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At least 73 records · Page 4

Equitable Strategies for Residential Building Energy Efficiency and Electrification in San José, California

Hotter summers, heat waves, wildfires, and droughts are already affecting San Jose residents, with historically marginalized communities impacted first and worst. The City of San Jose has ambitious goals to make the city climate-neutral by 2030 and serve as an example for cities to accelerate climate action around the world. Electrifying and decarbonizing residential buildings are important priorities to achieve San Jose's plans to reach carbon neutrality while enabling residents to live the "Good Life 2.0" - a vision that aligns with community-identified priorities of safety, health, freedom, community, and positive experiences. This technical assistance built upon the Electrify San Jose: Framework for Existing Building Electrification to identify actionable strategies to make single- and multi-family buildings both energy-efficient and all-electric. This report is intended to provide the San Jose Climate Smart team and their partners with relevant data, insights, and actionable analysis to aid in-depth and nuanced engagements with key stakeholders. In particular, the findings in this report highlight opportunities and challenges for San Jose City Council, residents, building owners, developers, financial institutions, and utility partners instrumental in building support and earning buy-in for energy efficiency and electrification upgrades in existing buildings.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Equitable Strategies for Residential Building Energy Efficiency and Electrification in San José, California [Slides]

Hotter summers, heat waves, wildfires, and droughts are already affecting San Jose residents, with historically marginalized communities impacted first and worst. The City of San Jose has ambitious goals to make the city climate-neutral by 2030 and serve as an example for cities to accelerate climate action around the world. Electrifying and decarbonizing residential buildings are important priorities to achieve San Jose's plans to reach carbon neutrality while enabling residents to live the "Good Life 2.0" - a vision that aligns with community-identified priorities of safety, health, freedom, community, and positive experiences. This technical assistance built upon the Electrify San Jose: Framework for Existing Building Electrification to identify actionable strategies to make single- and multi-family buildings both energy-efficient and all-electric. This report is intended to provide the San Jose Climate Smart team and their partners with relevant data, insights, and actionable analysis to aid in-depth and nuanced engagements with key stakeholders. In particular, the findings in this report highlight opportunities and challenges for San Jose City Council, residents, building owners, developers, financial institutions, and utility partners instrumental in building support and earning buy-in for energy efficiency and electrification upgrades in existing buildings.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Variation Tolerant and Energy-Efficient Charge Domain Compute-in-Memory Array with Binary and Multi-Level Cell Ferroelectric FET

Here, in this work, we present a variation-tolerant and energy-efficient charge-domain Ferroelectric FET (FeFET) based Compute-in-Memory (CiM) array design that is compatible with both binary and multi-level cell memory sensing. We demonstrate that: 1) by exploiting FeFET as a nonvolatile switch, its high ON/OFF ratio in the subthreshold region can suppress the error introduced by the inaccurate ON state conductance, thus realizing robust CiM operations, unlike the current-domain CiM design where the computation results is highly sensitive to the device conductance variation; 2) by leveraging a dense dynamic random access memory (DRAM)-like 1FeFET1C cell structure, the proposed design benefits from the existing high density DRAM establishment while also significantly relaxing the capacitor retention and transistor leakage requirement; 3) the charge-domain CiM supports both binary FeFET with minimum overhead and MLC FeFET with tolerable latency for MLC state sensing, whose efficacy is validated experimentally on both cell-level and array-level; 4) the proposed CiM shows much better device variation resilience than conventional current-domain CiM, and also improves inference accuracy. Macro-level evaluation results demonstrate significantly higher energy efficiency and area efficiency compared to prior CiM works.

Duan, Jiahui [University of Notre Dame, IN (United↗

Single-Cell Universal Logic-in-Memory Using 2T-nC FeRAM: An Area and Energy-Efficient Approach for Bulk Bitwise Computation

This work presents a novel approach to configure 2T-nC ferroelectric RAM (FeRAM) for performing single cell logic-in-memory operations, highlighting its advantages in energy-efficient computation over conventional DRAM-based approaches. Unlike conventional 1T-1C dynamic RAM (DRAM), which incurs refresh overhead, 2T-nC FeRAM offers a promising alternative as a non-volatile memory solution with low energy consumption. Our key findings include the potential of quasi-nondestructive readout (QNRO) sensing in 2T-nC FeRAM for logic-in-memory (LiM) applications, demonstrating its inherent capability to perform inverting logic without requiring external modifications, a feature absent in traditional 1T-1C DRAM. We successfully implement the MINORITY function within a single cell of 2T-nC FeRAM, enabling universal NAND and NOR logic, validated through SPICE simulations and experimental data. Additionally, the research investigates the feasibility of 3D integration with 2T-nC FeRAM, showing substantial improvements in storage and computational density, facilitating bulk-bitwise computation. Our evaluation of eight real-world, data-intensive applications reveals that 2T-nC FeRAM achieves 2× higher performance and 2.5× lower energy consumption compared to DRAM. Furthermore, the thermal stability of stacked 2T-nC FeRAM is validated, confirming its reliable operation when integrated on a compute die. These findings emphasize the advantages of 2T-nC FeRAM for LiM, offering superior performance and energy efficiency over conventional DRAM.

36 MATERIALS SCIENCE↗

A mathematical design framework for membrane pre-concentration in energy-efficient recovery of fermentation products

Due to the dilute nature of products manufactured via fermentation and cell-free bioprocessing, dewatering is a common unit operation in downstream processing (DSP) for bioproduct recovery, but it is typically energy intensive. To improve DSP energy efficiency for bio-based small molecules, integrating high-pressure membrane pre-concentration is a promising process option. However, this approach is typically constrained by a tradeoff between concentration factor (CF) and product recovery (PR), namely increasing the CF typically results in greater product loss, and vice versa. Here we developed a model that enables process design guidelines to: (i) identify scenarios in which the additional energy consumption and product loss from membrane pre-concentration are justified for use in DSP, and (ii) determine the optimal CF that minimizes process specific energy consumption. We compared the energy consumption of high-pressure membrane-integrated processes to evaporation-only processes and applied the model to an experimental case study for the separation and purification of butyric acid from Clostridium tyrobutyricum fermentation using an in situ product recovery (ISPR) process. The model estimated that integrating a tangential-flow reverse osmosis (RO) pre-concentration unit could reduce process energy consumption up to 45%. The use of advanced membrane pre-concentration technologies, such as negative rejection membranes and organic solvent reverse osmosis (OSRO), have the potential to further reduce the overall process specific energy consumption up to 96%, projected based on modeling. Overall, membrane pre-concentration, especially when strategically integrated prior to an evaporation step with optimized process conditions, holds significant potential for improving DSP energy efficiency, particularly in applications requiring substantial solvent removal for product recovery from dilute mixtures.

09 BIOMASS FUELS↗

Chloride Molten Salt Electrolysis Enables Integrated and Energy-Efficient Process for NdFeB Magnet Fabrication

Rare-earth elements (REEs) have been identified by NATO, the USDOE, and USGS as critical materials, i.e., materials which have significant demand yet pose supply-chain risks. Many of the existing processes for separations, metallization, and final parts production used across the REE supply chain involve energy intensive steps. For example, neodymium (Nd or NdPr) is produced using oxyfluoride electrolysis of Nd 2 O 3 , which requires hydrofluoric acid to produce a key electrolyte component (NdF 3 ) and generates undesired perfluorocarbon (PFC) gases. Such challenges make securing a resilient supply chain for NdFeB permanent magnets in countries like the United States prohibitively difficult. Here, we propose a chloride-based MSE process that circumvents these challenges, delivering high-purity NdPr from a (NdPr)Cl 3 feed from upstream REE separations. This eliminates environmentally-damaging steps of oxalate or carbonate precipitation and calcination, and enables superior production rates due to greater solubility of (NdPr)Cl 3 in chloride melts compared to Nd 2 O 3 . We show that CMSE generates high-purity NdPr (99.4 wt.%) while being energy-efficient (~ 6 kWh/kg-Nd). NdPr from CMSE was used to fabricate a NdFeB magnet with an excellent maximum energy product (> 40 MGOe), comparable to commercially available NdFeB magnets. This establishes CMSE as a leading approach for integrated, energy-efficient NdFeB magnet production.

Materials science↗

AI-Powered Knowledge Graphs for Neuromorphic and Energy-Efficient Computing

The surge in scientific literature obscures breakthroughs and hinders the discovery of new research paths. We propose an artificial intelligence (AI) powered framework using large language models (LLMs) and knowledge graphs (KGs) to automate parts of scientific discovery, focusing on energy-efficient AI circuits. Our hybrid approach combines LLMs, structured data, and ontology-based reasoning to construct a comprehensive knowledge graph that integrates insights across computational neuroscience, spiking neuron models, learning rules, architectural motifs, and neuromorphic device technologies. This multi-domain representation enables the generation of hypotheses that connect biological function with implementable, energy-efficient hardware architectures. Using KG embeddings and graph neural networks, the framework generates hypotheses for novel circuits, validates them through optimization on exascale HPC systems, and with tools like SuperNeuro and Fugu, the most promising designs will be prototyped in hardware. This open-source system aims to accelerate discoveries and bridging neuroscience with hardware innovation, drive collaboration, and unlock new opportunities in low-power AI computing.

Gautam, Ashish [ORNL]↗

Energy Efficiency Analysis and Grid Service Results for Commercial Buildings using the VOLTRON IoT Platform

In fiscal year 2021 (FY21), the Commercial Buildings Integration Program (CBI) within the Building Technologies Office (BTO), funded PNNL to conduct a field evaluation of the AIRCx and ILC using an Internet-of-Things (IoT) platform, VOLTTRON. The primary goal of the project is to show that software solutions deployed and delivered through an IoT-platform can identify energy efficiency opportunities and manage peak load (beyond the traditional demand response) in commercial buildings. There are also two secondary goals: 1) show that the energy efficiency solutions will result in identification of significant savings opportunities (10% to 30%) as well as energy cost reductions (10% to 15%) by managing the peak load in commercial buildings, and 2) show that an IoT-based software solution is more cost-effective compared to a manual process in meeting the Re-tuning/retro commissioning (RCx) mandates and there is a pathway for broader adoption of this approach. This report provides AIRCx and ILC results for two building located in District of Columbia managed by the energy service provider Intellimation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Integration of hydrophobic gas diffusion layers for zero-gap electrolyzers to enable highly energy-efficient CO 2 electrolysis to C 2 products

Electrochemical CO 2 reduction (eCO2R) is an attractive route for mitigating global CO 2 emissions while producing value-added chemicals. Ethylene is one product of eCO2R and is an essential industrial precursor with a global market of $230 billion. The large-scale implementation of C 2 H 4 -selective CO 2 electrolyzers remains challenging because of low energy efficiencies. In this work, we develop the design principles necessary for incorporating an expanded polytetrafluoroethylene (ePTFE) electrode into a zero-gap electrolyzer while simultaneously developing an integrated electrical front contact that reduces the ohmic resistances inherent to electrically insulating gas diffusion layers. By co-designing the catalyst layer, gas diffusion medium, and operating conditions for a zero-gap ePTFE gas diffusion electrode (GDE), we achieved a full-cell voltage of 2.5 V at 200 mA cm −2 at 25 cm 2 geometric area cell with Faradaic efficiencies of 48% for ethylene and 40% for ethanol. This work highlights strategies for developing a scalable, stable, and highly energy-efficient eCO2R for C 2 products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Human Factors and Technologies Design to Improve User Acceptance of Pooled Rideshare for Increasing Transportation System Energy Efficiency

This multi-year project delivered a comprehensive, human-factors-driven framework to understand, model, and improve pooled rideshare (PR) adoption in the United States. Through three large-scale national survey studies involving more than 16,000 participants across multiple cities and demographic groups, the research established one of the most extensive datasets to date on user perceptions, behavioral barriers, and service expectations related to pooled rideshare. These data revealed key human factors barriers of user acceptance of PR and suggested potential actionable experience optimizations that could lead to increased PR usage. This foundational knowledge guided the development of novel human-factors models and behavioral choice models that quantify how psychological, demographic, and trip-level factors influence willingness to pool. Building on these empirical insights, the project developed advanced behavioral modeling tools, including mixed logit and integrated choice and latent variable models, to capture both observable and latent influences on PR adoption. These models significantly improved the ability to predict riders’ acceptance of pooled trips, explaining choice heterogeneity through latent constructs such as safety, service experience, privacy concerns, time sensitivity, and environmental attitudes. Together, these models provide a robust analytical foundation for designing PR systems that more effectively meet user needs. The project translated human-factors insights and behavioral models into actionable technology innovations by extending POLARIS—an agent-based, activity-based travel simulation platform—into a fully functional pooled rideshare simulation environment. New PR modules, acceptance models, and regional scenarios were implemented for Greenville, SC and Austin, TX, enabling high-fidelity validation of algorithmic strategies under realistic demand and traffic conditions. The simulation platform supported the development and evaluation of adaptive discount-based assignment algorithms, enhanced willingness-to-pay formulations, demographic-aware incentive mechanisms, and a proactive joint assignment and repositioning strategy. Simulation results demonstrated substantial gains in pooling uptake, average vehicle occupancy, energy efficiency, and fleet profitability. In Greenville, pooling adoption more than doubled, while reductions in vehicle-miles traveled and energy consumption were significant. In Austin, pooling improvements were achieved with minimal service-quality trade-offs, and profitability increased across all fleet sizes. Through this research, we developed a comprehensive understanding of the human factors barriers that limit user acceptance of pooled rideshare services. These insights enabled the design of human-factors-aware pooled rideshare technologies that more effectively address user concerns and improve adoption rates. By integrating these models into an advanced agent-based simulation framework, we demonstrated that higher adoption of pooled rideshare can lead to measurable improvements in energy efficiency and system performance. Together, these contributions establish a validated pathway from human-centered analysis to technology development and energy-saving outcomes, supporting national goals for more sustainable and efficient mobility systems.

Jia, Yunyi↗

Bio-Inspired Energy-Efficient Nanofabricated Electrical Contacts

Nanoscale electrical contacts, especially those between materials of dissimilar electronic properties, often represent one of the main causes of drops in energy transfer efficiency. They are also among the sources of above-threshold noise, and their performance often decreases over the lifetime of the nanodevices. Scale-down limitations from mesoscopic to nanoscale devices, and likewise, of nanoscale to quantum-scale devices are also impeded by contacts’ quality. Making more reliable, energy-efficient electrical contacts is among the goals of the nanoelectronics research within the framework of energy-efficient electronic systems. This report focuses on the design, nanofabrication, and testing of novel shapes of electrical contacts. Lithography and nanofabrication were utilized to mimic the approximate shape of insect setae for mesoscale contacts design. The contacts are tested for elementary charge transport via I–V curves and for the broadband, 1/f noise. Tests show that contacts design leads to a measurable decrease in the energy necessary to operate a contact as a switch by at least 12–20%, depending on temperature, while broadband noise shows measurably lower power spectra, for bio-inspired contacts. The proposed method is open to modifications and improvements as required by various on-chip applications.

36 MATERIALS SCIENCE↗

Oneida Indian Nation Facility Energy Efficiency Project (Final Technical Report)

The Oneida Indian Nation (“Oneida”) implemented a comprehensive energy efficiency project across nearly 30 facilities over the course of the project period. Grounded in findings from a 2018 energy audit, the project installed LED lighting, high-efficiency HVAC systems, programmable thermostats, variable speed drives, and kitchen exhaust controls across 28 Nation facilities and the Turning Stone Resort and Casino (TSRC) campus.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales

As we enter the exascale computing era, efficiently utilizing power and optimizing the performance of scientific applications under power and energy constraints has become critical and challenging. We propose a low-overhead autotuning framework to autotune performance and energy for various hybrid MPI/OpenMP scientific applications at large scales and to explore the tradeoffs between application runtime and power/energy for energy efficient application execution, then use this framework to autotune four ECP proxy applications—XSBench, AMG, SWFFT, and SW4lite. Our approach uses Bayesian optimization with a Random Forest surrogate model to effectively search parameter spaces with up to 6 million different configurations on two large-scale HPC production systems, Theta at Argonne National Laboratory and Summit at Oak Ridge National Laboratory. The experimental results show that our autotuning framework at large scales has low overhead and achieves good scalability. Using the proposed autotuning framework to identify the best configurations, we achieve up to 91.59% performance improvement, up to 21.2% energy savings, and up to 37.84% EDP (energy delay product) improvement on up to 4096 nodes.

Autotuning↗

Energy Efficiency Improvement Approaches in Ice Related Processes

Application and development of energy efficient techniques to separate ice from different surfaces and substrates is of significant value in the context of building equipment performance. A hybrid approach to help dislocate the ice layer using advanced materials and ultrasonic vibration to lower ice adhesion strength was investigated. Application of advanced polymer materials in lowering the adhesion strength of ice was confirmed where the measured strength was lowered by 50-70% depending on the material and geometry. Additionally, utilization of induced ultrasonic vibration in further lowering the ice harvesting energy was confirmed on multiple materials and geometries. Durability of the coating enhancement was also confirmed in a thermal cycling test under realistic operating conditions. Integration of these technical approaches was implemented and validated in commercial ice makers showing energy consumption reduction by ~ 15% to 30% depending on the technical enhancement.

Cheekatamarla, Praveen↗

Energy Efficient Mobility Systems (2023 Annual Progress Report)

This document summarizes the progress of VTO Energy Efficient Mobility Systems projects supported during the fiscal year 2023. DOE conducts research to understand how the changing mobility landscape will affect transportation energy consumption and identifies opportunities to create more efficient, affordable, reliable, accessible, equitable, and secure transportation options that enhance mobility for individuals and businesses. Within EERE, the EEMS Program is responsible for this research portfolio. This APR describes work that the EEMS Program conducted during FY 2023 in support of the EEMS Program goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy Efficiency for the Wastewater Industry

This information sheet discusses the technology pillar, Energy Efficiency, as a pathway toward improving wastewater infrastructure sustainability and resiliency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy Efficiency Analysis for Residents of North Birmingham, Alabama

The community of North Birmingham, Alabama, participated in the Communities LEAP pilot program. As part of this technical assistance pilot, residential buildings, energy efficiency, and electrification were analyzed. This factsheet has a summary of the results.

building envelope↗