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At least 235 records · Page 13

Adopting occupancy-based HVAC controls in commercial building energy codes: Analysis of cost-effectiveness and decarbonization potential

Recent research has shown the energy-saving potential of occupancy-based HVAC controls (OBCs) in commercial buildings. However, building energy codes have not fully adopted this technology. This study aims to evaluate the cost-effectiveness and decarbonization benefits of OBCs and provide guidance for integrating occupancy sensors into building energy code development. To this end, a parametric simulation using EnergyPlus and a nationwide cost-effectiveness analysis are carried out considering three building types and 40 representative cities in the U.S. Here, the findings reveal that the current cost-effectiveness performance of OBCs is limited due to the high cost of occupancy sensors. However, incorporating the societal cost of carbon factor in future energy and environmental policy could greatly enhance the actual cost-effectiveness performance. Besides, a reduction in the cost of occupancy sensors to approximately 60% of the current price level could also greatly shorten the discounted payback period of OBCs. Additionally, OBCs demonstrate significant potential in building decarbonization, with potential CO 2 emissions savings of more than 5.56 million metric tons across the three building types and 40 selected cities. Finally, policy implications are provided to guide the incorporation of occupancy-based HVAC controls in future energy codes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Breakthrough innovations in carbon dioxide mineralization for a sustainable future

Greenhouse gas emissions and climate change concerns have prompted worldwide initiatives to lower carbon dioxide (CO 2 ) levels and prevent them from rising in the atmosphere, thereby controlling global warming. Effective CO 2 management through carbon capture and storage is essential for safe and permanent storage, as well as synchronically meeting carbon reduction targets. Lowering CO 2 emissions through carbon utilization can develop a wide range of new businesses for energy security, material production, and sustainability. CO 2 mineralization is one of the most promising strategies for producing thermodynamically stable solid calcium or magnesium carbonates for long-term sequestration using simple chemical reactions. Current advancements in CO 2 mineralization technologies, focusing on pathways and mechanisms using different industrial solid wastes, including natural minerals as feedstocks, are briefly discussed. However, the operating costs, energy consumption, reaction rates, and material management are major barriers to the application of these technologies in CO 2 mineralization. Further, the optimization of operating parameters, tailor-made equipment, and smooth supply of waste feedstocks require more attention to make the carbon mineralization process economically and commercially viable. Here, carbonation mechanisms, technological options to expedite mineral carbonation, environmental impacts, and prospects of CO 2 mineralization technologies are critically evaluated to suggest a pathway for mitigating climate change in the future. The integration of industrial wastes and brine with the CO 2 mineralization process can unlock its potential for the development of novel chemical pathways for the synthesis of calcium or magnesium carbonates, valuable metal recovery, and contribution to sustainability goals while reducing the impact of global warming.

54 ENVIRONMENTAL SCIENCES↗

Improving Efficiency of Off-Road Vehicles by Novel Integration of Electric Machines and Advanced Combustion Engines

Modern off-road equipment will increasingly rely on electrified implements that will deliver precision control with a smaller footprint than hydraulics. The primary energy converter, however, will be an onboard reciprocating internal combustion engine because of the power density of hydrocarbon fuels in comparison to electrical energy storage and the remote locations where much of this equipment is deployed. Adding energy storage and electric machines creates opportunities to improve efficiency while reducing emissions. This program investigated approaches to take advantage of the extra flexibility that an enhanced electrical system to enable high-efficiency, low-emissions combustion technologies. The current program evaluated hybridization of both the torque application and air-handling systems to maximize efficiency while minimizing cost. This program designed, analyzed and tested a hybrid off-road vehicle consisting of a series electric powertrain with energy storage, an electrified air system, and a 33% downsized diesel engine. Detailed comparisons were made between the base powertrain and the developed powertrain using powertrain simulations, engine testing, and vehicle testing. The key results of the study are: • The resulting vehicle reduces fuel consumption by 5% to 15% at equal productivity. The primary improvements were due to recovery of regenerative braking losses for cycles where large transients are encountered. • The electrified air system was an enabler to allow engine downsizing. This was most important for duty-cycles where the engine primarily operated at moderate loads and had few low speed high torque conditions. • Engine level improvements showed re-optimization of the powertrain is possible when electrified air handing is available. Increased exhaust gas recirculation and advanced injection timing allowed up to a 15% reduction in brake specific fuel consumption at equal NOx and transient response. Compared to the larger engine, the downsized engine achieves up to an 18% reduction in brake specific fuel consumption over the non-road transient cycle. • The life cycle analysis and total cost of ownership study showed that the hybrid powertrain has the potential to reduce 5-year CO2 and total cost of ownership by ~6% over the baseline vehicle. The results also indicated that a pure battery electric vehicle is not feasible in this application and is likely to increase the CO2 emissions due to the CO2 from battery production. A hybrid powertrain with low carbon fuels shows the potential to substantially reduce CO2 and total cost of ownership.

02 PETROLEUM↗

ELECTRIFICATION OF A HEAVY-DUTY OFF-ROAD MATERIAL HANDLER: ENERGY SAVINGS AND EMISSION REDUCTIONS

Federal regulations are driving the adoption of electrification technologies to reduce carbon dioxide equivalent (CO2e) emissions, a metric that quantifies the global warming potential of various greenhouse gases in terms of carbon dioxide (CO2). Although no specific CO2 regulations exist for heavy-duty off-road machines, future reductions are likely, given stricter emissions standards for on-road vehicles. The heavy-duty off-road sector offers significant fuel-saving potential, as its focus has traditionally been on reliability and performance rather than fuel efficiency. This dissertation examines fuel and CO2e savings opportunities on a heavy-duty off-road material handler, the Pettibone Cary-Lift 204i, from stock configuration to simple modifications to a complete teardown and reconfiguration of the machine with a plug-in series hybrid architecture using electrified hydraulics. The study begins by modeling the baseline machine’s fuel and energy consumption, calibrating with experimental data from custom operating cycles. An energy analysis identifies key areas for fuel savings. Two simple powertrain modifications result in a combined 16.2% fuel savings. Next, a Pugh-style analysis narrows a list of electrified architectures, leading to high-fidelity models that evaluate total lifetime CO2e and costs. Higher electrification levels reduce CO2e emissions but increase costs, and electricity grid emissions significantly impact CO2e for plug-in architectures. A plug-in series hybrid is chosen for the project. In its base control form, 49% fuel and 29% CO2e savings are expected from the plug-in series hybrid compared to the baseline machine. Further savings are pursued through regenerative braking (6.3%) and load-following hydraulic control (17.8%), totaling 24.1% fuel savings, and leading to a total of 61% fuel and 41% CO2e savings compared to the baseline. Battery chemistries and charging strategies are also analyzed for cost and CO2e impacts, finding LFP batteries as superior due to longevity, and overnight level 2 charging usually at a lower cost but resulting in higher emissions than opportunity DC fast-charging (DCFC). DCFC emissions are highly dependent on grid emissions, and DCFC cost is highly dependent on grid demand charges. Finally, artificial intelligence is applied to operating cycle recognition. Neural network accuracy ranges from 81% to 99%, with applications to worksite efficiency and safety improvements.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Ultra-Fast Resonant DC Breaker

This project’s focus was to create an ultra-fast resonant hybrid dc circuit breaker for medium voltage electric systems. Medium voltage DC systems offer higher efficiency, additional resiliency, more controllability, and greater flexibility over comparable AC systems. Although technically, medium voltage DC systems are more attractive than their AC counterparts, no solution exists for the protection of medium voltage DC systems, and thus one cannot build a reliable MVDC system. This research will fill the technology gap, providing a MVDC protection solution, allowing mass adoption and proliferation of MVDC systems. MVDC systems will allow greater integration of renewable energy sources, higher efficiency of transmission and distribution, reduced losses in transmission lines, reduce carbon emissions, and higher electric power reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Life Cycle Assessment for Closed-Loop Pumped Hydropower Energy Storage in the United States

The federal government has initiated an aggressive set of policies to achieve a net-zero carbon emission goal for the electricity sector by 2050. As a result, rapid growth in deployment of renewable energy technologies is expected. Most commercially mature technologies are temporally variable and do not provide grid inertia, while renewable technologies with high projected deployment have intermittent generation methods. Energy storage technologies are needed to both dispatch power on-demand and help provide the needed grid inertia. Pumped storage hydro (PSH) is a well-established technology that has gained renewed interest in recent years offering energy-balancing, grid stability, control of electrical network frequency, and large-scale storage capacity. For widespread adoption of PSH, more information is needed regarding its current life cycle environmental impacts. The objective of this study is to perform a full life cycle assessment (LCA) of new closed-loop PSH in the U.S. The functional unit for this study is 1 kWh of electrical power delivered to the grid and the base case project lifetime is 80 years. The life cycle inventory for this project accounts for all material and energy flows associated with the green-field construction, operation, maintenance, and decommissioning of a closed-loop PSH plant in the U.S. Collected data represents a range of potential PSH specifications and geographic locations coming from all prospective closed-loop PSH installations in the U.S. with data available. In addition, existing PSH installations are used to provide assumptions for inventory inputs. Results presented will include the global warming potential (GWP IPCC 100a) and Energy Return on Investment (EROI) from our base case (average PSH installation) as well as from scenario analyses and model sensitivity. These results will be compared to the impacts from existing PSH sites and alternate storage technologies. Methods align with the assumptions and guidelines put in place by previous PSH LCAs to ensure an accurate comparison with the results from this report.

ENERGY PLANNING, POLICY, AND ECONOMY,HYDRO ENERGY↗

Overview of Quantum Sensing Materials and Techniques for Energy Sector Applications

The energy sector has become increasingly dependent upon highly sensitive sensing devices for a wide range of applications. Variables such as temperature, pH, electromagnetic fields, ions, and pressure must be measured with high precision, often in harsh conditions (e.g. highly corrosive environments due to high temperature, pressure and humidity). These sensors are deployed in infrastructure such as transformers, pipelines, mines, nuclear power plants, and other areas to ensure safe operating conditions and uninterrupted, optimized service. Moreover, new opportunities for sensors have emerged due to the expansion of smart grids/meters, driverless vehicles, and the discovery of new oil, gas, and critical mineral deposits. The continued maturation of quantum sensing technologies offers exciting opportunities for quantum-enhanced measurements within the energy sector that may provide significant improvements in sensitivity beyond the classical limit. Here, an overview of established and emerging quantum materials for sensing applications will be provided, from trapped ions to color centers in diamond and silicon carbide. Associated quantum sensing methods for these materials will be discussed, with an emphasis on platforms that are nearing commercial viability. Specific application opportunities within the energy sector for quantum sensors will then be analyzed, including oil/gas discovery, greenhouse gas emission monitoring, pH and ion sensing, current measurement in electric vehicle batteries, and quantum-enhanced spectroscopy. Remaining barriers, such as quantum sensor platform miniaturization and ruggedization, will also be analyzed. A specific project at the National Energy Technology Laboratory involving the functionalization of qubits using metal-organic frameworks for enhanced quantum sensing will also be highlighted. Here, nitrogen vacancy centers (NV) in nanodiamonds, a commercially available qubit with long coherence times and utilizable quantum properties at room temperature, are encapsulated in a controlled way using the metal-organic framework ZIF-8. The ZIF-8 provides a well-defined, porous scaffold that can be controlled to promote the selective uptake of specific target analytes, such as gas molecules or ions. The quantum sensing performance of this composite material is either preserved or enhanced following ZIF-8 encapsulation; the optically detected magnetic resonance response of the NV nanodiamonds with and without the ZIF-8 coating are identical, while the ZIF-8 coating increases the longitudinal spin relaxation lifetime (T1) of the NV centers, an important parameter for spin relaxometry-based quantum sensing experiments. Taken together, these results demonstrate the importance of qubit functionalization as a crucial step for rationally designing high performance quantum sensors.

Crawford, Scott↗

Control of Excitonic Energy Transfer in RGB Quantum Dot:Polymer Composites for Tunable White Emission

Tint-controlled white light is crucial for both illumination systems and display applications. Here, in this study, we demonstrate solution-processed quantum-dot light-emitting diodes (QD-LEDs) featuring a red–green–blue (RGB) QD–poly(methyl methacrylate) (PMMA) composite emissive layer (EML) for tunable white electroluminescence (EL). In this composite EML, PMMA functions as a dispersion matrix that modulates the interdot spacing (d), thereby controlling Förster resonance energy transfer (FRET) between QDs. By adjustment of the PMMA content, the balance of R, G, and B emissions is controlled, enabling systematic and continuous tuning of the EL color from greenish to reddish white at a fixed RGB ratio and constant driving bias. Time-resolved photoluminescence measurements confirm that the variation in the exciton lifetime with the PMMA fraction is the primary factor for tuning the EL color. Notably, nearly pure white EL with CIE coordinates close to (0.33, 0.33) is achieved using a diluted PMMA matrix without significant degradation of the electrical properties. Our results demonstrate d as an independent design parameter for decoupling color tuning from RGB composition and electrical operation, providing a versatile design framework for high-quality white- or tint-controlled QD-LEDs toward advanced solid-state lighting and display technologies.

36 MATERIALS SCIENCE↗

Surface-Enhanced Raman Detection of the CO 2 Moisture Swing

The development of scalable, energy-efficient carbon dioxide (CO 2 ) capture technologies is critical for achieving net-zero emissions. Moisture swing (MS) sorbents offer a promising alternative to traditional thermal regeneration methods by enabling reversible CO 2 binding through humidity-driven ion hydrolysis. In this study, we investigate the anion speciation dynamics in two classes of MS materials─an anion-exchange resin with a bicarbonate anion and activated carbon impregnated with potassium bicarbonate salt─using both sorption measurements and in situ surface-enhanced Raman spectroscopy (SERS). Ni-coated Ag nanowires were employed as SERS substrates to enhance signal intensity and enable the real-time detection of carbonate (CO 3 2– ), bicarbonate (HCO 3 – ), and hydroxide (OH – ) species under controlled humidity conditions in both air and nitrogen atmospheres. The results reveal humidity-dependent interconversion between anionic species with significant spectral shifts confirming the reversible hydrolysis reactions that drive the MS mechanism. Under humid conditions, we observed the depletion of bicarbonate signals and a concurrent increase in carbonate species, consistent with moisture-induced desorption of CO 2 . With the activated carbon samples, we further observed the formation of hydroxide. These findings not only validate the mechanistic models of humidity-driven anion exchange in MS sorbents but also demonstrate the practical potential of SERS as an operando diagnostic tool for monitoring CO 2 capture media. The ability to resolve and semiquantitatively evaluate the reversible transformation of carbonate, bicarbonate, and hydroxide ions under realistic environmental conditions provides valuable insight for the rational design, performance optimization, and quality control of next-generation sorbent materials for direct air capture applications.

CO2 capture↗

A Framework for Characterizing the Initial Thermal Conditions of Light-Duty Vehicles in Response to Representative Utilization Patterns, Ambient Conditions, and Vehicle Technologies

It is widely understood that the thermal state of a light-duty vehicle at the beginning of a trip influences the vehicle performance throughout the drive cycle. Cold starts, or initial states with component temperatures near ambient conditions, are strongly correlated with reduced vehicle performance and energy efficiency and with increased emissions. Despite this understanding, there is little literature available that characterizes initial thermal states beyond empirical studies and simplified analyses of dwell times. We introduce a framework that considers vehicle activity patterns, including the previous drive event, duration of the previous dwell event, and relevant ambient conditions occurring during these events. Moreover, the framework allows for technologies to influence the prominence of cold starts and warm starts. An example application of the methodology using a powertrain model approach revealed the significance of all constituent factors: controlling for ambient conditions, the shortest dwell lengths corresponded to an average initial oil temperature of 70°C versus 23°C for the long dwell length simulations, and aggressive conditioning cycles corresponded to an average initial oil temperature of 51°C versus only 35°C for a short conditioning cycle. The coldest ambient conditions evaluated (-30°C to -10°C) produced a weighted initial oil temperature of 19°C versus 57°C for the warmest ambient conditions evaluated (30°C to 50°C). Finally, we introduce weighting factors that account for the real-world frequency of conditioning cycle and dwell length combinations. The procedure outlined may be useful for discovering real-world performance improvements associated with vehicle technologies, a topic of interest to both vehicle manufacturers and regulators.

33 ADVANCED PROPULSION SYSTEMS↗

Crossing the Finish Line: Integration of Data-Driven Process Control for Maximization of Energy and Resource Efficiency in Advanced Water Resource Recovery Facilities

Improvements in process monitoring and control at water resource recovery facilities (WRRFs) could result in reductions in electricity consumption, chemical inputs, and greenhouse gas emissions, as well as improved energy recovery. Many current WRRF data collection, monitoring, and control approaches use 20th century process monitoring and control systems, which require large design safety factors to ensure reliability in the absence of more advanced, precise controls. Implementation of more modern data-driven control tools could lead to more efficient operations that provide intrinsic reliability with better overall process performance at full-scale. This project (1) developed and demonstrated data-driven process controls at full-scale facilities for five promising WRRF process technologies that provide whole-plant approaches and offer substantial energy and resource recovery benefits, and (2) created a Machine Learning (ML) Toolkit and an implementation guide of new process control approaches that walks users through each step of the ML workflow and illustrates the steps through case study examples.

54 ENVIRONMENTAL SCIENCES↗

Indefinite and bidirectional near-infrared nanocrystal photoswitching

Materials whose luminescence can be switched by optical stimulation drive technologies ranging from superresolution imaging, nanophotonics, and optical data storage, to targeted pharmacology, optogenetics, and chemical reactivity. Furthermore, these photoswitchable probes, including organic fluorophores and proteins, can be prone to photodegradation and often operate in the ultraviolet or visible spectral regions. Colloidal inorganic nanoparticles can offer improved stability, but the ability to switch emission bidirectionally, particularly with near-infrared (NIR) light, has not, to our knowledge, been reported in such systems. Here, we present two-way, NIR photoswitching of avalanching nanoparticles (ANPs), showing full optical control of upconverted emission using phototriggers in the NIR-I and NIR-II spectral regions useful for subsurface imaging. Employing single-step photodarkening and photobrightening, we demonstrate indefinite photoswitching of individual nanoparticles (more than 1,000 cycles over 7 h) in ambient or aqueous conditions without measurable photodegradation. Critical steps of the photoswitching mechanism are elucidated by modelling and by measuring the photon avalanche properties of single ANPs in both bright and dark states. Unlimited, reversible photoswitching of ANPs enables indefinitely rewritable two-dimensional and three-dimensional multilevel optical patterning of ANPs, as well as optical nanoscopy with sub-Å localization superresolution that allows us to distinguish individual ANPs within tightly packed clusters.

36 MATERIALS SCIENCE↗

Integration of renewable energy generation and storage systems for emissions reduction in an islanded campus microgrid

Microgrid connected building communities are projected to play an integral part in the clean energy transition. These types of systems, when integrated with distributed energy resources (DERs) such as combined heat and power (CHP), district heating and cooling, renewable generation, and energy storage, can provide clean, reliable power to critical facilities and vulnerable communities. The intermittent nature of renewable generation is a challenge when integrating renewables into any grid system, but particularly in islanded microgrids. The University of Texas at Austin (UT) operates an islanded microgrid powered by a CHP plant, while also utilizing district heating and cooling systems and thermal energy storage (TES). High fidelity operating data was used to develop a validated reduced order model of UT’s integrated campus energy systems to serve as a testbed for use in a case study. Hypothetical renewable energy installations on land owned by UT in west Texas were modeled and integrated into the validated campus models along with battery energy storage (BES). Simulations showed that a combination of renewable energy from wind, and optimally controlled 24-hour thermal and battery storage systems could reduce carbon dioxide emissions on campus by 45.4%. The additional retrofit of burner systems to utilize hydrogen natural gas blends resulted in an overall annual emissions reduction of 54.7%. Carbon capture and storage eliminated the majority of the remaining emissions with increased plant energy expenditure. The presented simulations display the practical limitations of a CHP system complemented by renewable generation and short-term storage in eliminating emissions. Furthermore, results highlight the need for further research and development in long duration storage technologies and hydrogen fueled turbines to increase penetration of renewable energy and reduce emissions.

CHP↗

Remote Radiation Sensing Using Aerial and Ground Platforms

Remote sensing of ionizing radiation has a significant role in waste management, nuclear material management and nonproliferation, and radiation safety. Robotic platforms can surpass the number of tasks that are achieved by humans. With this technique, the operator's radiation exposure can be decreased. Remote sensing allows for the evaluation and monitoring of radiological contamination. Gamma-ray and neutron sensors were integrated onto the robotic platforms. This approach allows for the radiation sensor data to be dynamically tracked and mapped thus enabling further analysis of the radiation flux in temporal and spatial domains. The goal is to complete scheduled tasks while the robot is being irradiated. To achieve this, electronic components must be shielded and radiation hardened. CZT Detector: Cadmium Zinc Telluride (CZT) detector technology has been a promising solution for gamma-ray and x-ray measurements. Detector data is transferred to the Odroid minicomputer that controls and powers the module via the USB. Robot Operating System (ROS) was utilized for data acquisition and data fusion. The Mariscotti method was employed for the spectrum analysis. A function was programmed in ROS for the automatic identification of photopeaks. CLYC Detector: A Cs{sub 2}LiYCl{sub 6}:Ce{sup 3+} (CLYC) detector was used for simultaneous medium-resolution gamma-ray measurements and neutron counting. A 2.54 cm diameter photomultiplier tube (PMT) was equipped with a high voltage supply and a miniature digitizer. Gamma-ray excitation: fast core-to-valence luminescence (CVL) with 1 ns decay constant, and prompt Ce{sup 3+} emission with 50 ns decay constant. Neutron excitation: slow cerium self-trapped excitation (Ce{sup 3+} STE), 1000 ns decay constant. Radiation Source Localization: Maximum Likelihood Estimation (MLE) and gradient-based methods were used to locate the position of a radiation source based on measured radiation intensities. Multi-Particle Transport Code FLUKA: Estimation of radiation damage of the electronic components is important in order to optimize the robot's operational time while it is irradiated. Displacement per atom (DPA) represents the radiation damage in materials exposed to the ionizing radiation. Various shielding layers of different thickness t were analyzed (< 5% statistical error). The model of the controller of the UAS was designed in FLUKA. Conclusion: CZT and CLYC detectors were integrated onto the robotic platforms. Radiation source localization and contour mapping using robotic platforms were studied. Functions for data analysis and fusion were developed in ROS. FLUKA code was utilized to analyze DPA values. Layers of low-density and high-density materials were used to shield the UAS electronics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Savings in Action: Lessons from Observed and Modeled Residential Solar Plus Storage Systems

The electric grid is rapidly evolving as small-scale, demand-side resources play increasingly important roles in grid operations and decarbonization. Maximizing the potential of demand-side resources involves incentivizing electricity customers to use those resources in ways that benefit the broader electrical grid. These incentives depend largely on the electricity cost savings that customers can realize from demand-side resource adoption. Determining these potential cost savings is a complex task. Cost savings depend on numerous factors, including the characteristics of different technologies, the algorithms that control these devices, system performance, customer behavior, electricity rate structures, and climatic factors. Another challenge is that estimated cost savings are frequently based on modeled rather than observed system performance, particularly in the academic literature. In this study, we begin to fill the gap in empirical research of demand-side resources using data from a new construction residential community equipped with rooftop solar and storage (S+S) in Arizona. We use these data to analyze the factors that determine customer electricity cost savings and emissions impacts of S+S in the real world. We then compare these data to modeled system performance to understand how models deviate from real-world outcomes. Based on these findings, we explore ways to improve such models and, conversely, use modeled results to suggest improvements to actual S+S deployment. The results of these analyses can be summarized in four key findings: 1) rate structures play a central role in the grid and customer value of demand-side resources; 2) certain customers can benefit more from demand-side resource adoption than others; 3) modeled battery dispatch and sizing reveals opportunities for additional cost savings; and 4) optimal dispatches can reduce grid emissions while maximizing bill savings.

14 SOLAR ENERGY↗

Validation of a Co-Optimized, Smart Hybrid Heat Pump Control

This study examines a residential dual fuel (DF) heating system that integrates heat pump and gas furnace technology with a home’s forced-air distribution ducts. Specifically, it explores a retrofit where an “add-on” heat pump replaces the air conditioning (A/C) system and is combined with the home’s existing furnace and air handler. The research team developed and validated an innovative control scheme for this integrated DF system that selected the more economical heating source (furnace or heat pump) while maintaining comfort in the home. The project’s field study and subsequent modeling analysis show that this control scheme can decrease energy use, cost, and emissions compared to a furnace-only system. As homes in mixed and cold climates transition to more electric space heating, furnace-to-dual fuel system retrofits offer a solution that can alleviate the retrofit costs, energy cost concerns, and peak load impacts of full electrification.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Next-Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR) - Predictive Data-Driven Vehicle Dynamics and Powertrain Control: from ECU to the Cloud (Final Scientific/Technical Report)

This project developed and demonstrated a predictive, data-driven vehicle control system designed to improve energy efficiency and driving performance. The team created intelligent self-driving car technology that optimizes fuel and electricity use by proactively planning vehicle actions. By combining Level 4 autonomous driving capabilities with vehicle-to-everything (V2X) connectivity, the system enables vehicles to adjust speed and change lanes in response to traffic signals, surrounding vehicles, and road conditions, reducing unnecessary stops and delays. In testing, the system improved vehicle fuel economy by more than 30% and reduced travel time by approximately 10%, compared to a conventional adaptive cruise control baseline. These results demonstrate the technical effectiveness of using predictive, V2X-enabled strategies, such as traffic light timing and surrounding traffic awareness, to inform real-time vehicle powertrain control and driving behavior. Additionally, a supporting cloud platform was developed to provide dispatch and route recommendations as well as to log vehicle data, demonstrating the economic feasibility of this approach at the fleet level. By optimizing dispatching and routing operations, this technology enables electric fleet operators to use their vehicles more efficiently and reduce reliance on diesel backups, lowering both operating costs and energy consumption. Overall, this project’s technology advances the future of clean, energy-efficient transportation, enabling vehicles and fleets to reduce energy waste, cut costs, and lower emissions through intelligent automation and connectivity.

33 ADVANCED PROPULSION SYSTEMS↗

Tunable quantum emitters on large-scale foundry silicon photonics

Abstract Controlling large-scale many-body quantum systems at the level of single photons and single atomic systems is a central goal in quantum information science and technology. Intensive research and development has propelled foundry-based silicon-on-insulator photonic integrated circuits to a leading platform for large-scale optical control with individual mode programmability. However, integrating atomic quantum systems with single-emitter tunability remains an open challenge. Here, we overcome this barrier through the hybrid integration of multiple InAs/InP microchiplets containing high-brightness infrared semiconductor quantum dot single photon emitters into advanced silicon-on-insulator photonic integrated circuits fabricated in a 300 mm foundry process. With this platform, we achieve single-photon emission via resonance fluorescence and scalable emission wavelength tunability. The combined control of photonic and quantum systems opens the door to programmable quantum information processors manufactured in leading semiconductor foundries.

Larocque, Hugo (ORCID:000900095849780X)↗