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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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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Innovative control mechanism for research and test reactors using mandrel-shaped control rods

Research and test reactors have historically played a pivotal role in supporting the initial development of nuclear reactors. They continue to provide essential data for enhancing fuel designs and material knowledge. However, with many such reactors aging and the growing demand for data to bolster advanced reactor development, it is more necessary to research potential design attributes of the next generation of research and test reactors. For test reactors dedicated to fuel and material testing, the design of control mechanisms significantly influences the stabilization of neutron flux levels in irradiation positions while sustaining criticality. This study presents an innovative control mechanism for potential research and test reactor designs. It employs small absorber rods that move in opposite axial directions to maintain axial symmetry of power and neutron flux during burnup cycles. These rods maximize reactivity worth while also offering flexibility to flatten the radial power distribution. An axial translation of the control mechanisms’ absorbers, as compared to the rotational movement of absorbers in control cylinders, also provides a benefit to available excess reactivity and cycle length. Additionally, this work utilizes a simplified core model of the Advanced Test Reactor to assess the performance of this control mechanism. Compared to the current control system based on rotating control cylinders, the new control mechanism has the potential to enhance, or at least maintain, neutronic performance parameters in this reactor design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Efficient Computation of Doppler-Broadened Elastic Scattering Kernel Moments Using Ladder-Operator Formulation

Anefficient routine for computing Legendre moments of the Doppler-broadened elastic scattering kernel, including resonance scattering effects, has been implemented in the ISOXML module of Griffin. Isotropic scattering in the center-of-mass system and the ideal gas model for target motion are assumed. A ladder-operator formulation is introduced to compute all Legendre moments from order 0 to N simultaneously, enabling near-linear scaling of computational cost with respect to the maximum Legendre order. A physics-based strategy for constructing outgoing energy grids has also been developed, in which a tailored base grid is combined with adaptive refinement to maintain accuracy while limiting the number of outgoing energy points. For energies between resonances, a constant cross-section model is employed to further reduce computational cost. In addition, a quantitative criterion is derived to determine isotope-wise cut-off incident energies based on a prescribed up-scattering probability coverage. For 238U, up to incident energies of approximately 75, 230, and 661 eV at 294, 900, and 2500 K (corresponding to a 2% up-scattering probability threshold), computation of P0 kernels requires 1–8 s and computation of P0–P5 kernels requires 0.4–4 min using a single thread, while maintaining 1–3% relative error in up-scattering probability. These results demonstrate that the proposed formulation enables accurate and computationally practical Doppler-broadened kernel generation for online multigroup cross-section production in Griffin.

Doppler-broadening↗
DOE OSTI2025

Operator learning for energy-efficient building ventilation control with computational fluid dynamics simulation of a real-world classroom

Energy-efficient ventilation control plays an important role in reducing building energy consumption while ensuring occupant health and comfort. While Computational Fluid Dynamics (CFD) simulations provide detailed and physically accurate representations of indoor airflow, their high computational cost limits their use in real-time building control. In this work, we present a neural operator learning framework that combines the physical accuracy of CFD with the computational efficiency of machine learning to enable building ventilation control with the high-fidelity fluid dynamics models. Our method jointly optimizes the airflow supply rates and vent angles to reduce energy use and adhere to air quality constraints. We train an ensemble of neural operator transformer models to learn the mapping from building control actions to airflow fields using high-resolution CFD data. This learned neural operator is then embedded in an optimization-based control framework for building ventilation control. Experimental results show that our approach achieves significant energy savings compared to maximum airflow rate control, rule-based control, as well as data-driven control methods using spatially averaged CO 2 prediction and deep learning–based reduced-order models, while consistently maintaining safe indoor air quality. These results highlight the practicality and scalability of our method in maintaining energy efficiency and indoor air quality in real-world buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Designing reinforcement learning algorithms for building HVAC control: From experimental observation to simulation comparisons

Advanced supervisory-level control with reinforcement learning (RL) is regarded as a promising solution for HVAC systems to minimize energy consumption while maintaining thermal comfort and indoor air quality. However, most RL applications were conducted in the simulation environment rather than real-world HVAC systems. This paper developed a value-based RL controller termed Deep Q-Network (DQN) for a typical central HVAC system and evaluated its performance in a building test facility. By comparing DQN with a rule-based controller, the study not only demonstrated the cases where DQN could properly maintain indoor comfort but also discussed possible reasons why DQN failed in some other situations. Recognizing the limitations of value-based RL algorithms from the experimental tests, a simulation study was conducted to compare DQN with an alternative RL approach, an actor–critic algorithm termed Deep Deterministic Policy Gradient (DDPG). In scenarios with a relatively large action space, DDPG outperformed DQN by requiring fewer computational resources and achieving better thermal comfort, lower energy consumption, and more stable control actions. The findings suggest that the ability of DDPG to handle continuous control variables more effectively allows for faster convergence in training and more precise control in practice, which enhances the overall efficiency and reliability of the HVAC system.

Guo, Fangzhou↗
DOE OSTI2026

Localization and functional exploration of leiomodin-2’s C-terminal binding sites

Striated muscle contraction occurs through interactions between overlapping myosin-based thick and actin-based thin filaments within the sarcomere. For effective contraction to occur, the length of the thin filament must be maintained to allow for sufficient overlap with the thick filament. The proteins leiomodin and tropomodulin compete for binding at the pointed end of thin filaments to regulate their length, utilizing their homologous N-terminal actin and tropomyosin binding sites. Leiomodin also has a region called the C-terminal extension, absent in tropomodulin. In this region, the cardiac isoform (leiomodin-2) contains additional actin-binding sites that enable it to bind along the sides of thin filaments in a Ca2+-dependent manner. Here, using nuclear magnetic resonance spectroscopy, we localize the regions of the C-terminal extension that contain residues involved in thin filament side-binding. Using co-sedimentation assays, we reveal that these regions can independently bind thin filaments and discover that the poly-proline region plays a role as a linker, maintaining an adequate distance between two of the regions required for effective interaction to occur. In addition to its role in side-binding, we provide direct evidence that the poly-proline region interacts with profilin and propose a new mechanism by which leiomodin-2 may assist in the polymerization of profilin-bound actin at thin filament pointed ends.

ACTIN-BINDING PROTEINS↗
DOE OSTI2024

An experimental and chemical kinetic modeling study of 4-butoxyheptane combustion

Here, the combustion kinetics of a novel oxygenated bioblendstock for diesel, 4-butoxyheptane (4-BH), was investigated experimentally using a flow reactor and a heated, high-pressure shock tube. The flow reactor experiments employed oxygen as the oxidizer and helium as the diluent with oxidation conducted at atmospheric pressure and 10 bar for temperatures from 400 to 1000 K at 20-K intervals. The fuel, oxidizer, and diluent flow rates were varied at different temperatures to maintain a constant initial fuel mole fraction of 1000 ppm, with stoichiometric equivalence ratio, and a residence time of 2.0 s. The reacted gas was fed to two separate GC systems that could qualitatively and quantitatively detect product species. Additionally, real fuel-air ignition delay time (IDT) data were collected using a heated, high-pressure shock-tube facility. Fuel lean (φ = 0.5) and stoichiometric (φ = 1.0) mixtures were investigated at 10 atm as well as at 30 atm for the fuel lean case for temperatures between 847 and 1259 K. A detailed chemical kinetics mechanism was developed to model the product distribution from the flow reactor and IDTs from the shock tube. The proposed model was able to predict the double NTC behavior in flow reactor experiments reasonably well. Model predictions at low temperatures were observed to be highly sensitive to the rate constants of ketohydroperoxide (KHP) decomposition in the case of the OOH group in α position which were modeled based on existing literature studies on ethers. It was noted that in the absence of theoretical or experimental studies, the rate constants for KHP decomposition used in the literature were empirically set. Additional studies are required to address the gap in model prediction obtained in this study and to reduce the uncertainty in kinetics models for ether oxidation. Predicted product concentrations and IDTs showed some quantitative agreement with experimental data, but the overall reactivity of the IDTs is underpredicted. Additionally, significant deviation is observed for the IDT results at 10 atm for the stoichiometric case with minor deviations for the other cases. The reaction pathways to the missing products were then further analyzed theoretically through quantum-mechanical calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Enhancing the dark-state bistability and thermal stability of zinc dynamic windows with nitrile electrolytes

Reversible metal electrodeposition (RME) for dynamic windows is a promising alternative to traditional electrochromics. We explore the reasons behind the bistability of practical RME dynamic windows under a wide temperature range, i.e., how well they maintain their dark state without external power. While Zn dynamic windows with dimethyl sulfoxide electrolytes exhibit adequate bistability at room temperature, their performance degrades at elevated temperatures due to the presence of small amounts of water. Here, to overcome this problem, we developed a set of Zn nitrile electrolytes. The integrated devices can maintain dark-state bistability over at least 1 month at 85°C with 0.1% transmission using a propionitrile (PrCN) electrolyte. Additionally, the PrCN-based Zn dynamic windows possess high optical contrast, color-neutral switching, and promising cyclability, making Zn RME in nitrile electrolytes a promising solution for achieving robust dynamic windows.

RME↗
DOE OSTI2026

Development of physics-consistent conditional diffusion model to overcome data scarcity in critical heat flux

Deep generative modeling provides a powerful pathway to overcome data scarcity in energy-related applications where experimental data are often limited. By learning the underlying probability distribution of the training dataset, deep generative models, such as the diffusion model, can generate high-fidelity synthetic samples that statistically resemble the training data. Such synthetic data generation can significantly enrich the size and diversity of the available training data, and more importantly, improve the robustness of downstream machine learning models in predictive tasks. The objective of this paper is to investigate the effectiveness of diffusion models for overcoming data scarcity in nuclear energy applications. By leveraging a public dataset on critical heat flux which covers a wide range of commercial nuclear reactor operational conditions, we developed a diffusion model that can generate an arbitrary amount of synthetic samples. Since a vanilla diffusion model can only generate samples randomly, we also developed a conditional diffusion model capable of generating targeted critical heat flux data under user-specified thermal-hydraulic conditions. The performance of the diffusion model was evaluated based on its ability to capture empirical feature distributions and pair-wise correlations, as well as to maintain physical consistency. The results showed that both the diffusion model and conditional diffusion model can successfully generate realistic and physics-consistent critical heat flux data. Furthermore, uncertainty quantification results demonstrate that the conditional diffusion model is highly effective in augmenting critical heat flux data while maintaining acceptable levels of uncertainty.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Dual-season thermal energy storage-integrated heat pump system for load shifting: experiments, modeling and nationwide analysis

Here, this paper proposes and validates a dual-season thermal energy storage-integrated heat pump (TES-HP) system that shifts building electric load in both cooling and heating modes using a single phase-change TES. The design uses the TES as a heat sink for the condenser in summer and a heat source for the evaporator in winter, thereby reducing on-peak electric demand while ensuring compatible with existing air-distribution systems. A 14-kW TES-HP prototype with six operating modes and novel refrigerant charge management strategies was experimentally tested under varied conditions. Subsequently, data-driven polynomial performance curves were developed and validated against experiments, then coupled with a phase change material (PCM) model and a calibrated building model within a rule-based controller. Single-day case studies demonstrated effective on-peak demand reduction while maintaining thermal comfort. During cooling, hourly power was lowered by up to 1.5 kW; in heating, average hourly power decreased from over 3.5 kW to 1.8 kW, compared to an HP-only system, achieving 64.5 % load shifting, and the need for resistance heating was eliminated. Seasonal simulations showed typical on-peak electricity savings of 25–35 % in cooling and 40–65 % in heating, with the largest benefits on the hottest and coldest days. Extended response-surface analysis and nationwide mapping quantified load shifting as functions of ambient and TES temperatures, revealing a seasonal trade-off in TES phase-change temperature. These results demonstrate the TES-HP system as a practical and scalable solution for grid-interactive buildings that reduces on-peak demand and electricity use while maintaining thermal comfort and enhancing grid flexibility and reliability.

Grid-interactive buildings↗
DOE OSTI2024

Stabilizing a low temperature phase change material based on Glaubers salt

The aim of this research is to enhance the performance of Glauber's salt (sodium sulfate decahydrate, SSD) as a phase change material (PCM) for thermal energy storage applications, as well as for shipping of temperature-sensitive materials. The study investigates the effects of modifying SSD with potassium chloride (KCl) and ammonium chloride (NH 4 Cl) to achieve lower phase transition temperatures of between +6 °C and + 13 °C. Sodium polyacrylate (PAAS) is employed as a thickening agent to prevent phase separation, and borax is used as a nucleating agent to suppress supercooling. Various ratios of KCl:NH 4 Cl are tested, and the impact of PAAS concentration on phase segregation is explored. The results show that a 2 wt% concentration of PAAS effectively prevents phase separation. Samples with a KCl:NH 4 Cl ratio of 1:1.83 exhibit stable phase transition behavior and maintain latent heat values within the range of 130–140 J/g after 30 thermal cycles. Maintaining a total KCl and NH 4 Cl proportion of 10 wt% is crucial to achieve the desired lower melting temperature. As a result, the study highlights the significance of thermal cycling in improving the stability of the PCM. The optimized SSD-based eutectic PCM formulations hold promise for applications in the cold chain industry.

25 ENERGY STORAGE↗
DOE OSTI2025

Investigating the FLASH Effect in a Rat Brain Organotypic Model With a Novel High-Energy Electron Beam

Ultrahigh dose rate (FLASH) radiation therapy is reported to reduce normal tissue toxicity while maintaining tumor control; however, mechanism(s) remain obscure. To study FLASH mechanisms in brain tissue, we developed a novel experimental platform featuring a specialized high-energy electron linear accelerator, High Intensity Gamma Ray Source (HIGS), paired with an organotypic ex vivo brain metastasis model. We varied interpulse spacing to modulate the mean dose rate (MDR) of our unique 35 MeV electron beam, while maintaining extremely high instantaneous dose rate (IDR). We characterized dosimetry and targeting accuracy of the FLASH beam with film dosimetry. We combined this FLASH beam with an organotypic rat brain slice/breast carcinoma coculture model of brain metastasis to assess effects on normal and neoplastic tissues. Live-cell and bioluminescence imaging demonstrated cancer cell growth effects, whereas normal tissue responses and immune activation were assessed using live-cell imaging, cytokine profiles, and confocal microscopy. Here, we performed comparison experiments with 20 MeV electrons from a Varian clinical linear accelerator (VCLA) using conventional dose rates. The highest IDR of the FLASH beam to date was 20.7 ± 0.6 MGy/s, with maximum MDR of 20.7 MGy/s delivered in 1 pulse of 1 µs duration. Beam targeting was accurate to <1 mm and reproducible. HIGS-FLASH and VCLA dose rates equivalently decreased cancer cell growth. HIGS-FLASH irradiation significantly increased tumor necrosis factor α and fractalkine levels and confocal microscopy revealed distinct changes in microglial morphology slices suggesting microglia activation. Our novel experimental platform produces extremely high dose rates and rapid normal/neoplastic tissue readouts for mechanistic research into the effects of FLASH radiation in the brain. HIGS-FLASH irradiation induces comparable cancer cell growth inhibition but differential effects on cytokines and microglial morphology, suggesting that acute innate immune responses may be involved in FLASH normal tissue effects in the brain.

Kay, Tyler V. [Duke University, Durham, NC (United↗
DOE OSTI2025

Asynchronous aging and turnover of human circulating and tissue-resident memory T cells across sites

Memory T cells are maintained in tissues as circulating effector-memory (T EM ) and tissue-resident (T RM ) populations for protective immunity, though the role of site and subset in memory persistence remains undefined. Here, in this work, we investigated age-associated dynamics of human T cells in lymphoid organs, mucosal sites, and blood over 10 decades of life using retrospective radiocarbon ( 14 C) birth dating, along with cellular, transcriptome, and epigenetic profiling. Memory T cells across peripheral sites exhibited continuous turnover with mean lifespans of 1–2 years, while the spleen contained longer-lived T cells. Over age, T EM cells expressed senescent markers and a GZMK transcriptional signature, while T RM cells maintained site-specific resident phenotypes without exhibiting features of senescence. Both T EM and T RM cells showed age-associated DNA hypomethylation, though T RM cells exhibited more epigenetically regulated genes. Together, our findings reveal asynchronous aging of human memory T cells by subset and site, as well as persistence of T RM cells without immunosenescence.

T cells↗
DOE OSTI2024

A multiscale model to understand the interface chemistry, contacts, and dynamics during lithium stripping

A reversible Li-metal electrode, paired with a solid electrolyte, is critical for attaining higher energy density and safer batteries beyond the current lithium-ion cells. A stable stripping process may be even harder to attain as the stripping process will remove Li-atoms from the surface, and naturally reduce surface contact area, if not self-corrected by other mechanisms, such as diffusion and plastic deformation under an applied external stack pressure. Here, we capture these mechanisms occurring at multiple length- and time- scales, i.e., interface interactions, vacancy hopping, and plastic deformation, by integrating density functional theory (DFT) simulations, kinetic Monte Carlo (KMC), and continuum finite element method (FEM). By assuming the self-affine nature of multiscale contacts, we predict the steady-state contact area as a function of stripping current density, interface wettability, and stack pressure. We further estimate the exponential increase of overpotential due to contact area loss to maintain the same stripping current density. We demonstrate that a lithiophilic interface requires less stack pressure to reach the same steady-state contact area fraction than a lithiophobic interface. A “tolerable steady-state” contact area loss for maintaining stable stripping is estimated at 20 %, corresponding to a 10 % increase in overpotential. To constrain contact loss within the tolerance, the required stack pressure is 0.1, 0.5, and 2 times the yield strength of lithium metal for three distinct interfaces, lithiophilic Li/lithium oxide(Li2O), Li/lithium lanthanum zirconium oxide(LLZO), and lithiophoblic Li/lithium fluoride(LiF), respectively. The modeling results agree with experiments on the impact of the stack pressure quantitatively, while the discrepancy in stripping rate sensitivity is attributed to the simplifying interface interaction in our simulations. Overall, this multiscale simulation framework demonstrates the importance of electrochemical-mechanical coupling in understanding the dynamics of the Li/SE interface during stripping.

Feng, Min↗
DOE OSTI2026

Trace levels of PtRu on NiMo foam electrodes towards hydrogen evolution reaction

Electrochemical water splitting plays a critical role in high purity hydrogen production. To lower capital cost and energy consumption, efficient catalysts are required to boost the hydrogen evolution reaction (HER), especially in alkaline media. Although PtRu alloy materials are still considered the state-of-the-art catalyst for the HER under alkaline media, large-scale application is hindered by its scarcity and high cost. NiMo alloy catalysts can be potential Pt-free alternatives to drive the sluggish kinetics of the HER under alkaline media, but their HER activity is still not ideal due to the limitation of Volmer step. Herein, we investigated the impact of trace levels of PtRu catalysts on NiMo electrodes towards the HER by incorporating advantages of both PtRu and NiMo catalysts to minimize cost and maintain a promising HER activity. Trace levels of PtRu catalysts from 0.0173 to 0.2648 mg cm −2 were loaded on commercial NiMo foam electrodes by a facile electrodeposition technique utilizing ppm concentration levels of PtRu in electrolyte. The results show that 0.0173 mg cm −2 PtRu loading on NiMo electrode can significantly enhance HER activity compared to the pristine NiMo foam electrode (Tafel slopes drop from ∼170 to ∼60 mV dec −1 ) due to the remarkable decline of energy barriers towards water dissociation and hydrogen adsorption. Meanwhile, the rate determining step (RDS) switches from the Volmer step to the Heyrovsky step when the PtRu loading increases to 0.0675 mg cm −2 . Promising catalytic stability is observed at 100 mA cm −2 over the course of 50 h with a PtRu loading of 0.1198 mg cm −2 . In conclusion, this work demonstrates a potential strategy to decrease the cost and simultaneously maintain superior HER performance by integrating trace levels of PtRu catalyst with NiMo foam electrodes.

Electrochemical water splitting↗
DOE OSTI2026

Evaluation of 3D pixel silicon sensors for the CMS Phase-2 Inner Tracker

The high-luminosity upgrade of the CERN LHC requires the replacement of the CMS tracking detector to cope with the increased radiation fluence while maintaining its excellent performance. An extensive R&D program, aiming at using 3D pixel silicon sensors in the innermost barrel layer of the detector, has been carried out by CMS in collaboration with the FBK (Trento, Italy) and CNM (Barcelona, Spain) foundries. The sensors will feature a pixel cell size of 25 × 100 µm 2 , with a centrally located electrode connected to the readout chip. The sensors are read out by the RD53A and CROCv1 chips, developed in 65 nm CMOS technology by the RD53 Collaboration, a joint effort between the ATLAS and CMS groups. This paper reports the results achieved in beam test experiments before and after irradiation, up to a fluence of approximately 2 . 6 × 1 0 16 n eq /cm 2 . Measurements of assemblies irradiated to a fluence of 1 × 10 16 n˙eq/cm 2 show a hit detection efficiency higher than 96% at normal incidence, with fewer than 2% of channels masked, across a bias voltage range greater than 50 V . Even after irradiation to a higher fluence of 1.6 × 10 16 n˙eq/cm 2 , similar performance is maintained over a bias voltage range of 30 V , remaining well within CMS requirements.

3D pixel↗
DOE OSTI2025

Root cause analysis of a molten salt pump in FLUSTFA

The primary salt pump installed in the high-temperature FLUoride Salt Test Facility (FLUSTFA) was successfully operated for some time, but later ceased operation. To understand what occurred, a Root Cause Analysis (RCA) was performed. Steps taken to try to get the pump operational include adjusting the shaft position, increasing the heating power of the tape heaters on the pump volute, and manually rotating the pump shaft. While removing the insulation, corrosion was noted on the outside of the pump volute, and decolorization of the insulation and tape heaters was observed. Significant corrosion products were also observed in the pump itself and the piping connected to the pump. The nitrogen cover gas was maintained from before salt was introduced into the loop until the pump was dismounted and continues to be maintained even after the pump was removed. After considering probable scenarios, causes were assigned and corrective actions were developed to prevent those causes. Then, the RCA was presented to an advisory committee for review, the “Review Committee,” consisting of experts in large molten salt systems: Brandon Haugh, David Holcomb, Kevin Robb, and Vicente Rojas. As a result, the advisory committee provided comprehensive feedback, which have been incorporated into a revised RCA. Findings have then been summarized and reported in this publication.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Understanding the ignition process and flame structure of conventional and oxygenated fuels under engine relevant conditions – An optical study

Renewably generated synthetic fuels such as poly-oxymethylene ethers (OME) have a significant potential to effectively break the soot-NOX trade-off in compression ignition engines by using exhaust gas recirculation (EGR) to maintain low nitrogen oxide (NOX) emissions while maintaining good efficiency and simultaneously contributing to circular carbon economy. However, owing to the fundamental differences in properties of OME when compared to fossil-based diesel fuels, it is critical to fully understand its ignition and combustion phenomenology to take advantage of this fuel to its utmost potential. In this context, this work outlines the results of a systematic experimental study performed in a heavy-duty, single-cylinder, optical engine probing the spatial and temporal progression of fuel decomposition and ignition behavior of OME when compared to n-dodecane, a diesel-fuel surrogate. Thermodynamic analysis and optical diagnostics techniques including simultaneous HCHO-PLIF and OH-PLIF complemented by high-speed OH* chemiluminescence were employed along with parametric sweeps of intake temperature and EGR dilution rates. OME does not exhibit any observable low temperature heat release irrespective of the ambient oxygen concentration. Differences in the observed diffusive flame structure such as longer flame lift-off length, less pronounced combustion recession, faster premixed burn at ignition (“volumetric” ignition), non-sooting behavior suggest that the inherent presence of fuel-bound oxygen in OME can skew the air-fuel ratio (AFR) distribution within the jet thereby reducing the reliance of combustion on mixing and air entrainment. This leads to rapid late-cycle oxidation leading to shorter combustion duration and favorable combustion phasing. Results also suggest that OME exhibits relatively weak negative temperature coefficient (NTC) behavior, however, the OME fuel-decomposition kinetic-pathways produce significant concentration of HCHO, which might be erroneously interpreted as a product of cool-flames.

Air-fuel ratio↗
DOE OSTI2024

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

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

Oke, Doris↗