynamics of structural changes and observed indicators of the mechanistically important coherent oscillations of the Fe–CO bond distance (predicted by recent quantum wavepacket dynamics) are seen to depend strongly on pump laser energy, in line with quantum chemical analysis. Our results confirm both the feasibility and necessity of performing ultrafast TR-SFX pump–probe experiments in the linear photoexcitation regime. We consider this to be a starting point for reassessing both the design and the interpretation of ultrafast TR-SFX pump–probe experiments such that mechanistically relevant insight emerges.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

The enigmatic Galactic Center excess: Spurious point sources and signal mismodeling

The Galactic Center GeV excess (GCE) has garnered great interest as a possible signal of either dark matter annihilation or some novel astrophysical phenomenon, such as a new population of gamma-ray emitting pulsars. In a companion paper, we showed that in a 10° radius region of interest (ROI) surrounding the Galactic Center, apparent evidence for GCE point sources (PSs) from non-Poissonian template fitting (NPTF) is actually an artifact of unmodeled north-south asymmetry of the GCE. In this work, we develop a simplified analytic description of how signal mismodeling can drive an apparent preference for a PS population, and demonstrate how the behavior pointed out in the companion paper also appears in simpler simulated datasets that contain no PS signals at all. We explore the generality of this behavior in the real gamma-ray data, and discuss the implications for past and future studies using NPTF techniques. While the drop in PS preference once north-south asymmetry is included is not ubiquitous in larger ROIs, we show that any overly-rigid signal model is expected to yield a spurious PS signal that can appear very convincing: as well as apparent significance comparable to what one would expect from a true PS population, the signal can exhibit stability against a range of variations in the analysis, and a source count function that is very consistent with previous apparent NPTF-based detections of a GCE PS population. This contrasts with previously studied forms of systematic mismodeling which are unlikely to mimic a PS population in the same way. Finally, in the light of this observation, and its explicit realization in the region where the GCE is brightest, we argue that a dominantly smooth origin for the GCE is not in tension with existing NPTF analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Preparation of 1,3-Dihydroxyphenazine

The ability to effectively store energy produced by intermittent renewable sources is a critical challenge for chemists and materials scientists. Redox flow batteries (RFB), which generate current by the flow of electrons between dissolved redox active compounds in separate solutions, are envisioned as a method to store renewable energy at the electrical grid scale. The best known examples of RFBs are driven by redox active metal or main group complexes. Within the past decade, redox active organic molecules have begun to be used in the construction of RFBs with high cell potential and cycle stability, at economical price points. Of particular interest are substituted dihydroxy phenazines, a class of heterocycles, that have recently been used as an anolyte for aqueous organic RFBs. Recent work indicates that different regioisomers of dihydroxyphenazine show dramatically different solubility and stability under electrochemical cycling conditions. Of particular interest was 1,3-dihydroxyphenazine (1,3-DHP), which showed greater than 1.5 M solubility in 2M KOH and excellent electrochemical stability. Current methods of producing 1,3-DHP, however, are low yielding and cumbersome. In the article proposal that follows, we offer an improved method of producing 1,3-DHP at high purity and moderate yield. The method detailed below was used by the Materials Engineering Research Facility (MERF) at Argonne National Lab to deliver more than 1.5 kg of this compound for use in the construction of aqueous organic RFBs.

Dzwiniel, Trevor [Argonne National Laboratory (ANL↗

DOE OSTI2020

A Dynamic Reduction Network for Point Clouds

Classifying whole images is a classic problem in machine learning, and graph neural networks are a powerful methodology to learn highly irregular geometries. It is often the case that certain parts of a point cloud are more important than others when determining overall classification. On graph structures this started by pooling information at the end of convolutional filters, and has evolved to a variety of staged pooling techniques on static graphs. In this paper, a dynamic graph formulation of pooling is introduced that removes the need for predetermined graph structure. It achieves this by dynamically learning the most important relationships between data via an intermediate clustering. The network architecture yields interesting results considering representation size and efficiency. It also adapts easily to a large number of tasks from image classification to energy regression in high energy particle physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Engineering intricacies of implementing single-atom alloy catalysts for low-temperature electrocatalytic CO 2 reduction

Catalysts research for electrocatalytic CO 2 reduction reactions (CO 2 R) has undergone rapid growth in the last decade. Single-atom alloy catalysts (SAAs) featuring atomically dispersed metal dopants on host metal surfaces have shown promises in boosting CO 2 R yield by optimizing the structure and synergy of the catalytic metals at the atomic scale. Despite the exciting development of SAAs for CO 2 R in fundamental science, dedicated studies for its engineering implementation have been absent. We use this perspective to discuss our non-exhaustive engineering considerations for implementing SAAs for CO 2 R. Here, the perspective starts with a brief overview of the current research status for SAAs in CO 2 R, followed by focal points on structure uncertainties associated with catalyst manufacturing, catalyst layer degradation during reaction, and possibilities for SAAs to mitigate the salt precipitation issue at the device level. We hope our opinions will engage increasing attention toward the engineering catalysis research for applying SAAs to CO 2 R at scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

New heat flux model for non-axisymmetric divertor infrared structures

A convective heat flux model for perturbed plasmas, based on guiding center ion drift in vacuum elds (A. Wingen, et al., Phys. Plasmas 21 (2014) 012509), has been updated. The old model only considered ion heat flux, while here also electron heat flux is included. The updated model predicts divertor heat flux distributions in non-axisymmetric (3D) plasmas with applied Resonant Magnetic Perturbation (RMP) fields, and includes electric scalar potentials. It is found that a radial electric field in the near Scrape-o Layer (SOL) can considerably shift the footprints toroidally, leading to a smearing out eff ect of the incident heat flux, while a simple model for sheath potential has little impact on footprints. Various approaches to model electron heat flux are studied. A convective electron model, based on collisionless free streaming, is found to yield the best agreement with measurements, while a conductive model requires a at temperature gradient inside lobes to yield acceptable peak heat ux values. A heuristic heat flux layer approach, based on a fixed layer width also requires a limited heat flux inside the last closed flux surface (LCFS); by selecting various locations of the LCFS, the results of the conductive or convective model can be recovered respectively. The sum of ion and electron heat fluxes, both obtained by the convective model, is compared to experimental data for multiple time slices in DIII-D. Strike point splitting is observed with peak heat fluxes and layer widths that compare well to infrared camera (IR) measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Speed of sound in methane under conditions of planetary interiors

We present direct observations of acoustic waves in warm dense matter. We analyze wave-number- and energy-resolved x-ray spectra taken from warm dense methane created by laser heating a cryogenic liquid jet. X-ray diffraction and inelastic free-electron scattering yield sample conditions of 0.3 ± 0.1 eV and 0.8 ± 0.1 g/ cm − 3 , corresponding to a pressure of ∼ 13 GPa. Inelastic x-ray scattering was used to observe the collective oscillations of the ions. With a highly improved energy resolution of ∼ 50 meV, we could clearly distinguish the Brillouin peaks from the quasielastic Rayleigh feature. Data at different wave numbers were utilized to derive a sound speed of 5.9 ± 0.5 km/s, marking a high-temperature data point for methane and demonstrating consistency with Birch's law in this parameter regime. Published by the American Physical Society 2024

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Switchgrass ( Panicum virgatum L.) cultivars have similar impacts on soil carbon and nitrogen stocks and microbial function

Abstract Switchgrass ( Panicum virgatum L.) production for biofuel has the potential to produce reasonable yields on lands not suited for conventional agriculture. We assessed nine switchgrass cultivars representing lowland and upland ecotypes grown for 11 years at a site in the upper Midwest USA for belowground differences in soil carbon and nitrogen stocks, soil organic matter fractions, and standing root biomass to 1 m depth. We also compared potential nitrogen mineralization and carbon substrate use through community‐level physiological profiling in surface soils (0–10 cm depth). Average yields and standing root biomass differed among cultivars and between ecotypes, but we found no significant cultivar‐related impacts on soil carbon and nitrogen stocks, on the distribution of particulate and mineral‐associated soil organic matter fractions, nor on potential nitrogen mineralization or microbial community‐level physiological profiles. That these traits did not differ among cultivars suggests that soil carbon and nitrogen gains under switchgrass are likely to be robust with respect to cultivar differences, and to this point not much affected by breeding efforts.

Agriculture↗

DOE OSTI2024

Fast, Nondestructive and Precise Biomass Measurements Are Possible Using Lidar-Based Convex Hull and Voxelization Algorithms

Light detection and ranging (lidar) scanning tools are available that can make rapid digital estimations of biomass. Voxelization and convex hull are two algorithms used to calculate the volume of the scanned plant canopy, which is correlated with biomass, often the primary trait of interest. Voxelization splits the scans into regular-sized cubes, or voxels, whereas the convex hull algorithm creates a polygon mesh around the outermost points of the point cloud and calculates the volume within that mesh. In this study, digital estimates of biomass were correlated against hand-harvested biomass for field-grown corn, broom corn, and energy sorghum. Voxelization (r = 0.92) and convex hull (r = 0.95) both correlated well with plant dry biomass. Lidar data were also collected in a large breeding trial with nearly 900 genotypes of energy sorghum. In contrast to the manual harvest studies, digital biomass estimations correlated poorly with yield collected from a forage harvester for both voxel count (r = 0.32) and convex hull volume (r = 0.39). However, further analysis showed that the coefficient of variation (CV, a measure of variability) for harvester-based estimates of biomass was greater than the CV of the voxel and convex-hull-based biomass estimates, indicating that poor correlation was due to harvester imprecision, not digital estimations. Overall, results indicate that the lidar-based digital biomass estimates presented here are comparable or more precise than current approaches.

Environmental Sciences & Ecology↗

DOE OSTI2025

Hydrogen Bond Benchmark: Focal‐Point Analysis and Assessment of DFT Functionals

We performed a hierarchical, convergent ab initio benchmark study and systematically analyzed the performance of density functional approximations for describing hydrogen bonds in small neutral, cationic, and anionic complexes, as well as in larger systems involving amide, urea, deltamide, and squaramide moieties. Focal point analyses (FPA), extrapolating to the ab initio limit, were carried out using correlated wave function methods up to CCSDT(Q) for the small complexes and CCSD(T) for the larger systems, together with correlation-consistent Gaussian basis sets up to the complete basis set limit. Optimized geometries and vibrational frequencies were obtained at the CCSD(T) level. The resulting FPA hydrogen-bond energies converge within a few tenths of a kcal mol −1 . These reference data were used to evaluate 60 density functionals (including 12 dispersion-corrected), spanning the local-density approximation (LDA), generalized gradient approximations (GGAs), meta-GGAs, hybrids, meta-hybrids, double-hybrids, and range-separated hybrids. Overall, the meta-hybrid M06-2X provides the best performance for both hydrogen bond energies and geometries, while the dispersion-corrected GGAs BLYP-D3(BJ) and BLYP-D4 also yield accurate hydrogen-bond data and can serve as cost-effective options for studying large and complex systems.

coupled cluster theory↗