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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Solvent-Cast Solid Electrolyte Membranes Based on a Charged Rigid-Rod Polymer and Ionic Liquids

Solid-state electrolytes are attractive for use in electrochemical devices because they remove the need for a flammable liquid electrolyte while contributing to the structural integrity of the device. We have recently developed a class of solid electrolytes, termed molecular ionic composites (MICs), composed of ionic liquids (ILs) and a rigid-rod polyelectrolyte, poly(2,2'-disulfonyl-4,4'-benzidine terephthalamide) (PBDT). MIC materials, originally obtained through an ion-exchange process between IL and PBDT aqueous solution, possess an unprecedented combination of high ionic conductivity, high thermal stability, low flammability and widely tunable tensile storage moduli. Here we present a facile solvent casting method for preparing MIC membranes. These membranes are uniform, flexible, and tough, with tunable composition and thickness (≥ 40 μm). Unlike the previous ion-exchange method, which only allowed incorporation of hydrophilic ILs, we can now incorporate hydrophobic ILs to prepare MIC membranes for, e.g. battery electrolytes. A sodium (Na) metal symmetric cell constructed with a PBDT-Pyr 14 TFSI membrane as the solid electrolyte shows long-term stable cycling (> 500 h.) at 60 °C. Furthermore, the ability to prepare MICs using both hydrophilic and hydrophobic ILs initiates a wider range of MIC materials and broadens the array of applications accessible by MIC membranes.

25 ENERGY STORAGE↗
DOE OSTI2026

A Scalable Reduced‐Order Model for the Steady Navier–Stokes Equations

Scaling up new scientific technologies from laboratory to industry often involves demonstrating performance on a larger scale. Computer simulations can accelerate design and predictions in the deployment process, though traditional numerical methods are computationally intractable even for intermediate pilot plant scales. Recently, the component reduced order modeling method has been developed to tackle this challenge by combining projection reduced order modeling and discontinuous Galerkin domain decomposition. However, while many scientific or engineering applications involve nonlinear physics, this method has only been demonstrated for various linear systems. In this work, the component reduced order modeling method is extended to steady Navier–Stokes flow, with application to general nonlinear physics in view. The large‐scale, global domain is decomposed into a combination of small‐scale unit component. Linear subspaces for flow velocity and pressure are identified via proper orthogonal decomposition over sample snapshots collected from each small‐scale unit component. Velocity bases are augmented with a pressure supremizer to satisfy the inf–sup condition for stable pressure prediction. Two different nonlinear reduced order modeling methods are employed and compared for efficient evaluation of nonlinear advection: A third‐order tensor projection operator and the empirical quadrature procedure. The proposed method is demonstrated on the flow over arrays of five different unit objects, achieving a 23‐fold speedup with less than 4% relative error in domains up to 256 times larger than the unit components. Furthermore, a numerical experiment with the pressure supremizer strongly indicates the need for a supremizer for stable pressure prediction. A comparison between the tensorial approach and the empirical quadrature procedure revealed a slight advantage of the empirical quadrature procedure. The framework is compared with an alternating Schwarz‐based reduced‐order approach, demonstrating improved efficiency and robustness for the DG‐based global solver while retaining flexibility for sub‐scale iterative solvers. The method is further extended to a coupled advection–diffusion and Navier–Stokes system, illustrating its applicability to multi‐physics problems and its potential for more general, inter‐coupled nonlinear systems.

42 ENGINEERING↗
DOE OSTI2020

Solar+ Optimizer: A Model Predictive Control Optimization Platform for Grid Responsive Building Microgrids

With the falling costs of solar arrays and battery storage and reduced reliability of the grid due to natural disasters, small-scale local generation and storage resources are beginning to proliferate. However, very few software options exist for integrated control of building loads, batteries and other distributed energy resources. The available software solutions on the market can force customers to adopt one particular ecosystem of products, thus limiting consumer choice, and are often incapable of operating independently of the grid during blackouts. In this paper, we present the “Solar+ Optimizer” (SPO), a control platform that provides demand flexibility, resiliency and reduced utility bills, built using open-source software. SPO employs Model Predictive Control (MPC) to produce real time optimal control strategies for the building loads and the distributed energy resources on site. SPO is designed to be vendor-agnostic, protocol-independent and resilient to loss of wide-area network connectivity. The software was evaluated in a real convenience store in northern California with on-site solar generation, battery storage and control of HVAC and commercial refrigeration loads. Preliminary tests showed price responsiveness of the building and cost savings of more than 10% in energy costs alone.

14 SOLAR ENERGY↗
DOE OSTI2022

SolarPlus-Optimizer v0.1

With the falling costs of solar arrays and battery storage and reduced reliability of the grid due to natural disasters, small-scale local generation and storage resources are beginning to proliferate. However, very few software options exist for integrated control of building loads, batteries and other distributed energy resources. The available software solutions on the market can force customers to adopt one particular ecosystem of products, thus limiting consumer choice, and are often incapable of operating independently of the grid during blackouts. In this software package, we present the "Solar+ Optimizer" (SPO), a control platform that provides demand flexibility, resiliency and reduced utility bills, built using open-source software. SPO employs Model Predictive Control (MPC) to produce real time optimal control strategies for the building loads and the distributed energy resources on site. SPO is designed to be vendor-agnostic, protocol-independent and resilient to loss of wide-area network connectivity. The software was evaluated in a real convenience store in northern California with on-site solar generation, battery storage and control of HVAC and commercial refrigeration loads. Preliminary tests showed price responsiveness of the building and cost savings of more than 10% in energy costs alone.

Prakash, AnandKrishnan↗
DOE OSTI2022

Modeling Analog Tile-Based Accelerators Using SST

Analog computing has been widely proposed to improve the energy efficiency of multiple important workloads including neural network operations, and other linear algebra kernels. To properly evaluate analog computing and explore more complex workloads such as systems consisting of multiple analog data paths, system level simulations are required. Moreover, prior work on system architectures for analog computing often rely on custom simulators creating signficant additional design effort and complicating comparisons between different systems. To remedy these issues, this report describes the design and implementation of a flexible tile-based analog accelerator element for the Structural Simulation Toolkit (SST). The element focuses on heavily on the tile controller—an often neglected aspect of prior work—that is sufficiently versatile to simulate a wide range of different tile operations including neural network layers, signal processing kernels, and generic linear algebra operations without major constraints. The tile model also interoperates with existing SST memory and network models to reduce the overall development load and enable future simulation of heterogeneous systems with both conventional digital logic and analog compute tiles. Finally, both the tile and array models are designed to easily support future extensions as new analog operations and applications that can benefit from analog computing are developed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Automated Redox Titrations via Interdigitated Electrode Arrays: Application to the Mediated Electron Transfer Interrogation of Charge and Rate on Electrodeposited Polymers

Mediated electron transfer (MET) plays a crucial role in energy storage and conversion technologies such as redox targeting flow batteries (RTFBs), yet its experimental investigation often requires labor-intensive and low-throughput setups. To address this, we developed a microfabricated interdigitated electrode array (IDA) platform that enables automated, high-throughput electrochemical redox titration measurement to be performed to study the MET process. Our redox titration method enables simultaneous measurement of the charge capacity and rate of MET processes on a material or surface. Automated redox titration (ART) facilitates systematic investigation of the MET process across a broad parameter space, exemplified through the study of polypyrrole (PPy) and a pyrene-4,5,9,10-tetrone azo group-based polymer (PTAP), both redox-active polymers relevant to various energy storage applications. Using PPy as a model material, 500 redox titration measurements were conducted within 50 h, varying the electrode gap widths, polymer charging potentials, voltammetric scan rates, and electrolyte concentrations. Finite-element simulations confirmed the electrochemical responses and elucidated the kinetics of the MET reactions. Our automated methodology was further tested with PTAP, revealing a surprising charging potential dependence on the rate of MET. The automation, flexibility, and scalability of our redox titration platform pave the way not only for advanced studies of MET processes relevant to RTFBs, but also with implications in the understanding of next-generation energy storage materials, molecular electrocatalysis, and biosensing.

electrochemical analysis↗
DOE OSTI2022

Unraveling the regulation of sugar beet pulp utilization in the industrially relevant fungus Aspergillus niger

Efficient utilization of agro-industrial waste, such as sugar beet pulp, is crucial for the bio-based economy. The fungus Aspergillus niger possesses a wide array of enzymes that degrade complex plant biomass substrates, and several regulators have been reported to play a role in their production. The role of the regulators GaaR, AraR, and RhaR in sugar beet pectin degradation has previously been reported. However, genetic regulation of the degradation of sugar beet pulp has not been assessed in detail. In this study, we generated a set of single and combinatorial deletion mutants targeting the pectinolytic regulators GaaR, AraR, RhaR, and GalX as well as the (hemi-)cellulolytic regulators XlnR and ClrB to address their relative contribution to the utilization of sugar beet pulp. We show that A. niger has a flexible regulatory network, adapting to the utilization of (hemi-)cellulose at early timepoints when pectin degradation is impaired.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The Stability of Fiber Spectrographs in the Faint-source Regime

The use of optical fibers in astronomical instrumentation offers high-multiplex and light-gathering flexibility. However, with most previous fiber spectrographs optimized for large fields of view on modest-aperture telescopes, the performance of fibers in the context of faint targets on large telescopes remains largely untested. In this paper, we evaluate aspects of fiber stability, especially as they apply in the context of precision sky subtraction of faint sources at modest spectral resolution ($R$ ~ 3000). After introducing a framework for describing potential systematic errors, we use publicly available data from existing instruments, including instrumentation used by the fourth-generation Sloan Digital Sky Survey’s MaNGA project (MaNGA: Mapping Nearby Galaxies at Apache Point Observatory) and the Very Large Telescope’s FLAMES: Fiber Large Array Multi Element Spectrograph. We isolate sources of fiber systematics and estimate the observed amplitude of persistent residuals as well as stochastic noise contributions resulting from changing fiber stresses. Comparing these levels against their impact on various sky subtraction schemes demonstrates that 0.1% precision sky subtraction with fiber instruments is possible. As a demonstration, we show that the MaNGA instrument can deliver 0.2% residuals on bright near-IR sky lines with nonlocal sky subtraction, if pseudo-slit limitations are addressed by allocating 50% of its fibers to sky. We further highlight recently published deep exposures that achieved a 1$σ$ background level of 27.6 AB per square arc second, equivalent to a precision of 0.2% of the sky background continuum.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Beam Measurements of the Tianlai Dish Radio Telescope using an Unmanned Aerial Vehicle

Precision measurement of the beam pattern of an antenna is very important for many applications. While traditionally such measurement is often made in a microwave anechoic chamber or at a test range, measurement using an unmanned aerial vehicle offers a number of advantages: the measurement can be made for the assembled antenna on site, thus reflecting the actual characteristics of the antenna of interest, and more importantly, it can be performed for larger antennas which cannot be steered or easily measured using the anechoic chamber and test range. Here we report our beam measurement experiment with UAV for a 6 meter dish used in the Tianlai array, which is a radio astronomy experiment. Due to the dish's small collecting area, calibration with an astronomical source only allows for determining the antenna beam pattern over a very limited angular range. We describe in detail the setup of the experiment, the components of the signal transmitting system, the design of the flight path and the procedure for data processing. We find the UAV measurement of the beam pattern agrees very well with the astronomical source measurement in the main lobe, but the UAV measurement can be extended to the fourth side lobe. The measured position and width of each lobe also shows good agreement with electromagnetic field simulation. This UAV-based approach of beam pattern measurement is flexible and inexpensive, and the technique may also be applied to other experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Bayesian projection pursuit regression

In projection pursuit regression (PPR), a univariate response variable is approximated by the sum of $M$ “ridge functions,” which are flexible functions of one-dimensional projections of a multivariate input variable. Traditionally, optimization routines are used to choose the projection directions and ridge functions via a sequential algorithm, and $M$ is typically chosen via cross-validation. Here, we introduce a novel Bayesian version of PPR, which has the benefit of accurate uncertainty quantification. To infer appropriate projection directions and ridge functions, we apply novel adaptations of methods used for the single ridge function case ($M$=1), called the Bayesian Single Index Model; and use a Reversible Jump Markov chain Monte Carlo algorithm to infer the number of ridge functions $M$. We evaluate the predictive ability of our model in 20 simulated scenarios and for 23 real datasets, in a bake-off against an array of state-of-the-art regression methods. Finally, we generalize this methodology and demonstrate the ability to accurately model multivariate response variables. Its effective performance indicates that Bayesian Projection Pursuit Regression is a valuable addition to the existing regression toolbox.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Demonstrating Advanced Nuclear Energy Solutions for Net Zero

Background/Objectives. The aggressive goals being set by nation states, communities, and private industry for decarbonization of grid electricity, industrial heat sources, and transportation around the world are imperative to mitigating the devastating effects that we are seeing from climate change. Although many of these goals focus on accomplishments by 2035 or 2050, the decisions that we make today won’t just impact the landscape of energy systems for the next 20 or 30 years—they will shape the world’s environment for centuries to come. That means that we can’t just focus on technologies that will get us to 2050, but technologies that will withstand our energy demands over that long-ranging future. Success will require us to utilize all of the clean energy resources that we have available to meet demands for electricity, heat, and steam, and we will need energy carriers such as hydrogen that do not emit additional greenhouse gases at the point of use. Nuclear energy, ranging from technologies in service today to advanced, higher temperature and modular systems that will be in service this decade, will provide a robust complement to renewable energy resources that operate variably. Researchers across the U.S. Department of Energy laboratory complex are working to advance multiple aspects of these clean energy solutions, with many focusing on integrated energy system solutions that leverage all available clean energy assets to meet wide-ranging energy demands. Approach/Activities. Nuclear energy is a proven, zero-emission option during operation that can provide consistent, dispatchable power to meet electricity demands while also providing high-quality heat that can meet energy demands beyond the electricity sector. Energy system design should seek to maximize these assets. As a dispatchable energy source with a small land utilization footprint, nuclear energy can be collocated with renewable resources, and the smaller systems that will be deployed this decade (ranging from a few megawatts to hundreds of megawatts) can be installed right where that energy is needed. Integrated nuclear and renewable systems will enhance power grid reliability and resilience, and they will help stabilize the grid through their increasingly flexible operation. Licensing, installation, and broad adoption of these advanced nuclear energy systems are expected to progress significantly in the 2020s, but this may be longer than desired by some stakeholders wishing to implement impactful clean energy decisions today. However, one must recall that nuclear energy systems will operate for 80 or more years, as is being demonstrated by current fleet nuclear systems. The nuclear community is extremely thorough in reviewing these systems with regard to safety and security; these efforts ensure that the deployed systems will continue to provide reliable, resilient energy over that operational lifetime. That investment of time up front will ensure that we can support energy demands over the centuries to come. While advanced nuclear technologies move through this process, communities and private industry may choose to install renewable generation systems that can later be coupled to the complementary nuclear systems as they become available—thus moving closer to the net zero goals in the near term. Choosing technologies and deployment configurations that allow small modular nuclear powerhouses to be added to these “energy parks” as they become available will ensure that advanced technologies can be readily adopted to support growing demands for clean energy. Results/Lessons Learned. The primary focus of integrated energy systems (IES) research is to assess the technical and economic potential of novel multi-input, multioutput solutions that are expected to enhance energy system flexibility, reliability, and resilience as we pursue a clean energy transition. Various energy applications and product streams beyond electricity are being evaluated, ranging from generation of potable water to production of hydrogen, fertilizers, synthetic fuels, and various chemicals. In early FY23 Idaho National Laboratory (INL) will commission thermal energy generation systems that emulate nuclear fission energy input using electric heating and will allow for integrated system testing with thermal energy storage, hydrogen production via high temperature electrolysis (HTE), and power systems hardware to demonstrate operation of a clean energy park within a microgrid or larger grid infrastructure, supporting up to 450 kW of heat input via electric heating and demonstrating operation of HTE systems at the multi-hundred kW scale. This presentation will highlight the wide array of RD&D being conducted at INL and partner laboratories to develop and deploy nuclear and renewable-based IES that will be key to achieving our net zero goals, including both computational and experimental demonstrations. By working with key collaborators in industry, analytical st

08 HYDROGEN↗
DOE OSTI2020

H2@Scale Concept Hydrogen Demand and Resources

The H2@Scale concept involves hydrogen as an energy intermediate. Hydrogen can be produced from various conventional and renewable energy sources including as a responsive load on the electric grid. Hydrogen has many current applications and many more potential applications, such as energy for transportation, as a feedstock for synthetic fuels, and to upgrade oil and biomass, heat for industry and buildings, and electricity storage. Owing to its flexibility and fungibility, a hydrogen intermediate could link energy sources that have surplus availability to markets that require energy or chemical feedstocks, benefiting both. This data release provides estimates on hydrogens serviceable consumption potential for possible hydrogen applications and the technical potential for producing hydrogen from various resources. We define the technical potential as the resource potential constrained by real-world geography and system performance, but not by economics.

Array↗
DOE OSTI2020

A search for cosmogenic neutrinos with the ARIANNA test bed using 4.5 years of data

The primary mission of the ARIANNA ultra-high energy neutrino telescope is to uncover astrophysical sources of neutrinos with energies greater than 10 16 eV. A pilot array, consisting of seven ARIANNA stations located on the surface of the Ross Ice Shelf in Antarctica, was commissioned in November 2014. We report on the search for astrophysical neutrinos using data collected between November 2014 and February 2019. A straight-forward template matching analysis yielded no neutrino candidates, with a signal efficiency of 79%. We find a 90% confidence upper limit on the diffuse neutrino flux of E 2 Φ=1.7× 10 -6 GeV cm -2 s -1 sr -1 for a decade wide logarithmic bin centered at a neutrino energy of 1018,eV, which is an order of magnitude improvement compared to the previous limit reported by the ARIANNA collaboration. The ARIANNA stations, including purpose built cosmic-ray stations at the Moore's Bay site and demonstrator stations at the South Pole, have operated reliably. Sustained operation at two distinct sites confirms that the flexible and adaptable architecture can be deployed in any deep ice, radio quiet environment. We show that the scientific capabilities, technical innovations, and logistical requirements of ARIANNA are sufficiently well understood to serve as the basis for large area radio-based neutrino telescope with a wide field-of-view.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Will LISA Detect Harmonic Gravitational Waves from Galactic Cosmic String Loops?

Rapid advancement in the observation of cosmic strings has been made in recent years placing increasingly stringent constraints on their properties, with $G\mu\lesssim 10^{-11}$ from Pulsar Timing Array (PTA). Cosmic string loops with low string tension clump in the Galaxy due to slow loop decay and low gravitational recoil, resulting in great enhancement to loop abundance in the Galaxy. With an average separation of down to just a fraction of a kpc, and the total power of gravitational wave (GW) emission dominated by harmonic modes spanning a wide angular scale, resolved loops located in proximity are powerful, persistent, and highly monochromatic sources of GW with a harmonic signature not replicated by any other sources, making them prime targets for direct detection by the upcoming Laser Interferometer Space Antenna (LISA), whose frequency range is well-matched. Unlike detection of bursts where the detection rate scales with loop abundance, the detection rate for harmonic signal is the result of a complex interplay between the strength of GW emission, loop abundance, and other sources of noise, and is most suitably studied through numerical simulations. We develop a robust and flexible framework for simulating loops in the Galaxy for predicting direct detection of harmonic signal from resolved loops by LISA. Our simulation reveals that the most accessible region in the parameter space consists of large loops $\alpha=0.1$ with low tension $10^{-21}\lesssim G\mu\lesssim 10^{-19}$. Direct detection of field theory cosmic strings is unlikely, with the detection probability $p_{\mathrm{det}}\lesssim 2\%$ for a 1-year mission. An extension suggests that direct detection of cosmic superstrings with a low intercommutation probability is very promising. Searching for harmonic GW signal from resolved loops through LISA observations will potentially place physical constraints on string theory.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Shifting Between Compute and Memory Bounds: A Compression-Enabled Roofline Model

In the evolving landscape of high-performance computing, especially to fight the end of Moore’s Law and Dennard’s Scaling, the ability to shift between compute-bound and memory-bound states is critical for enhancing adaptability and flexibility to diverse system and domain-specific architectures. Such capability is vital for optimizing performance across distinguished hardware configurations, such as accelerators, memory hierarchies, and cache systems. Despite that ad hoc optimization techniques, such as compressed/approximate computation, have been enabled for compute-/data-intensive computing for improved performance in distinct hardware settings, there lacks an understanding of 1) the rational behind performance improvement; 2) capability of different optimizations; 3) what optimization to respond to specific computational and memory demands. This work proposes a compression-enabled roofline model to facilitate this adaptability with data compression techniques to balance and transform between computational and memory demands. This model enables applications to adjust in response to the specific strengths and limitations of the underlying hardware and system to optimize resource utilization. The effectiveness of this approach is demonstrated with matrix multiplication kernels on different input sizes, with turning on/off various compression techniques, including 1) low-precision floating point; 2) sparse matrix formulation; and 3) compressed arrays with ZFP. By reducing memory transfer volumes and cache misses and increasing data locality and computational intensity through compression, the specific roofline model can transform between compute and memory bounds to align more efficiently with system capabilities. This advancement not only improves overall performance but also maximizes adaptability in diverse computing environments.

Naraparaju, Ramasoumya [University of Washington]↗
DOE OSTI2022

Data Science-Driven Analysis of Substrate-Permissive Diketopiperazine Reverse Prenyltransferase NotF: Applications in Protein Engineering and Cascade Biocatalytic Synthesis of (-)-Eurotiumin A

Prenyltransfer is an early-stage carbon-hydrogen bond (C-H) functionalization prevalent in the biosynthesis of a diverse array of biologically active bacterial, fungal, plant, and metazoan diketopiperazine (DKP) alkaloids. Toward the development of a unified strategy for biocatalytic construction of prenylated DKP indole alkaloids, we sought to identify and characterize a substrate-permissive C2 reverse prenyltransferase (PT). As the first tailoring event within the biosynthesis of cytotoxic notoamide metabolites, PT NotF catalyzes C2 reverse prenyltransfer of brevianamide F. Solving a crystal structure of NotF (in complex with native substrate and prenyl donor mimic dimethylallyl S-thiolodiphosphate (DMSPP)) revealed a large, solvent-exposed active site, intimating NotF may possess a significantly broad substrate scope. To assess the substrate selectivity of NotF, we synthesized a panel of 30 sterically and electronically differentiated tryptophanyl DKPs, the majority of which were selectively prenylated by NotF in synthetically useful conversions (2 to > 99%). Quantitative representation of this substrate library and development of a descriptive statistical model provided insight into the molecular origins of NotF's substrate promiscuity. This approach enabled the identification of key substrate descriptors (electrophilicity, size, and flexibility) that govern the rate of NotF-catalyzed prenyltransfer, and the development of an "induced fit docking (IFD)-guided" engineering strategy for improved turnover of our largest substrates. We further demonstrated the utility of NotF in tandem with oxidative cyclization using flavin monooxygenase, BvnB. This one-pot, in vitro biocatalytic cascade enabled the first chemoenzymatic synthesis of the marine fungal natural product, (-)-eurotiumin A, in three steps and 60% overall yield.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Making Northway, Alaska Resilient and Sustainable Through Energy Efficiency and Solar Power

This project implemented energy efficiency measures and installed 6 kW solar arrays on three community buildings in Northway, Alaska, in a collaboration between the Department of Energy - Office of Indian Energy Policy and Programs, the Northway Village Council (NVC), the Tanana Chiefs Conference (TCC), and the Alaska Native Tribal Health Consortium (ANTHC). Northway is a small community in interior Alaska, close to the Canadian border, with high fuel and energy costs: $3.00 per gallon of diesel and $0.56 per kWh, respectively, in 2016, when the project began. The energy efficiency and solar power installation plans aligned with Northway’s long-term energy goals of increasing renewable energy and decreasing reliance on fossil fuels, per the Northway Community Energy Action Plan, the Alaska Interior Regional Energy Plan, and TCC Comprehensive Economic Development Strategy. The project focused on three buildings: (1) the community hall (and later office) building, (2) the washeteria building, and (3) the water/sewer garage. It included multiple directions for energy efficiency measures, such as installing LED lighting upgrades, programmable thermostats, vending machine energy misers, efficient pumps, and adding glycol loops at the water/sewer plant. Since the village has a high potential for solar energy, in order to increase resilience and decrease costs, solar systems were installed on three community buildings. Later, a battery was installed in the community hall to capture solar power produced but not used during the day, and allow the flexibility to use that power during evening and night, further decreasing the reliance on grid power for that building. Electricity savings realized by the village between 2011-2012 and 2018-2019 by improving energy efficiencies in the buildings and adding solar was 23%. This is despite the community hall doubling in size during the same time period. If that is taken into consideration (by adding community hall usage into the 2011-2012 usage one additional time), the energy savings from 2011-2012 to 2018-2019 was 37%.

14 SOLAR ENERGY↗
DOE OSTI2024

Bilayer Ion Trap Design for 2D Arrays

Junctions are fundamental elements that support qubit locomotion in two-dimensional ion trap arrays and enhance connectivity in emerging trapped-ion quantum computers. In surface ion traps they have typically been implemented by shaping radio frequency (RF) electrodes in a single plane to minimize the disturbance to the pseudopotential. However, this method introduces issues related to RF lead routing that can increase power dissipation and the likelihood of voltage breakdown. Here, we propose and simulate a novel two-layer junction design incorporating two perpendicularly rotoreflected (rotated, then reflected) linear ion traps. The traps are vertically separated, and create a trapping potential between their respective planes. The orthogonal orientation of the RF electrodes of each trap relative to the other provides perpendicular axes of confinement that can be used to realize transport in two dimensions. While this design introduces manufacturing and operating challenges, as now two separate structures have to be precisely positioned relative to each other in the vertical direction and optical access from the top is obscured, it obviates the need to route RF leads below the top surface of the trap and eliminates the pseudopotential bumps that occur in typical junctions. Here in this paper the stability of idealized ion transfer in the new configuration is demonstrated, both by solving the Mathieu equation analytically to identify the stable regions and by numerically modeling ion dynamics. Our novel junction layout has the potential to enhance the flexibility of microfabricated ion trap control to enable large-scale trapped-ion quantum computing.

42 ENGINEERING↗