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DOE OSTI2026

QProR: An Efficient Framework for Quantity-of-Interest Based Progressive Retrieval with Guaranteed Error Control

Scientific applications generate an unprecedented volume of data, overwhelming the network and file systems’ bandwidth and posing challenges for efficient and scalable data retrieval and analysis. Progressive data compression offers a promising solution by enabling on-demand retrieval at reduced size. However, existing progressive methods either fail to bound the errors in essential quantities of interest (QoIs) derived from raw data or suffer from suboptimal retrieval efficiency. In this work, we propose QProR, an efficient QoI-based progressive framework that optimizes progressive retrieval for target QoIs. Our key contributions include: (1) a systematic framework that integrates error-controlled lossy compressors with bitplane encoding while decoupling the two processes for high flexibility and adaptability; (2) a novel weighted bitplane encoding method which incorperates QoI knowledge into data refactoring to enhance retrieval efficiency; (3) an optimized retrieval strategy that accounts for the varying impacts of different variables on multivariate QoIs; (4) comprehensive evaluations using six real-world datasets from multiple scientific applications and thorough comparisons against state of the arts. Experimental results demonstrate that QProR achieves up to 80.38% reduction in the retrieval size under the same requested QoI error tolerance, when compared with the best-performing existing methods. When transferring 384 GB of scientific data to remote sites, QProR delivers up to 1.68 × speedup in the end-to-end data transfer performance.

Li, Wenbo [University of Kentucky]↗

DOE OSTI2025

Editors’ Choice—Molten Salt Electrolysis in Chloride Melts for Energy-Efficient Iron Metal Production

This study explores chloride molten salt electrolysis (CMSE) as a promising route for energy-efficient iron metal (Fe) production. Moderate temperature (500 °C) LiCl-KCl molten salts offer excellent thermodynamic stability, high ionic conductivity and diffusivity, and high solubility for FeCl 3 , thereby enabling efficient Fe metal extraction at high electrowinning rates. Here, we demonstrate the two essential steps for converting taconite ore into Fe metal. First, Fe 2 O 3 from taconite pellets was selectively leached in HCl yielding a high-purity FeCl 3 aqueous solution, while the gangue components settled at the bottom. Then, anhydrous FeCl 3 was electrolyzed in a LiCl-KCl eutectic molten salt at 500 °C at high current density (1 A cm −2 ) and at high Coulombic efficiency (>85%). Analysis of the electrowon Fe deposits revealed dendritic structures with purity of >99 wt%, which could be further improved to nearly 100 wt% through arc re-melting. CMSE offers low specific energy consumption (3.7 kWhr kg −1 ), competitive with H 2 -DRI and other electrolytic approaches being pursued globally. Our findings underscore the potential of CMSE as an energy-efficient route for electrosynthesis of Fe metal.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Efficient Capacitive Deionization Using Thin Film Sodium Manganese Oxide

Capacitive deionization (CDI) is an emerging electrochemical desalination technology, which could outperform other desalination technologies if new electrode materials are developed with high electrochemical salt sorption capacities. Recent work has demonstrated improved desalination efficiency using redox-active materials in hybrid CDI (hCDI) electrodes. Here, we report new charge-storage behavior in thin-film sodium manganese oxide (NMO) which promises to enable new levels of desalination efficiency. We deposit thin-film MnO via atomic layer deposition (ALD), and electrochemically convert it to NMO in NaCl(aq). NMO coated electrodes exhibit increases in charge storage capacity up to 170 times higher than uncoated electrodes. Electrochemical quartz crystal microbalance (EQCM) measurements reveal that thin-film NMO leads to the electrochemical removal of 2.3 Na+ ions per electron. This super-stoichiometric removal of Na+ is corroborated by ab initio modeling that predicts a new electrochemical phenomenon at the NMO surface, which we term electron-decoupled ion transfer, or “EDIT.” We also describe a new custom low-volume and low-mass-loading hCDI cell which enables the study of the desalination performance of the EDIT mechanism. An hCDI cell comprised of NMO-coated carbon nanotube (CNT) cathode and Ag nanoparticle-decorated CNT anode yields a ~20-fold improvement in charge storage over bare CNT electrodes. The hCDI cell has a reversible charging efficiency (mol NaCl (mol e-)-1) of 123 ± 5% and a coulombic efficiency of 93%, corroborating our EQCM results and the EDIT mechanism. The EDIT mechanism, as well as the hCDI cell design that enabled its study, promise to hasten the development of hCDI devices with unprecendented performance

ab initio modeling↗

DOE OSTI2020

Nested active learning for efficient model contextualization and parameterization: pathway to generating simulated populations using multi-scale computational models

There is increasing interest in the use of mechanism-based multi-scale computational models (such as agent-based models (ABMs)) to generate simulated clinical populations in order to discover and evaluate potential diagnostic and therapeutic modalities. The description of the environment in which a biomedical simulation operates (model context) and parameterization of internal model rules (model content) requires the optimization of a large number of free parameters. In this work, we utilize a nested active learning (AL) workflow to efficiently parameterize and contextualize an ABM of systemic inflammation used to examine sepsis. Contextual parameter space was examined using four parameters external to the model’s rule set. The model’s internal parameterization, which represents gene expression and associated cellular behaviors, was explored through the augmentation or inhibition of signaling pathways for 12 signaling mediators associated with inflammation and wound healing. We have implemented a nested AL approach in which the clinically relevant (CR) model environment space for a given internal model parameterization is mapped using a small Artificial Neural Network (ANN). The outer AL level workflow is a larger ANN that uses AL to efficiently regress the volume and centroid location of the CR space given by a single internal parameterization. We have reduced the number of simulations required to efficiently map the CR parameter space of this model by approximately 99%. In addition, we have shown that more complex models with a larger number of variables may expect further improvements in efficiency.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Efficient exascale discretizations: High-order finite element methods

Efficient exploitation of exascale architectures requires rethinking of the numerical algorithms used in many large-scale applications. These architectures favor algorithms that expose ultra fine-grain parallelism and maximize the ratio of floating point operations to energy intensive data movement. One of the few viable approaches to achieve high efficiency in the area of PDE discretizations on unstructured grids is to use matrix-free/partially assembled high-order finite element methods, since these methods can increase the accuracy and/or lower the computational time due to reduced data motion. In this paper we provide an overview of the research and development activities in the Center for Efficient Exascale Discretizations (CEED), a co-design center in the Exascale Computing Project that is focused on the development of next-generation discretization software and algorithms to enable a wide range of finite element applications to run efficiently on future hardware. CEED is a research partnership involving more than 30 computational scientists from two US national labs and five universities, including members of the Nek5000, MFEM, MAGMA and PETSc projects. We discuss the CEED co-design activities based on targeted benchmarks, miniapps and discretization libraries and our work on performance optimizations for large-scale GPU architectures. We also provide a broad overview of research and development activities in areas such as unstructured adaptive mesh refinement algorithms, matrix-free linear solvers, high-order data visualization, and list examples of collaborations with several ECP and external applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Data from Highly Efficient Single-Pot Scarless Golden Gate Assembly

Golden Gate assembly is one of the most widely used DNA assembly methods due to its robustness and modularity. However, despite its popularity, the need for BsaI-free parts, the introduction of scars between junctions, as well as the lack of a comprehensive study on the linkers hinders its more widespread use. Here, we first developed a novel sequencing scheme to test the efficiency and specificity of 96 linkers of 4-bp length and experimentally verified these linkers and their effects on Golden Gate assembly efficiency and specificity. We then used this sequencing data to generate 200 distinct linker sets that can be used by the community to perform efficient Golden Gate assemblies of different sizes and complexity. We also present a single-pot scarless Golden Gate assembly and BsaI removal scheme and its accompanying assembly design software to perform point mutations and Golden Gate assembly. This assembly scheme enables scarless assembly without compromising efficiency by choosing optimized linkers near assembly junctions.

Conversion↗

DOE OSTI2026

Data for Mitochondrial ATP Generation is More Proteome Efficient than Glycolysis

Metabolic efficiency profoundly influences organismal fitness. Heterotrophs, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. While respiration is more energy-efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (i.e. faster). Through quantitative flux analysis and proteomics, we find however that mitochondrial respiration is actually more proteome-efficient than aerobic glycolysis. This is shown across yeasts, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which is valuable for hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth, but outgrow respiratory cells in oxygen limitation. Thus, aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.

Metabolomics↗

DOE OSTI2023

Integrated SOAs enable energy-efficient intra-data center coherent links

Coherent optical links are becoming increasingly attractive for intra-data center applications as data rates scale. Realizing the era of high-volume short-reach coherent links will require substantial improvements in transceiver cost and power efficiency, necessitating a reassessment of conventional architectures best-suited for longer-reach links and a review of assumptions for shorter-reach implementations. In this work, we analyze the impact of integrated semiconductor optical amplifiers (SOAs) on link performance and power consumption, and describe the optimal design spaces for low-cost and energy-efficient coherent links. Placing SOAs after the modulator provide the most energy-efficient link budget improvement, up to 6 pJ/bit for large link budgets, despite any penalties from nonlinear impairments. Increased robustness to SOA nonlinearities makes QPSK-based coherent links especially attractive, and larger supported link budgets enable the inclusion of optical switches, which could revolutionize data center networks and improve overall energy efficiency.

Maharry, Aaron (ORCID:0000000273732697)↗

DOE OSTI2020

Maximizing the external radiative efficiency of hybrid perovskite solar cells

Despite rapid advancements in power conversion efficiency in the last decade, perovskite solar cells still perform below their thermodynamic efficiency limits. Non-radiative recombination, in particular, has limited the external radiative efficiency and open circuit voltage in the highest performing devices. We review the historical progress in enhancing perovskite external radiative efficiency and determine key strategies for reaching high optoelectronic quality. Specifically, we focus on non-radiative recombination within the perovskite layer and highlight novel approaches to reduce energy losses at interfaces and through parasitic absorption. By strategically targeting defects, it is likely that the next set of record-performing devices with ultra-low voltage losses will be achieved.

14 SOLAR ENERGY↗

DOE OSTI2020

National Mandates Won’t Save Us!: How to Design Energy Efficiency Policies that Address Institutional Barriers to Change

There are many national policies aimed at driving an increase in energy efficiency (EE) implementation. But how effective are they? Over the past 20 years, the U.S. government has established five legal authorities mandating federal agencies to prioritize energy-efficient products when purchasing. As the largest single buyer of energy-consuming products, energy-efficient purchasing across the federal sector would result in huge energy savings and emissions reductions. Despite this, our research has found that only ~55% of federal purchases currently meet existing requirements. If national mandates are not enough to ensure that federal agencies are buying efficient products, what is? To answer this question, we surveyed 161 procurement and sustainability staff from 26 different federal agencies. Findings revealed that several institutional factors (i.e., the roles, rules, and tools within an organization) play a key role in determining how likely federal buyers are to prioritize EE. Ensuring that federal agencies comply with existing EE requirements is foundational to achieving a clean energy future. This will require more than national mandates, but also the design of policies that successfully identify and address the institutional factors that must be changed in order to increase EE implementation. This paper presents an overview of the data collection and analysis methods for our study, as well as key survey findings and the insights they offer for overcoming institutional barriers to compliance with existing EE requirements. We conclude by discussing how these strategies can be broadly applied to improve the design of EE policies in the U.S. and beyond.

Morabito, Molly↗

DOE OSTI2017

1366 Project Automate: Enabling Automation for <$0.10/W High-Efficiency Kerfless Wafers Manufactured in the US

For photovoltaic (PV) manufacturing to thrive in the U.S., there must be an innovative core to the technology. Project Automate builds on 1366’s proprietary Direct Wafer® kerfless wafer technology and aims to unlock the cost and efficiency advantages of thin kerfless wafers. Direct Wafer is an innovative, U.S.-friendly (efficient, low-labor content) manufacturing process that addresses the main cost barrier limiting silicon PV cost-reductions – the 35-year-old grand challenge of manufacturing quality wafers (40% of the cost of modules) without the cost and waste of sawing. This simple, scalable process will allow 1366 to manufacture “drop-in” replacement wafers for the $10 billion silicon PV wafer market at 50% of the cost, 60% of the capital, and 30% of the electricity of conventional casting and sawing manufacturing processes. This SolarMat project developed the Direct Wafer processes’ unique capability to tailor the shape of wafers to simultaneously make thinner AND stronger wafers (with lower silicon usage) that enable high-efficiency cell architectures. By producing wafers with a unique target geometry including a thick border (which determines handling characteristics) and thin interior regions (which control light capture and electron transport and therefore determine efficiency), 1366 can simultaneously improve quality and lower cost (using less silicon).

14 SOLAR ENERGY↗

DOE OSTI2017

Go Pink! The Effect of Secondary Quanta on Detective Quantum Efficiency

Photons are never directly observable. Consequently, we often use photoelectric detectors (eg CCDs) to record associated photoelectrons statistically. Nonetheless, it is an implicit goal of radiographic detector designers to achieve the maximum possible detector efficiency1. In part the desire for ever higher efficiency has been due to the fact that detectors are far less expensive than associated accelerator facilities (e.g. DARHT and PHERMEX2). In addition, higher efficiency detectors often have better spatial resolution. Consequently, the optimization of the detector, not the accelerator, is the system component with the highest leverage per dollar. In recent years, imaging scientists have adopted the so-called Detective Quantum Efficiency, or DQE as a summary measure of detector performance. Unfortunately, owing to the complex nature of the trade-space associated with detector components, and the natural desire for simplicity and low(er) cost, there has been a recent trend in Los Alamos to focus only on the zerofrequency efficiency, or DQE(0), when designing such systems. This narrow focus leads to system designs that neglect or even ignore the importance of high-spatial-frequency image components. In this paper we demonstrate the significant negative impact of these design choices on the Noise Power Spectrum1 (NPS) and recommend a more holistic approach to detector design. Here we present a statistical argument which indicates that a very large number (>20) of secondary quanta (typically visible light and/or recorded photo-electrons) are needed to take maximum advantage of the primary quanta (typically x-rays or protons) which are available to form an image. Since secondary particles come in bursts, they are not independent. In short, we want to maximize the pink nature of detector noise at DARHT.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Improved heavy-duty vehicle fuel efficiency in India, benefits, costs and environmental impacts

The main objectives of this analysis are to examine the benefits and costs of fuel-saving technologies for new heavy-duty vehicles (HDVs) in India over the next 10 years and, to explore how various scenarios for the deployment of vehicles with these technologies will impact petroleum consumption and carbon dioxide (CO 2 ) emissions over the next three decades. The study team developed simulation models for three representative HDV types—a 40-tonne tractor-trailer, 25-tonne rigid truck, and 16-tonne transit bus—based on top-selling vehicle models in the Indian market. The baseline technology profiles for all three vehicles were developed using India-specific engine data and vehicle specification information from manufacturer literature and input from industry experts. For each of the three vehicles we developed a comprehensive set of seven efficiency technology packages drawing from five major areas: engine, transmission and driveline, tires, aerodynamics, and weight reduction. Our analysis finds that India has substantial opportunity to improve HDV fuel efficiency levels using cost-effective technologies. Results from our simulation modeling of three representative HDV types—a tractor-trailer, rigid truck, and transit bus—reveal that per-vehicle fuel consumption reductions between roughly 20% and 35% are possible with technologies that provide a return on the initial capital investment within 1 to 2 years. Though most of these technologies are currently unavailable in India, experiences in other more advanced markets such as the US and EU suggest that with sufficient incentives and robust regulatory design, significant progress can be made in developing and deploying efficiency technologies that can provide real-world fuel savings for new commercial vehicles in India over the next 10 years. Bringing HDVs in India up to world-class technology levels will yield substantial petroleum and GHG reductions. By 2030, the fuel and CO2 reductions of the scenarios range from 10% to 34%, and at the end of 2050, these reductions grow to 13% and 41%. If we constrain the analysis to select the most efficient technology package that provides the fleets with payback times of 3 years or less, there are annual fleet-wide savings of roughly 11 MTOE of diesel and 34 MMT of CO 2 in 2030, and this grows to 31 MTOE and 97 MMT by 2050.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

High Efficiency Heat Exchanger for High Temperature and High Pressure Applications

CompRex, LLC (CompRex) specializes in the design and manufacture of compact heat exchangers and heat exchange reactors for high temperature and high pressure applications. CompRex’s proprietary compact technology not only increases heat exchange efficiency by at least 25 % but also reduces footprint by at least a factor of ten compared to traditional shell-and-tube solutions of the same capacity and by 15 to 20 % compared to other currently available Printed Circuit Heat Exchanger (PCHE) solutions. As a result, CompRex’s solution is especially suitable for Brayton cycle supercritical carbon dioxide (sCO2) systems given its high efficiency and significantly lower capital and operating expenses. CompRex has already successfully demonstrated its technology and ability to deliver with a pilot-scale compact heat exchanger that was under contract by the Naval Nuclear Laboratory for sCO2 power cycle development. The performance tested unit met or exceeded the thermal and hydraulic specifications with measured heat transfer between 95 to 98 % of maximum heat transfer and temperature and pressure drop values all consistent with the modeled values. CompRex’s vision is to commercialize its compact technology and become the leading provider for compact heat exchangers and heat exchange reactors for various applications including Brayton cycle sCO2 systems. One of the limitations of the sCO2 Brayton power cycle is the design and manufacturing of efficient heat exchangers at extreme operating conditions. Current diffusion-bonded heat exchangers have limitations on the channel size through which the fluid travels, resulting in excessive solid material per heat exchanger volume. CompRex’s design allows for more open area and shorter fluid proximity for increased heat transfer efficiency while sustaining the structural integrity needed for the application. CompRex is developing a novel improvement to its current heat exchanger design where fluids are directed to alternating channels so that each fluid is fully surrounded by the opposing fluid. As compared to similar existing compact heat exchangers, the new design converts most secondary surface area to primary surface area, eliminating fin inefficiencies. CompRex requests that all technical information about the heat exchanger designs be protected as proprietary information. To honor that request, only non-proprietay summaries are included in this report.

47 OTHER INSTRUMENTATION↗

DOE OSTI2018

The Cost of Saving Electricity Through Energy Efficiency Programs Funded by Utility Customers: 2009–2015

The average cost to utilities to save a kilowatt-hour (kWh) in the United States is 2.5 cents, according to the most comprehensive assessment to date of the cost performance of energy efficiency programs funded by electricity customers. These costs are similar to those documented earlier. Cost-effective efficiency programs help ensure electricity system reliability at the most affordable cost as part of utility planning and implementation activities for resource adequacy. Building on prior studies, Berkeley Lab analyzed the cost performance of 8,790 electricity efficiency programs between 2009 and 2015 for 116 investor-owned utilities and other program administrators in 41 states. The Berkeley Lab database includes programs representing about three-quarters of total spending on electricity efficiency programs in the United States.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

NanoStructured bulk thermoelectric generator for efficient power harvesting for self-powered sensor network

The goal of the Nuclear Energy Enabling Technology Research Project is to develop efficient and reliable thermoelectric (TE) generators for self-powered wireless sensor nodes (WSNs) for nuclear applications. The power harvesting technology has crosscutting significance to all United States Department of Energy Office of Nuclear Energy research and development programs, as it will enable self-powered WSNs in multiple nuclear reactor designs and spent fuel storage facilities using thermal energy available in a nuclear power plant or spent fuel storage facility. This project addresses an important technology gap that exists in truly realizing WSNs due to the need for cables to connect to external power supplies and develop TE power harvesting devices to deliver sufficient power to drive the WSNs. The outcomes of the project will lead to significant advancement in sensors and instrumentation technology, reducing cost, improving monitoring reliability, and therefore enhancing safety. The self-powered WSNs could support the long-term safe and economical operation of all reactor designs and fuel cycle concepts, as well as spent fuel storage and many other nuclear science and engineering applications. The research is based on recent breakthroughs in high-performance nanostructured bulk (nanobulk) half-Heusler and bismuth telluride thermoelectric materials that enable high-efficiency and high-power-density direct heat-to-electricity conversion over a wide temperature range. The nanobulk TE materials that the research team has already developed yield up to a 50% increase in the TE figure of merit, ZT, compared with state-of-the-art bulk counterparts. In addition to increased efficiency, the nanostructured materials are of potentially enhanced radiation tolerance due to the increased interface densities at the nanoscale grain boundaries that serves as efficient sinks to annihilate radiation-induced, freely-migrating structural defects. This report summarizes major technical results the team achieved in this three-year project, with a focus on the results obtained in the third year of the project. The report includes results on thermoelectric materials fabrication and optimization, irradiation effect on thermoelectric materials performance, thermoelectric device simulation, fabrication and testing, wireless sensor node system simulation, and the demonstration of a wireless sensor node powered by thermoelectric generators.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Relative Credits for Extra Efficiency Code Measures

Energy codes have traditionally contained mandatory and prescriptive items. Mandatory measures must be complied with in all situations while prescriptive measures can be traded with other efficiency measures by following a performance path. Recent editions of the International Energy Conservation Code (IECC) also contain additional efficiency packages, where one or more optional measures must be selected to satisfy an ‘additional’ efficiency requirement. Such a structure is currently employed in section C406 of the IECC, and similar approaches have been considered for ASHRAE Standard 90.1 as well as state building codes. This approach has the advantage of providing increasing levels of performance, while maintaining flexibility in allowing the designer to optimize the most appropriate technologies and efficiency measured based on the attributes of a particular project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2019

Challenges and Recommended Policies for Simultaneous Global Implementation of Low-GWP Refrigerants and High Efficiency in Room Air Conditioners

Increasing incomes, electrification, and urbanization—as well as a warming world—are driving up the global stock of air conditioners (ACs), particularly in emerging economies with hot climates. AC energy consumption is expected to increase substantially as the global stock of room ACs rises to 1.5 billion in 2030 and 2.5 billion in 2050. Hence, improving AC energy efficiency will be critical to reducing AC energy, cost (consumer lifecycle cost, electricity generation cost, etc.), peak load, and emissions impacts. The 2016 Kigali Amendment to the Montreal Protocol offers an opportunity to improve AC energy efficiency in tandem with the phasedown of high global warming potential (GWP) hydrofluorocarbon (HFC) refrigerants. Based on the most recent information, a literature review, and interviews with manufacturers and industry experts, we find the main barriers to deploying high-efficiency ACs include concerns about market demand and cost, which could be mitigated by appropriately improved design of market-transformation programs such as standards and labeling, incentive, and procurement programs. The main barriers to the low-GWP refrigerant transition include the need for timely revision of safety standards and associated costs for capacity-building activities allowing safe use of low-GWP refrigerants in ACs. Policy action and the market transformation can be accelerated by advancing the refrigerant transition and efficiency improvements in parallel.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗