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DOE OSTI2023

Antireflective Multi‐Dielectric Metasurfaces Operating in the Visible

Abstract As increasingly more demanding photonics applications are brought on‐chip, more complex design solutions are employed to deliver enhanced performance: e.g., meta‐molecules, inverse‐designed freeform structures, and multilayer metasurfaces. Instead, this study introduces anti‐reflective metasurfaces fabricated in a single nanolithography step that follows deposition of multiple dielectrics onto a substrate. Anti‐reflective metasurfaces offer fundamentally better transmission efficiencies compared to conventional equivalents. Conventional and anti‐reflective metalenses, both fabricated in the Ta 2 O 5 /SiO 2 material platform for 461 nm operation, show an improvement in focusing efficiencies from ≈ 55% to ≈ 90% at low numerical apertures and from ≈ 35% to ≈ 65% at high numerical apertures. Simulations of ideal and imperfect metalenses indicate that anti‐reflective metasurfaces not only improve transmission at the design library level, but also reduce spurious diffraction and protect against higher‐order scattering.

Optics↗

DOE OSTI2025

Deep reinforcement learning control for co-optimizing energy consumption, thermal comfort, and indoor air quality in an office building

With the recent demand for decarbonization and energy efficiency, advanced HVAC control using Deep Reinforcement Learning (DRL) becomes a promising solution. Due to its flexible structures, DRL has been successful in energy reduction for many HVAC systems. However, only a few researches applied DRL agents to manage the entire central HVAC system and control multiple components in both the water loop and the air loop, owing to its complex system structures. Moreover, those researches have not extended their applications by incorporating the indoor air quality, especially both CO2 and PM2.5concentrations, on top of energy saving and thermal comfort, as achieving those objectives simultaneously can cause multiple control conflicts. What's more, DRL agents are usually trained on the simulation environment before deployment, so another challenge is to develop an accurate but relatively simple simulator. Therefore, we propose a DRL algorithm for a central HVAC system to co-optimize energy consumption, thermal comfort, indoor CO2 level, and indoor PM2.5 level in an office building. To train the controller, we also developed a hybrid simulator that decoupled the complex system into multiple simulation models, which are calibrated separately using laboratory test data. The hybrid simulator combined the dynamics of the HVAC system, the building envelope, as well as moisture, CO2, and particulate matter transfer. Three control algorithms (rule-based, MPC, and DRL) are developed, and their performances are evaluated on the hybrid simulator environment with a realistic scenario (i.e., with stochastic noises). The test results showed that, the DRL controller can save 21.4 % of energy compared to a rule-based controller, and has improved thermal comfort, reduced indoor CO2 concentration. The MPC controller showed an 18.6 % energy saving compared to the DRL controller, mainly due to savings from comfort and indoor air quality boundary violations caused by unmeasured disturbances, and it also highlights computational challenges in real-time control due to non-linear optimization. Finally, we provide the practical considerations for designing and implementing the DRL and MPC controllers based on their respective pros and cons.

Guo, Fangzhou↗

DOE OSTI2020

Biosystems Design by Machine Learning

Biosystems such as enzymes, pathways, and whole cells have been increasingly explored for biotechnological applications. Yet, the intricate connectivity and complexity of biosystems pose a major hurdle in designing biosystems with desired features. As -omics and other high throughput technologies have been rapidly developed, the promise of applying machine learning (ML) techniques in biosystems design has started to become a reality. ML models enable the identification of patterns within complicated biological data across multiple scales of analysis and can augment biosystems design applications by predicting new candidates for optimized performance. ML is being used at every stage of biosystems design to help find non-obvious engineering solutions with fewer design iterations. In this review, we first describe commonly used models and modeling paradigms within ML. We then discuss some applications of these models that have already shown success in biotechnological applications. Moreover, we discuss successful applications at all scales of biosystems design, including nucleic acids, genetic circuits, proteins, pathways, genomes, and bioprocess. Lastly, we discuss some limitations of these methods and potential solutions as well as prospects of the combination of ML and biosystems design.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Low cost and massively parallel force spectroscopy with fluid loading on a chip

Current approaches for single molecule force spectroscopy are typically constrained by low throughput and high instrumentation cost. Herein, a low-cost, high throughput technique is demonstrated using microfluidics for multiplexed mechanical manipulation of up to ~4000 individual molecules via molecular fluid loading on-a-chip (FLO-Chip). The FLO-Chip consists of serially connected microchannels with varying width, allowing for simultaneous testing at multiple loading rates. Molecular force measurements are demonstrated by dissociating Biotin-Streptavidin and Digoxigenin-AntiDigoxigenin interactions along with unzipping of double stranded DNA of varying sequence under different dynamic loading rates and solution conditions. Rupture force results under varying loading rates and solution conditions are in good agreement with prior studies, verifying a versatile approach for single molecule biophysics and molecular mechanobiology. FLO-Chip enables straightforward, rapid, low-cost, and portable mechanical testing of single molecules that can be implemented on a wide range of microscopes to broaden access and may enable new applications of molecular force spectroscopy.

42 ENGINEERING↗

DOE OSTI2023

Generalized Mercier stability criterion for stellarators

The Mercier criterion is a well-known stability criterion for tokamaks. It is derived from a 2 × 2 matrix eigenvalue problem arising from the expansion of resonant solutions about a singular surface where m−nq=0, with m and n being the poloidal and toroidal mode numbers, respectively, and q being the safety factor. The stability criterion is that the eigenvalues must be real, otherwise, the solution oscillates, violating the Newcomb crossing criterion. Because of the non-axisymmetry of stellarators, different toroidal as well as poloidal harmonics couple to each other. It follows that each singular surface can have multiple resonant harmonics, with multiplicity M≥1. The corresponding matrix eigenvalue problem involves a 2M×2M matrix, resulting in M pairs of positive and negative eigenvalues. The generalized stability criterion is that all eigenvalues must be real. While the original Mercier criterion can be expressed in terms of quadratures of equilibrium quantities over the singular surface, which can be evaluated anywhere, the generalized Mercier criterion can only be evaluated on rational q surfaces with a given set of resonant harmonics.

Physics↗

DOE OSTI2025

Toward Establishing Uniqueness of Experimentally Determined Transference Numbers

The passage of current through a battery results in the development of concentration gradients in the electrolytic phase. For a fully characterized binary electrolyte, where the conductivity, salt diffusion coefficient, cation transference number, and the thermodynamic factor are known, concentration and potential gradients in the electrolytic phase can be modeled using Newman’s concentrated solution theory. We report two methods for measuring the transference number: the standard method based on electrochemical measurements ( t + , echem 0 ) and electrophoretic NMR ( t + , eNMR 0 ). The electrochemical approach requires combining measurements from multiple experiments; the equations used to determine the cation transference number and the thermodynamic factor are coupled, nonlinear algebraic equations. In the electrophoretic-NMR-based approach, however, the equations used to determine the cation transference number and the thermodynamic factor are decoupled. We find for a liquid electrolyte comprised of a lithium salt dissolved in tetraglyme, the values of the transference numbers obtained by these two methods are distinct. For example, at 30 °C, t + , echem 0 = −1.02 ± 1.11 and t + , eNMR 0 = 0.25 ± 0.04. The corresponding thermodynamic factors are also different. While the magnitude of the predicted concentration gradients based on the two sets of parameters are different, the predicted current-voltage relationships are similar.

Hickson, Darby T. (ORCID:0000000251339755)↗

DOE OSTI2025

Corral Summit Pumped Storage Hydropower Hybrid: Site Suitability Assessment

In 2024, Idaho National Laboratory (INL) and Pacific Northwest National Laboratory (PNNL) initiated a technical-assistance project to support Cat Creek Energy, LLC, (CCE) in evaluating site suitability for the proposed Corral Summit Pumped Storage Hydropower (PSH) project in south-central Idaho near Mackay Reservoir. The Corral Summit facility incorporates battery storage and photovoltaic (PV) solar arrays in a Trybrid configuration to deliver large-volume long-duration (LVLD) storage solutions for rural electric cooperatives in eastern Idaho. The evaluation process focused on determining the most-suitable location for the upper reservoir of the PSH system, guided by a comprehensive assessment framework spanning multiple categories, including physical characteristics, environmental constraints, building infrastructure, regulatory constraints, cultural resources and sensitivity, social factors, and power market and grid integration. Each site was analyzed based on a ranking scale (0–1), which scores ranging from “severely disfavored” to “highly favored,” allowing detailed comparisons of site-specific conditions. Categories such as hydraulic head, utilities corridor, land ownership, and transmission-grid limitations emerged as key contributors to the overall assessment. Site 2 (Idaho Trust) demonstrated a slight advantage over Site 1 (Bureau of Land Management) primarily due to favorable outcomes in regulatory constraints, building infrastructure, and power-market integration. However, Site 1 outperformed Site 2 in factors related to physical characteristics and social factors. The report emphasizes the need for further evaluation of both sites before clear determination of which site is preferred, due to the limited information available on either site at the time of this report. Key areas of evaluation to clearly define the preferred site are ecological impacts, cultural-resource surveys, and economic-feasibility assessments. For successful project execution, recommended follow-up actions include seismic and geotechnical surveys, groundwater and habitat monitoring, regulatory reviews of water rights and right-of-way agreements, cultural engagement with local tribal governments, and enhanced stakeholder strategies. These efforts will ensure the Corral Summit Trybrid facility meets local energy needs while balancing environmental, social, and regulatory responsibilities.

13 - HYDRO ENERGY↗

DOE OSTI2025

Corral Summit Pumped Storage Hydropower Hybrid Site Suitability Assessment (Rev.1)

13 - HYDRO ENERGY↗

DOE OSTI2023

$\mathrm{RADICAL}$-Pilot and $\mathrm{PMIx}$/$\mathrm{PRRTE}$: Executing Heterogeneous Workloads at Large Scale on Partitioned $\mathrm{HPC}$ Resources

Execution of heterogeneous workflows on high-performance computing (HPC) platforms present unprecedented resource management and execution coordination challenges for runtime systems. Task heterogeneity increases the complexity of resource and execution management, limiting the scalability and efficiency of workflow execution. Re-source partitioning and distribution of tasks execution over portioned re-sources promises to address those problems but we lack an experimental evaluation of its performance at scale. Here this paper provides a performance evaluation of the Process Management Interface for Exascale (PMIx) and its reference implementation PRRTE on the leadership-class HPC plat-form Summit, when integrated into a pilot-based runtime system called RADICAL-Pilot. We partition resources across multiple PRRTE Distributed Virtual Machine (DVM) environments, responsible for launching tasks via the PMIx interface. We experimentally measure the work-load execution performance in terms of task scheduling/launching rate and distribution of DVM task placement times, DVM startup and termination overheads on the Summit leadership-class HPC platform. Integrated solution with PMIx/PRRTE enables using an abstracted, standardized set of interfaces for orchestrating the launch process, dynamic process management and monitoring capabilities. It extends scaling capabilities allowing to overcome a limitation of other launching mechanisms (e.g., JSM/LSF). Explored different DVM setup configurations provide insights on DVM performance and a layout to leverage it. Our experimental results show that heterogeneous workload of 65,500 tasks on 2048 nodes, and partitioned across 32 DVMs, runs steady with resource utilization not lower than 52%. While having less concurrently executed tasks resource utilization is able to reach up to 85%, based on results of heterogeneous workload of 8200 tasks on 256 nodes and 2 DVMs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Potential Adoption and Benefits of Co-Optimized Multimode Engines and Fuels for U.S. Light-Duty Vehicles

Exploring a diverse portfolio of technologies for decarbonization is crucial to understanding the potential impacts of different technological solutions and their associated environmental implications. Using high-octane, high-sensitivity biofuel blends in co-optimized multimode engines can increase engine efficiency and reduce vehicle emissions. Here, the multimode engine research focuses on the benefits of light-duty vehicle engines, which can operate in multiple modes depending on the vehicle's load. Low-temperature combustion can improve efficiency and reduce emissions (such as those from oxides of nitrogen and particulate matter) during low-load operation, while spark ignition performance is maintained in high-load operation. These advanced engines can be optimized to run on blends of biobased fuels. This analysis models scenarios for potential market adoption of co-optimized multimode vehicles fueled by three different bioblendstocks: ethanol, isopropanol, and isobutanol. An integrated modeling approach is used to forecast the energy and environmental impacts of the deployment of co-optimized multimode vehicles and fuels in the light-duty sector over the 2020-to-2050 time horizon. The multidisciplinary approach combines vehicle sales modeling, system dynamics modeling of the biorefining industry, and life cycle assessment to estimate the emissions and energy benefits. The models consider market forces such as consumer preferences for vehicle attributes, biofuel supply and demand dynamics subject to biorefinery capacity build-out and bioresource constraints, and forecasted changes to the U.S. bulk energy system over time. Market adoption of co-optimized vehicles is evaluated across a wide parameter space for incremental vehicle cost and engine efficiency improvement. This analysis reveals that the deployment of co-optimized multimode fuels and vehicles results in up to a 5% reduction in annual sector-wide life cycle greenhouse gas (GHG) emissions by 2050, relative to a business-as-usual scenario, but is also indicates environmental trade-offs, such as higher life cycle water-use. Emission benefits could potentially increase beyond 2050, as the new technologies penetrate the market and gain a foothold. Results also show that, under certain circumstances, vehicles with engines co-optimized for use with high-octane, high-sensitivity biofuel blends can be cost-competitive with conventional gasoline, while reducing GHG emissions. Our modeling results indicate that co-optimized multimode fuels and engines can be strategically leveraged in tandem with electrification to decarbonize the light-duty sector. Co-optimized vehicles could play a role in the early years of the time horizon, while electric vehicles (EVs) could become more competitive in the later years, highlighting the complementary benefits of these technologies for GHG reductions.

Oke, Doris↗

DOE OSTI2024

Understanding the Impact of Fuel on Surfactant Microstructure of Firefighting Foam

Abstract Aqueous film-forming foam is being phased out due to the environmental impacts of fluorinated surfactants contained in the firefighting foams. To develop an environmentally friendly firefighting foam, it is important to understand the factors controlling the firefighting performance of surfactants. Fuel transport through foam has been considered as a dominant mechanism for foam collapse. Therefore, the impact of fuels (heptane, octane and trimethylbenzene (TMB)) on surfactant microstructure was studied for three different types of surfactants (Capstone, Glucopon, and siloxane) that have applications in firefighting foam. Multiple techniques were used to identify the microstructure and interfacial properties of surfactants with and without exposure to liquid fuel. The ignition time of fuel vapor through foam and solubility of fuel through liquid surfactant solution were measured as well. This work shows fuel solubility has an impact on the surfactant microstructure and interfacial properties. In addition, fuel solubility and vapor pressure affect the ignition time of fuel vapors.

Engineering↗

DOE OSTI2020

After the hurricane: Validating a resilience assessment methodology

With increasing utility grid outages in the United States, there is growing interest in assessing risk and developing mitigation strategies to reduce the impact of grid outages. Working with the U.S. Air Force, the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) developed a replicable energy resilience assessment methodology and investment decision tool to: (1) identify and score hazards and vulnerabilities at the site level; (2) analyze risks to energy infrastructure; and (3) identify and prioritize energy resilience investments. This work improves on existing resilience assessment methodologies and tools by combining a bottom-up, all-hazards assessment methodology with top-down geographic information system mapping capabilities to provide an innovative, dynamic tool for identifying and prioritizing actionable solutions. This process combines probabilistic forecasting with an iterative approach for continuously updating and reassessing risks to address temporal dynamism. Relationships among systems are modeled and visualized to estimate the effectiveness of resilience actions across multiple interdependent systems and inform financial priorities through cost-difficulty-impact trade-offs. The approach is validated in a case study at Tyndall Air Force Base (AFB) in Florida, which experienced a Category 5 hurricane in 2018. The risks and mitigation strategies identified pre-hurricane are compared with post-hurricane, realized impacts. The assessment effectively identifies risks and actions to increase site energy resilience, but the methodology can be enhanced though greater consideration of the interdependencies between the energy system and related systems like transportation, communication, and food/water systems, which impact the recovery of the energy system and the base.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Zwitterion Moieties in Polypeptides Synergistically Enhance the Release of Cellulose and Amorphous Polysaccharides from Plant Cell Walls

This study demonstrated that covalently localized zwitterionic moieties in zwitterionic polypeptides (ZIPs) effectively disrupt hydrogen bonds in cellulosic substrates, including filter paper and plant cell wall materials, without significant cytotoxicity. ZIPs with varying densities of zwitterionic side chains were synthesized via the postpolymerization modification of histidinecontaining oligopeptides. The newly developed ZIPs predominantly comprised repeating units with zwitterionically converted side chains. Such ZIPs can cleave multiple hydrogen bonds by anchoring the zwitterionic structure at specific sites, thereby partially dissociating the polysaccharide chains in the cell wall. They are especially effective in dissolving amorphous cellulose, even at low concentrations in aqueous solutions. Importantly, this effect was achieved with minimal cellular toxicity, harnessing the advantages of ionic liquid-like properties while mitigating their high-toxicity limitations. This biofriendly approach to cell wall denaturation highlights a novel method for controlling hydrogen bond networks in polysaccharides and cell walls. These findings indicate a new approach for reducing biomass recalcitrance and developing next-generation biobased materials and fuels derived from plant cell walls.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Ion complexation waves emerge at the curved interfaces of layered minerals

Abstract Visualizing hydrated interfaces is of widespread interest across the physical sciences and is a particularly acute need for layered minerals, whose properties are governed by the structure of the electric double layer (EDL) where mineral and solution meet. Here, we show that cryo electron microscopy and tomography enable direct imaging of the EDL at montmorillonite interfaces in monovalent electrolytes with ångstrom resolution over micron length scales. A learning-based multiple-scattering reconstruction method for cryo electron tomography reveals ions bound asymmetrically on opposite sides of curved, exfoliated layers. We observe conserved ion-density asymmetry across stacks of interacting layers in cryo electron microscopy that is associated with configurations of inner- and outer-sphere ion-water-mineral complexes that we term complexation waves. Coherent X-ray scattering confirms that complexation waves propagate at room-temperature via a competition between ion dehydration and charge interactions that are coupled across opposing sides of a layer, driving dynamic transitions between stacked and aggregated states via layer exfoliation.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Catalytic open-circuit passivation by thin metal oxide films of p-Si anodes in aqueous alkaline electrolytes

Ni and NiO x -based protective thin films are shown to catalyze the oxidation of Si in the presence of O 2 in strongly alkaline KOH(aq) even in the absence of illumination. The O 2 in solution drove the open-circuit potential of the electrode to >0.4 V, which is positive of the Si passivation potential. The elevated electrochemical potential of the surface promoted formation of passive oxides on exposed Si regions of Si/Ni electrodes. Catalytic passivation of Si extended the durability of an np + -Si(100)/NiO x photoanode to >400 h while operating under simulated day/night cycles. In contrast, electrodes without a Ni(O x ) layer and/or without O 2 in solution displayed direct etching of the Si and corrosion pitting during non-illuminated, simulated nighttime episodes of day/night cycling. The O 2 -derived catalyzed passivation of Si using thin films can be generalized to multiple phases of NiO x as well as to materials other than Ni. Finally, relative to operation in aqueous alkaline conditions, decreasing the pH of the electrolyte decreased the dissolution rate of the protective oxide layer formed by the catalyzed passivation process, and consequently increased the durability of the photoanode, but yielded lower photoelectrode fill factors for water oxidation due to the relatively large kinetic overpotentials for the electrocatalyzed oxygen-evolution reaction at near-neutral pH.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Quarkyonic solution to the hyperon puzzle

We show that Quarkyonic Matter can mitigate the hyperon puzzle. The key observation is that the hyperon threshold is shifted to a higher density by a factor of constituent strange quark mass. We illustrate this effect by using the ideal dual Quarkyonic (IdylliQ) model with multiple flavors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

A Code-Agnostic Driver Application for Coupled Neutronics and Thermal-Hydraulic Simulations

While the literature has numerous examples of Monte Carlo and computational fluid dynamics (CFD) coupling, most are hard-wired codes intended primarily for research rather than as standalone, general-purpose applications. In this work, we describe an open source application, ENRICO, that enables coupled neutronic and thermal-hydraulic simulations between multiple codes that can be chosen at runtime (as opposed to a coupling between two specific codes). The application has been designed such that the control flow logic, domain mapping, nonlinear fixed-point iteration, solution transfers, and convergence checks are all agnostic to the underlying physics solvers used. Special emphasis has also been placed on enabling efficient execution on distributed-memory computing environments. The transfer of solution fields between solvers is performed in memory rather than through filesystem I/O. Additionally, solvers can be configured to run on overlapping or disjoint sets of processes. To date, coupling with the OpenMC and Shift Monte Carlo codes, the Nek5000 CFD code, and a simplified heat diffusion and subchannel solver has been implemented in ENRICO. We present results for coupled simulations of a single light-water reactor fuel assembly based on the NuScale reactor using various combinations of the physics solvers. For this problem, the coupled simulations are shown to converge in about four Picard iterations. A comparison of the heat source and temperature distributions computed by ENRICO using OpenMC coupled with Nek5000 and Shift coupled with Nek5000 illustrates remarkable agreement between the codes.

42 ENGINEERING↗

DOE OSTI2024

Analytical insights into the interplay of momentum, multiplicity, and the speed of sound in heavy-ion collisions

We introduce a minimal model of ultracentral heavy-ion collisions to study the relation between the speed of sound of the produced plasma and the final particles' energy and multiplicity. We discuss how the particles' multiplicity N tot and average energy E tot / N tot is related to the speed of sound c s by c s 2 = d ln ( E tot / N tot ) / d ln N tot if the fluid is inviscid, its speed of sound is constant and all final particles can be measured. We show that finite rapidity cuts on the particles' multiplicity N and energy E introduce corrections between c s 2 and d ln ( E / N ) / d ln N that depend on the system's lifetime. We study analytically these deviations with the Gubser hydrodynamic solution, finding that, for ultrarelativistic bosons, they scale as the ratio of the freeze-out temperature T FO over the maximum initial temperature of the fluid T 0 ; the nonthermodynamic aspect of these corrections is highlighted through their dependence on the system's initial conditions. Published by the American Physical Society 2024

Physics↗