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DOE OSTI2025

Analyzing line-of-sight selection biases in galaxy-scale strong lensing with external convergence and shear

The upcoming Vera Rubin Observatory Legacy Survey of Space and Time (LSST) will dramatically increase the number of strong gravitational lensing systems, requiring precise modeling of line-of-sight (LOS) effects to mitigate biases in lensing observations and cosmological inferences. We develop a method to construct joint distributions of external convergence (κ ext ) and shear (γ ext ) for strong lensing LOS by aggregating large-scale structure simulations with high-resolution halo renderings and non-linear correction. Our approach captures both smooth background matter and perturbations from halos, enabling accurate modeling of LOS effects. Here, we apply non-linear LOS corrections to κ ext and γ ext that address the non-additive lensing effects caused by objects along the LOS in strong lensing. We find that, with a minimum image separation of 1.0'', non-linear LOS correction due to the presence of a dominant deflector slightly increases the ratio of quadruple to double lenses; this non-linear LOS correction also introduces systematic biases of ∼ 0.1% for galaxy-AGN lens in the inferred Hubble constant (H 0 ) if not accounted for. We also observe a 0.66% bias for galaxy-galaxy lenses on H 0 , and even larger biases 1.02% for galaxy-AGN systems if LOS effects are not accounted for. These results highlight the importance of LOS for precision cosmology. The publicly available code and datasets provide tools for incorporating LOS effects in future analyses.

Hubble constant↗

DOE OSTI2025

Optimizing Alabama’s CO 2 Storage in Shelby County (Project OASIS): Task 4.0 Deliverable – Geologic Analysis Report

Project OASIS (Optimizing Alabama’s CO 2 Storage in Shelby County) is a geologic and reservoir characterization study designed to evaluate deep saline formations for potential long-term carbon dioxide (CO 2 ) storage in central Alabama near the National Carbon Capture Center (NCCC) and Alabama Power’s Plant Gaston. The project centers on the Cambro-Ordovician Knox Group and underlying strata such as the Conasauga and Rome Formations, which were investigated through the drilling of two stratigraphic test wells to obtain electronic well logs, core, and sidewall core plugs. These data provide direct measurements of porosity, permeability, and lithologic variability critical for reservoir characterization. Complementing the well program, a limited 2D seismic survey was acquired to help select the site for Westover #2, and a more regional Seismic Exchange (SEI) seismic survey was licensed and interpreted to define structural and stratigraphic frameworks in a new Static Earth Model (SEM), map reservoir continuity, and identify potential sealing intervals. Integrated with geologic and reservoir modeling, these datasets form the basis for evaluating storage capacity, injectivity, and containment.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Effect of modeled time horizon on quantifying the need for long-duration storage

Long-Duration Energy Storage (LDES) has gained interest due to its key role in attaining a decarbonized, low-cost, and stable grid driven by variable renewable electricity (VRE). Currently, there is a wide range of LDES technologies being developed to provide electricity with 8+ hours of consecutive discharge. However, current capacity expansion models used in long-term planning processes rarely consider low cost LDES as a candidate technology. If they do, the storage balancing horizon (SBH) of the model usually only considers non-consecutive 1-day periods that do not capture the potential of LDES to shift energy across multiple days or even seasons. Addressing these limitations in existing models, this work explores the ways in which the optimal energy storage changes when increasing the number of consecutive days in the SBH and how these changes will impact planners who are determining the future roles of energy storage. Our analysis uses SWITCH, an open-source capacity expansion model with a high spatial resolution for the entire Western Electricity Coordinating Council (WECC) in a zero-carbon scenario in 2050. We find that the number of consecutive days in the SBH changes both the total selected power and energy capacity of LDES when storage energy and power capacity overnight costs are $\$$13 USD/kWh (or less) and $113 USD/kW, respectively. We also find that the amount of required energy in storage to drive a future VRE-driven WECC grid ranges from 2.5 TWh to 16.0 TWh depending on the length of the SBH. The optimal storage duration (energy to power ratio) we obtain ranges from 10 h to 620 h among all the scenarios. Furthermore, depending on the storage cost assumption, we observe different charge/discharge patterns when varying the length of the SBH. Given our results, we anticipate that as more LDES technologies become commercially available, it will be critical to increase the length of the SBH to fully capture the benefits of LDES assets in long-term planning processes of high VRE-driven grids.

42 ENGINEERING↗

DOE OSTI2020

Quantitative assessment of eddy viscosity rans models for turbulent mixed convection in a differentially heated plane channel

Turbulent mixed convection between two vertical, infinite parallel plates at different temperatures is studied using various two-equation turbulence models. The numerical simulations are performed at a turbulent Reynolds number of Re τ = 150 and a Grashof number of Gr = 9.6 × 10 5 . Comparisons are made against the highly trusted DNS results. Consistent with the DNS approach, the current simulations are performed using constant properties and the Boussinesq approximation to predict the influence of buoyancy. Previous studies have provided assessments of two-equation turbulence models for various scenarios, but often rely on a qualitative “eye” test in order to determine the most appropriate model to predict a given flow. This study aims to provide a new form of quantitative assessment that accounts for both the physics captured by the turbulence model as well as the magnitude of the system response quantities (SRQ) using a modified symmetric mean absolute percent error (SMAPE) method. This method is designed to be approachable to researchers at any level and can be applied to system response quantities from multiple research fields. Uncertainty quantification is also performed to determine the discretization error for each turbulence model. Recommendations are made as to which turbulence models best capture the physics – hydrodynamically and thermally – using both local and global validation metrics. Lastly, a sensitivity analysis is performed on the damping functions used in the most accurate models. This underpins the potential of model developments and adjustments most worth pursuing for buoyant flows. Finally, this framework provides a more physics-based comparative analysis of the selected turbulence models.

42 ENGINEERING↗

DOE OSTI2025

Liquid Phase Modeling in Porous Media: Adsorption of Methanol and Ethanol in H-MFI in Condensed Water

Zeolites are used in the chemical and separation industries for their exceptional selectivity, adsorption capacity, regenerability, and stability in gas and liquid phase processing. Here, we developed an explicit solvation method for predicting solvent/condensed phase effects on adsorption free energies in microporous media such as zeolites based on the hybrid quantum mechanical/molecular mechanical free energy perturbation (QM/MM-FEP) technique. Our explicit solvation method for zeolite systems, called eSZS, aims to capture site-specific interactions during the adsorption process at the Brønsted acid sites of H-MFI zeolite while still considering the diverse configuration space of the solvent molecules. This strategy is ideal for chemical reactions or adsorbates that interact with the microporous medium in few distinct adsorbate/transition state configurations, i.e., the harmonic or similar approximations are acceptable for the adsorbate/transition state while such approximations break down for the solvent molecules that require extensive configuration space sampling. In this way, our approach effectively overcomes the limitations of implicit solvation models and classical force field methods for describing solvation effects on chemical reactions within porous materials such as zeolites. Specifically, in this study, we investigated various aspects of our hybrid QM/MM approach, including QM cluster size dependencies in a periodic electrostatically embedded cluster model (PEECM), rules for link atoms at the QM/MM boundary, and functional and basis set considerations for converged and reasonably accurate gas and aqueous phase methanol and ethanol adsorption free energy predictions in H-MFI. For gas phase adsorption of methanol and ethanol in H-MFI at a Brønsted acid site in T12 position, we compute adsorption free energies at 298 K of −0.61 and −0.75 eV, respectively, using a PEECM containing 50 Si and 1 Al atom with ωB97x-D/def2-TZVP level of theory. For solvent effect calculations, we sample the aqueous phase using grand canonical Monte Carlo (GCMC) simulations to (1) obtain a mean field of electrostatic interactions in the reaction system and (2) perform a rigorous free energy perturbation calculation. Similar to the experimentally and computationally observed endergonic solvation effects observed for hydrocarbon adsorption on metal surfaces, we also observe that a condensed aqueous environment destabilizes methanol and ethanol at these acid sites in H-MFI at 298 K. Specifically, the computed solvation free energies of adsorption (ΔΔG solv ) for methanol and ethanol are +0.44 and +0.54 eV, respectively. From this study, it is evident that adsorbates (methanol and ethanol) are competing with water for adsorption space inside the H-MFI zeolite, leading to an endergonic solvation effect. Here, we expect that the endergonic, aqueous solvent effect during adsorption in microporous zeolites is highly tunable by changing the pore size and hydrophobicity of the microporous material as this will affect the water density inside the pore structure.

Adsorption↗

DOE OSTI2024

Harnessing genetic engineering to drive economic bioproduct production in algae

Our reliance on agriculture for sustenance, healthcare, and resources has been essential since the dawn of civilization. However, traditional agricultural practices are no longer adequate to meet the demands of a burgeoning population amidst climate-driven agricultural challenges. Microalgae emerge as a beacon of hope, offering a sustainable and renewable source of food, animal feed, and energy. Their rapid growth rates, adaptability to non-arable land and non-potable water, and diverse bioproduct range, encompassing biofuels and nutraceuticals, position them as a cornerstone of future resource management. Furthermore, microalgae’s ability to capture carbon aligns with environmental conservation goals. While microalgae offers significant benefits, obstacles in cost-effective biomass production persist, which curtails broader application. This review examines microalgae compared to other host platforms, highlighting current innovative approaches aimed at overcoming existing barriers. These approaches include a range of techniques, from gene editing, synthetic promoters, and mutagenesis to selective breeding and metabolic engineering through transcription factors.

09 BIOMASS FUELS↗

DOE OSTI2021

Path-synchronous performance monitoring of interconnection networks based on source code attribution

Examples disclosed herein relate to path-synchronous performance monitoring of an interconnection network based on source code attribution. A processing node in the interconnection network has a profiler module to select a network transaction to be monitored, determine a source code attribution associated with the network transaction to be monitored, and issue a network command to execute the network transaction to be monitored. A logger module creates, in a buffer, a node temporal log associated with the network transaction and the network command. A drainer module periodically captures the node temporal log. The processing node has a network interface controller to receive the network command and mark a packet generated for the network command to be temporally tracked and attributed back to the source code attribution at each hop of the interconnection network traversed by the marked packet.

Chabbi, Milind M.↗

DOE OSTI2022

Proposed Material Properties, Allowable Stresses, and Design Curves of Diffusion Bonded Alloy 800H for the ASME Code Section III Division 5

Abstract Increased interest in compact heat exchangers (CHXs) to serve as intermediate heat exchangers of very high temperature reactors resulted in significant research and development on their design, analysis, and construction. Printed circuit heat exchangers are a type of CHXs with high thermal efficiency and compactness achieved through diffusion bonding a stack of etched plates with millimeter scaled channels. The diffusion bonding process changes the microstructural and mechanical properties of the wrought metal plates. The current nonnuclear design code ASME section VIII, division 1 captures the material property change through a “joint efficiency factor.” However, the current nuclear design code ASME section III, division 5 does not address or support the diffusion bonded material properties. Hence, there is a need to develop allowable stresses, isochronous curves, and fatigue life curves for various diffusion bonded alloys. In this study, Alloy 800H material was selected to establish the diffusion bonded material properties under tension, creep, fatigue, and creep-fatigue loads at elevated temperatures in the range 550–760 °C. A set of tests on diffusion bonded Alloy 800H (DB 800H) were performed and the acquired data are used in developing allowable stresses Sy, Su, Sr, Sm, St, Smt, So, isochronous curves and fatigue life curves according to the ASME section III, division 5 requirements. This paper also presents detailed procedures used in developing the ASME code section III division 5 design provisions for diffusion bonded Alloy 800H.

Engineering↗

DOE OSTI2025

Search for dark matter from the center of the Earth with 10 years of IceCube data

The nature of dark matter remains unresolved in fundamental physics. Weakly Interacting Massive Particles (WIMPs), which could explain the nature of dark matter, can be captured by celestial bodies like the Sun or Earth, leading to enhanced self-annihilation into Standard Model particles including neutrinos detectable by neutrino telescopes such as the IceCube Neutrino Observatory. This article presents a search for muon neutrinos from the center of the Earth performed with 10 years of IceCube data using a track-like event selection. We considered a number of WIMP annihilation channels (χχ→τ+τ-$$\chi \chi \rightarrow \tau ^+\tau ^-$$/W+W-$$W^+W^-$$/bb¯$$b\bar{b}$$) and masses ranging from 10 GeV to 10 TeV. No significant excess over background due to a dark matter signal was found while the most significant result corresponds to the annihilation channel χχ→bb¯$$\chi \chi \rightarrow b\bar{b}$$ for the mass mχ=250$$m_{\chi }=250$$ GeV with a post-trial significance of 1.06σ$$1.06\sigma $$. Our results are competitive with previous such searches and direct detection experiments. Our upper limits on the spin-independent WIMP scattering are world-leading among neutrino telescopes for WIMP masses mχ>100$$m_{\chi }>100$$ GeV.

Abbasi, R↗

DOE OSTI2020

Concurrent Relaxation through Accelerated Deep Learning

CRADL captures performance metrics of machine learning algorithms operating on mesh data from multiphysics codes This proxy application is a tool to explore scalability of inference on HPC platforms, and also gather performance metrics for inference on new machine learning specific hardware. CRADL is designed to give users as fine a control as possible over an inference simulation. Users may select the number of cycles, amount of data, and batch size to pass to the accelerator of choice. Additionally the user may select a number of performance optimization libraries and flags. CRADL comes packaged with a repository of anonymized multi-physics simulation data, as well as a pretrained model for inference. The code allows a user to load their own pre-trained model and data if they wish. The code can operate in multiple parallelization schemes, with performance enhancing options such as half-precision libraries, PyTorch benchmarking, and pinned memory with non-blocking data transfers.

Zieb, KristoferJ.↗

DOE OSTI2023

Indoor Occupancy Sensing via Networked Nodes (2012–2022): A Review

In the past decade, different sensing mechanisms and algorithms have been developed to detect or estimate indoor occupancy. One of the most recent advancements is using networked sensor nodes to create a more comprehensive occupancy detection system where multiple sensors can identify human presence within more expansive areas while delivering enhanced accuracy compared to a system that relies on stand-alone sensor nodes. The present work reviews the studies from 2012 to 2022 that use networked sensor nodes to detect indoor occupancy, focusing on PIR-based sensors. Methods are compared based on pivotal ADPs that play a significant role in selecting an occupancy detection system for applications such as Health and Safety or occupant comfort. These parameters include accuracy, information requirement, maximum sensor failure and minimum observation rate, and feasible detection area. We briefly describe the overview of occupancy detection criteria used by each study and introduce a metric called “sensor node deployment density” through our analysis. This metric captures the strength of network-level data filtering and fusion algorithms found in the literature. It is hinged on the fact that a robust occupancy estimation algorithm requires a minimal number of nodes to estimate occupancy. This review only focuses on the occupancy estimation models for networked sensor nodes. It thus provides a standardized insight into networked nodes’ occupancy sensing pipelines, which employ data fusion strategies, network-level machine learning algorithms, and occupancy estimation algorithms. This review thus helps determine the suitability of the reviewed methods to a standard set of application areas by analyzing their gaps.

Emad-Ud-Din, Muhammad (ORCID:0000000279515538)↗

DOE OSTI2020

Computing water flow through complex landscapes – Part 2: Finding hierarchies in depressions and morphological segmentations

Depressions – inwardly draining regions of digital elevation models – present difficulties for terrain analysis and hydrological modeling. Analogous “depressions” also arise in image processing and morphological segmentation, where they may represent noise, features of interest, or both. Here we provide a new data structure – the depression hierarchy – that captures the full topologic and topographic complexity of depressions in a region. We treat depressions as networks in a way that is analogous to surface-water flow paths, in which individual sub-depressions merge together to form meta-depressions in a process that continues until they begin to drain externally. This hierarchy can be used to selectively fill or breach depressions or to accelerate dynamic models of hydrological flow. Complete, well-commented, open-source code and correctness tests are available on GitHub and Zenodo.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Understanding Gas Solubility of Pure Component and Binary Mixtures within Multivalent Ionic Liquids from Molecular Simulations

Understanding the molecular-level solubility of CO 2 and its mixtures is essential to the progress of gas treating technologies. Herein, we use grand canonical Monte Carlo simulations to study the single component gas absorption of SO 2 , N 2 , CH 4 , and H 2 , and binary mixtures of CO 2 /SO 2 , CO 2 /N 2 , CO 2 /CH 4 , and CO 2 /H 2 of varying mole fractions within multivalent ionic liquids (ILs). Our results highlight the importance of the free volume effect and the anion effect when interpreting the absorption behavior of these mixtures, similar to the behavior of CO 2 found in our previous study. The deviation of the gas solubility between the pure component absorption versus the binary absorption, as well as the solubility selectivity, highlight the importance of the relative affinity of gas species within a mixture to the different anions. Further, the absorption selectivity within a specific IL system can be predicted based on the relative gas affinity to the anion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Synthesis, Isolation, and Study of Heterobimetallic Uranyl Crown Ether Complexes

Although crown ethers can selectively bind many metal cations, little is known regarding the solution properties of crown ether complexes of the uranyl dication, UO 2 2+ . Here, in this work, the synthesis and characterization of isolable complexes in which the uranyl dication is bound in an 18-crown-6-like moiety are reported. A tailored macrocyclic ligand, templated with a Pt(II) center, captures UO 2 2+ in the crown moiety, as demonstrated by results from single-crystal X-ray diffraction analysis. The U(V) oxidation state becomes accessible at a quite positive potential (E 1/2 ) of –0.18 V vs Fc +/0 upon complexation, representing the most positive U VI /U V potential yet reported for the UO 2 n+ core. Isolation and characterization of the U(V) form of the crown complex are also reported here; there are no prior reports of reduced uranyl crown ether complexes, but U(V) is clearly stabilized by crown chelation. Joint computational studies show that the electronic structure of the U(V) form results in significant weakening of U–O oxo bonding despite the quite positive reduction potential at which this species can be accessed, underscoring that crown-ligated uranyl species could demonstrate unique reactivity under only modestly reducing conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Carbon-negative hydrogen: aqueous phase reforming (APR) of glycerol over NiPt bimetallic catalyst coupled with CO 2 sequestration

Herein we report the production of high-pressure (19.3 bar), carbon-negative hydrogen (H 2 ) from glycerol with a purity of 98.2 mol% H 2 , 1.8 mol% light hydrocarbons (mainly methane), and 400 ppm of CO. Aqueous phase reforming (APR) of 10 wt% glycerol solution was studied with a series of NiPt alumina bimetallic catalysts supported on alumina. The Ni 8 Pt 1 -450 catalyst had the highest hydrogen selectivity (95.6%) and the lowest alkanes selectivity (3.7%) of the tested catalysts. The hydrogen selectivity decreased in the order of Ni 8 Pt 1 -450 > Ni 8 Pt 1 -260 > Ni 1 Pt 1 -260 > Pt-260. The CO 2 was sequestered with CaO adsorbent which formed CaCO 3 . We measured the adsorption capacity of the CaO adsorbent at different temperatures. Life cycle analysis showed that the APR of glycerol coupled with CO 2 capture has net negative CO 2 equivalent greenhouse gas emissions. The CO 2 emissions are –9.9 kg CO 2 eq./kg H 2 and –50.1 kg CO 2 eq./kg H 2 when grid electricity and renewable electricity are used, respectively, and the CO 2 is allocated respectively to the mass of products produced. The cost of this H 2 (denoted as “green-emerald”) was estimated to be 2.4 USD per kg H 2 when grid electricity is used and 2.7 USD per kg H 2 when using renewable electricity. The cost of glycerol has the highest contribution of 1.71 USD per kg H 2 . As a result, participation in the carbon credit markets can further decrease the price of the produced H 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

APS-DPP Distinguished Lecturer in Plasma Physics (DLPP) Program (Final Technical Report)

The final WVU-DLPP-project year has been a transition year on multiple fronts for the DLPP program. The first is a transition from the mode of operations adopted during the COVID-19 pandemic and the second is leadership for the program. During the pandemic, the lecture series went to a virtual format to maintain interactions between our distinguished lecturers and the community of small college and University plasma physics programs with an emphasis on underrepresented groups. Prof. John Foster was especially active with his invited lectures in the remote modality of the DLPPseries. While efforts included zoom calls for speakers to interact with students in addition to the seminar, this approach is much less impactful than face-to-face interactions. As we refresh the group of speakers, the lectures will move back to in person visits. We still retain the virtual option for our lecturers to cope with circumstances and remaining health concerns for individual. We have selected a new cohort of distinguished lecturers. A flyer was sent to a list of college and universities to advertise the DLPP speaker-visit opportunity. We have also drafted a thank you letter to the previous cohort who sustained the program through the pandemic. The other transition is the change in leadership, after the selection of the 2023 DLPPcohort, from Dr. Koepke who has been a staunch champion for the program and done a great job growing its presence, to Dr. Kline the co-chair. Dr. Koepke has been transferring his knowledge and providing excellent guidance in this transition. Over the past year, a best practices document was written as a means to capture not only the core program values, but create a living document that can maintain a continual transfer of information to subsequent leader for the program.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Investigation of the Effect of Framework Flexibility on Adsorption in SIFSIX-3-Cu using a Machine-Learned Force Field

Metal-organic frameworks (MOFs) are a promising class of adsorbents. The performance of MOF sorbents relies on high selectivity and low regeneration energy. This work focuses on the use of machine learned force fields (MLFFs) to model adsorption in a flexible MOF, SIFSIX-3-Cu. A DeePMD-based MLFF was trained to reproduce DFT (PBE+D3) energies, forces, and stresses, using an iterative sampling scheme combining sampling based on molecular dynamics, Monte Carlo, and geometry optimization to capture both attractive and repulsive regions of the potential energy surface. Flexibility of the MOF was explicitly included in this model. Hybrid Monte Carlo/molecular dynamics (MC/MD) simulations using the MLFF predicted adsorption isotherms in good agreement with experimental data for a range of pressures (40 Pa – 104 Pa) in contrast to rigid models, which overpredict CO2 adsorption at low pressures. The improvement was the result of a description of the variability of fluorine-fluorine diagonal distances at adsorption sites. This detailed description of flexibility afforded by the MLFF resulted in more accurate predictions adsorption isotherms when compared to the experimentally measured values. These results underscore the importance of including framework flexibility when modeling adsorption phenomena in MOFs, particularly for low pressure applications and provide a robust procedure for training MLFF models for MOFs.

Atomistic Simulation↗

DOE OSTI2022

Optimizing the fuel efficiency of an opposed piston engine for electric power generation

This paper investigates the optimal crankshaft motion for an opposed piston (OP) engine in a novel hybrid architecture to maximize fuel efficiency. The OP engine was selected for this work due to its inherent thermodynamic benefits and the balanced nature of the engine which can achieve downsizing through reducing the number of cylinders rather than the individual cylinder volume. The typical geartrain required on an OP engine was exchanged for two electric motors, reducing friction loss and decoupling the crankshafts. Using the motors to control the crankshaft motion profiles, this architecture introduces capabilities to dynamically vary compression ratio, combustion volume, and scavenging dynamics. To leverage these opportunities, an optimization scheme was developed utilizing nonlinear optimization of a 0-D model to compute the crankshaft motion profile that maximizes the work generated by the system. This optimization was then iteratively coupled with a high fidelity model which supplies the cylinder flow boundary conditions. This iterative approach reduces the model complexity used in the optimal control problem (OCP) while capturing the gas exchange dynamics critical to the 2-stroke cycle of the OP engine. By using the rate of change of motor torque as the input to the OCP, the torque fluctuation in a single cycle can be limited to ensure tracking feasibility. The results show crankshaft velocity slows during the compression stroke and conversely accelerates during the expansion stroke, reducing the peak motor torque required for control and thus reducing the motor losses. The extended residence time at top dead center, however, leads to an increase in heat transfer, illustrating the trade-off between the work extraction efficiency and the indicated engine efficiency.

Engineering↗