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At least 145 records · Page 8

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DOE OSTI2025

FLEX-FUEL MIXING CONTROLLED COMBUSTION ENABLED BY PRECHAMBER IGNITION

There is an imminent need to displace fossil diesel fuel with cleaner burning, domestically produced, renewable fuels for use in heavy-duty engines. Bioethanol is a prime candidate as it widely adopted in the U.S. as a gasoline additive ranging in volume percentage from 10% (E10) up to 85% (E85). Direct substitution of market available ethanol-gasoline blends for diesel fuel is not plausible as the stark reactivity differences would not constitute the same ignition quality nor achieve auto-ignition at all. This work focuses on the development of prechamber enabled mixing-controlled combustion (PC-MCC) as an advanced combustion strategy to facilitate reliable ignition and diffusion style combustion ethanol-gasoline fuel blends. PC-MCC involves integration of an actively fueled prechamber (PC) into a conventional compression ignition combustion system. When ignited, the PC ejects hot turbulent jets into the main combustion chamber that then interact with the direct injected fuel, prompting immediate ignition. The PC jet flames provide a robust thermal ignition source that allows the engine to operate agnostic of fuel composition, or flex-fuel. Computational fluid dynamics (CFD) modeling was used to assess critical design features of the PC while garnering insights into the ignition strategies that facilitate robust performance. A key finding was the ignition performance benefits of fuel-rich PC operation which yield exothermic jets. Based on the numerical findings, a prototype igniter was tested experimentally on both single and multi-cylinder engine platforms at a variety of operating conditions. The experimental results indicate flex-fuel PC-MCC is well capable of diesel-like combustion processes by demonstrating matched or improved gross thermal efficiencies and load variability within 2%. Fuel grade ethanol (E98) exhibited consistently lower NOx and immeasurable soot across the load space. E98 also demonstrated a significant improvement in thermal efficiency at light loads.

Zeman, Jared↗

DOE OSTI2026

Machine learning for slow-extraction uniformity at the Fermilab Delivery Ring

The Muon-to-Electron Conversion Experiment (Mu2e) requires uniform slow extraction from the Fermilab Delivery Ring during each 43 ms spill. This project analyzed 13,737 spills from seven parquet files collected during March and June 2026 commissioning. Each spill contained 430 samples at 0.1 ms resolution and was summarized by the Spill Duty Factor. Null Action and active proportional-integral-derivative conditions established operational baselines. Fixed-ramp sessions were segmented to evaluate reproducibility, drift, and spill-to-spill spread, while a deliberate quadrupole-ramp step identified the beam-response peak and trough. Median profiles were reproducible within fixed conditions but drifted over multi-hour periods. The resulting baselines and response features support future physics-based and machine-learning approaches to real-time spill regulation.

Prescott, Matthew J. [Purdue U., West Lafayette; F↗

DOE OSTI2023

Integration of seismic-pressure-petrophysics inversion of continuous active-seismic monitoring data for monitoring and quantifying CO 2 plume (Final Report)

The overall objective of this project is to develop and validate an integrated package of joint seismic-pressure-petrophysics inversion (jSPPI) of continuous active-source seismic monitoring dataset capable of providing real-time monitoring of CO 2 plume during geologic carbon sequestration (GCS). The three specific developments include: (a) the methodologies for fast seismic full waveform inversion of continuous active source seismic monitoring, (CASSM) datasets for simultaneously estimating velocity and attenuation, and with data assimilation; (b) joint Bayesian petrophysical inversion of seismic models and pressure data for providing and updating CO 2 saturation models; (c) the methods using multiple datasets including (Crainfield and Frio-II borehole) synthetic, laboratory, and field CASSM datasets. The outcomes of jSPPI include (a) a workflow for processing CASSM data, (b) Bayesian inversion algorithms using CASSM data and pressure response data, and (c) integration with data assimilation algorithms for continuously updating site-specific models used for prediction and reservoir management. The validation of joint FWI will be conducted using synthetic models based on the Cranfield and Frio experiments as well as field CASSM datasets collected as part of the Frio-II pilot injection. To quantify and map the mass and distribution of CO 2 (saturation), we will jointly invert velocity and attenuation measurements from the FWI with a Bayesian approach using a rock physics model for attenuation (e.g., White’s attenuation model with two selected patch sizes (White, 1976; Dutta and Seriff, 1979)). The Bayesian inversion will be applied to each time step in the CASSM survey in an updating scheme, which integrates with an ensemble of reservoir simulations at each step. A more complete experimental validation dataset will be collected as part of a mesoscale (2-3 m) gas-CO 2 injection experiment utilizing a higher frequency version of the CASSM system developed for laboratory studies; the integrated inversion will be demonstrated using this dataset which will provide both a dense geometry as well as more precise secondary confirmation measurements (e.g. saturation) typically not available in the field. The resulting real-time map of CO 2 saturation is able to provide a deeper scientific understanding of the complex, time-varying dynamics of subsurface fluid flow migration path as well as the rapid detection of CO 2 leakage hazards.

25 ENERGY STORAGE↗

DOE OSTI2023

Clean Cities: A Model of Collaborative Technology Innovation Built Over 30 Years

The Clean Cities Coalition Network is an example of successful government-sponsored efforts to reduce petroleum use and facilitate collaborative governance across sectors and levels of government within the transportation sector. In 1993, under what is now the Vehicle Technologies Office (VTO), the U.S. Department of Energy (DOE) established Clean Cities in response to a requirement in the Energy Policy Act (EPAct) of 1992 to implement voluntary alternative fuel deployment activities. VTO's Technology Integration Program is responsible for the Clean Cities Coalition Network and many other activities. DOE created a collaborative governance effort that has translated higher-level policy goals into multiple local collaborative practices for more than 30 years.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Modeling the Strategic Behavior of an Active Distribution Network in the ISO Markets

With increasing integration of distributed energy resources (DERs), active distribution networks (ADNs) can actively participate in the electricity markets by dispatching their DERs, which can change the existing electricity market paradigm. It is essential to investigate the strategic behaviors of ADNs and their DER dispatch when they participate in the wholesale market as price-makers. This paper proposes a bi-level optimization model to study the strategic behavior of an ADN in both energy and reserve markets. The optimal scheduling of DERs in the ADN is modeled as the upper level problem and the joint energy and reserve market-clearing of the ISO is modeled as the lower-level problem. The two-level optimization models exchange bidding information and energy/reserve prices with each other. The proposed bi-Ievel optimization problem is converted to a mathematical programming with equilibrium constraints (MPEC) by using Karush-Kuhn Tucker (KKT) conditions and strong duality theory. Further, the MPEC problem is reformulated as a computationally-solvable mixed integer second order cone programming (MISOCP) model. The simulation results on an illustrative case demonstrate the impact of the strategic bidding of the ADN on the day-ahead energy and reserve market prices.

active distribution network↗

DOE OSTI2021

Modeling the Strategic Behavior of an Active Distribution Network in the ISO Markets

Xue, Yaosuo↗

DOE OSTI2021

Increasing Integration of Data-driven Analyses in Operational Activities through Knowledge Management.

Abstract not provided.

Gunda, Thushara↗

DOE OSTI2025

ACES-GNN: can graph neural network learn to explain activity cliffs?

Graph Neural Networks (GNNs) have revolutionized molecular property prediction by leveraging graph-based representations, yet their opaque decision-making processes hinder broader adoption in drug discovery. This study introduces the Activity-Cliff-Explanation-Supervised GNN (ACES-GNN) framework, designed to simultaneously improve predictive accuracy and interpretability by integrating explanation supervision for activity cliffs (ACs) into GNN training. ACs, defined by structurally similar molecules with significant potency differences, pose challenges for traditional models due to their reliance on shared structural features. By aligning model attributions with chemist-friendly interpretations, the ACES-GNN framework bridges the gap between prediction and explanation. Validated across 30 pharmacological targets, ACES-GNN consistently enhances both predictive accuracy and attribution quality for ACs compared to unsupervised GNNs. Our results demonstrate a positive correlation between improved predictions and accurate explanations, offering a robust and adaptable framework to better understand and interpret ACs. This work underscores the potential of explanation-guided learning to advance interpretable artificial intelligence in molecular modeling and drug discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Energy-efficient Mott activation neuron for full-hardware implementation of neural networks

To circumvent the von Neumann bottleneck, substantial progress has been made towards in-memory computing with synaptic devices. However, compact nanodevices implementing non-linear activation functions are required for efficient full-hardware implementation of deep neural networks. Here, in this work, we present an energy-efficient and compact Mott activation neuron based on vanadium dioxide and its successful integration with a conductive bridge random access memory (CBRAM) crossbar array in hardware. The Mott activation neuron implements the rectified linear unit function in the analogue domain. The neuron devices consume substantially less energy and occupy two orders of magnitude smaller area than those of analogue complementary metal–oxide semiconductor implementations. The LeNet-5 network with Mott activation neurons achieves 98.38% accuracy on the MNIST dataset, close to the ideal software accuracy. We perform large-scale image edge detection using the Mott activation neurons integrated with a CBRAM crossbar array. Our findings provide a solution towards large-scale, highly parallel and energy-efficient in-memory computing systems for neural networks.

electrical and electronic engineering↗

DOE OSTI2024

Enabling Fairness in Distributed PV Curtailment for Voltage Regulation: A Comparative Analysis

The growing adoption of photovoltaic systems in power distribution networks has yielded numerous advantages, but it has also introduced challenges, particularly in managing overvoltage issues. Uncoordinated photovoltaic integration can lead to voltage rise beyond acceptable levels. Curtailing active power is an effective method for addressing overvoltage issues in power distribution systems. Nevertheless, it is essential to distribute the curtailment fairly among the resources to maintain fairness and achieve a well-balanced utilization of renewable energy. This paper presents a comparative study of different fairness schemes for active power curtailment in photovoltaic integration systems. Three different curtailment methods are selected for demonstration: i) proportional, ii) egalitarian, and iii) financial. The study involves evaluating the curtailment schemes based on their ability to distribute the curtailed power among the photovoltaic systems in a justifiable manner, focusing on their formulation and distributed solution. A detailed performance comparison is carried out to highlight the cost of catering for fairness schemes in photovoltaic curtailment using relevant metrics, where simulations are carried out using a modified IEEE 123-bus test case.

Mukherjee, Monish↗

DOE OSTI2023

Beneficial Integration of Energy Storage and Load Management with Photovoltaic (PV)

In recent years, a number of industry activities have aimed at addressing the integration challenges posed by the variability and uncertainty of higher penetration of renewable generation sources, like solar photovoltaic (PV) – one of the key objectives of the Sustainable and Holistic Integration of Energy Storage and Solar PV (SHINES) program launched by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). This EPRI led Beneficial Integration of Energy Storge, and Load Management with PV project aimed to design, develop, and demonstrate end-to-end distributed energy resource (DER) integration solution to build on these activities. EPRI led project team designed and implemented a local controller that uses model predictive control (MPC) algorithm to optimally manage DERs on site by planning for a receding horizon while executing the control settings for the first step of its plan. The team has also developed a system controller to interface with the local controller to demonstrate the hierarchical control and how it can leverage DER capabilities to address challenges like over voltage and thermal limit violations which typically limits the DER hosting capacity of distribution feeders. Team has demonstrated how the local controller with optimization algorithm can effectively manage controllable loads like HVAC, water heater, and pool pumps to allow for greater integration of PV with relatively smaller energy storage system requirements. Optimal utilization of the load control can also reduce the depth of discharge of batteries to meet grid export/import limit from behind-the-meter (BTM) DERs. Proper utilization of DER capabilities via local control intelligence, like the one developed and demonstrated in this project can help the industry to address integration challenges of higher penetration of solar PV in economically efficient manner. This can help to accelerate deployment of clean renewable energy systems at lower societal cost.

14 SOLAR ENERGY↗

DOE OSTI2020

The integral spliceosomal component CWC15 is required for development in Arabidopsis

Efficient mRNA splicing is a prerequisite for protein biosynthesis and the eukaryotic splicing machinery is evolutionarily conserved among species of various phyla. At its catalytic core resides the activated splicing complex Bact consisting of the three small nuclear ribonucleoprotein complexes (snRNPs) U2, U5 and U6 and the so-called NineTeen complex (NTC) which is important for spliceosomal activation. CWC15 is an integral part of the NTC in humans and it is associated with the NTC in other species. Here we show the ubiquitous expression and developmental importance of the Arabidopsis ortholog of yeast CWC15. CWC15 associates with core components of the Arabidopsis NTC and its loss leads to inefficient splicing. Consistent with the central role of CWC15 in RNA splicing, cwc15 mutants are embryo lethal and additionally display strong defects in the female haploid phase. Interestingly, the haploid male gametophyte or pollen in Arabidopsis, on the other hand, can cope without functional CWC15, suggesting that developing pollen might be more tolerant to CWC15-mediated defects in splicing than either embryo or female gametophyte.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

The 5 Cs of Agrivoltaic Success Factors in the United States: Lessons from the InSPIRE Research Study

The concept of agrivoltaics (combining agriculture and solar photovoltaics technologies on the same land in novel configurations) has emerged as an approach to mitigate conflicts between solar and agricultural activities by providing mutual benefits and added values to each sector. The U.S. Department of Energy has supported agrivoltaics research since 2015 through its Innovative Solar Practices Integrated with Rural Economies and Ecosystems (InSPIRE) research project (National Renewable Energy Laboratory 2022). The InSPIRE project is the most comprehensive coordinated research effort on agrivoltaics in the United States and has examined opportunities and tradeoffs at over 25 sites across the country that span crop production, pollinator habitat, ecosystem services, animal husbandry, and d. Integrating research sites with active commercial agricultural operations can introduce unique challenges for conducting research. This synthesis aims to highlight the technical and non-technical insights from InSPIRE agrivoltaic field research sites from 2015-2021 to support i) appropriate deployment of agrivoltaic projects; ii) more successful research on agrivoltaics; and iii) more effective partnerships on agrivoltaic projects. The synthesized lessons discussed here are focused less on specific case study outcomes (i.e., the percent change in crop yield in an agrivoltaics configuration), and instead more on the elements that enable and facilitate agrivoltaics projects to be installed and operated along with research to be conducted at those sites. We find that there are some insights that are applicable across all types of agrivoltaic projects, while ecosystem service projects and crop production agrivoltaic projects can often have other unique considerations.

14 SOLAR ENERGY↗

DOE OSTI2023

Impacts of water scarcity on agricultural production and electricity generation in the Middle East and North Africa

Incorporating the interdependencies between water, energy and food (WEF) within an integrated approach of planning and management could help nations worldwide to address sustainability concerns. This is a topic of great importance for the Middle East and North Africa (MENA) region, where water is a very limited resource. In this study, we develop an analytical framework to analyze the water-energy-food nexus in the MENA region to inform the formulation of integrated strategies for water, energy and food activities. Our approach is based on an integrated assessment model for the MENA region, which explicitly represents WEF sectors within an economic framework, in tandem with a set of relevant scenarios addressing three key dimensions (socioeconomics, climate and water-management). Using this framework, our study analyzes the current and projected status of water resources in the region, and the potential implications for the agriculture and electricity sectors. Our scenarios demonstrate that water scarcity worsens by the end of the 21st century in most MENA countries, mostly due to growing demands. The impacts of growing scarcity on agriculture are significant, with production projected to drop by 60 percent by 2050 in some countries. On the other hand, and to a lesser extent, water-saving technologies and fuel-switching in the power sector play a key role in mitigating the effects of water scarcity on electricity generation in some parts of the MENA region. Our analysis then underscores the need to reduce the dependence of MENA’s agricultural and energy sectors on water, and transition to renewable energies to reduce water scarcity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Chlorophyllase from Arabidopsis thaliana Reveals an Emerging Model for Controlling Chlorophyll Hydrolysis

Chlorophyll (Chl) is one of Nature’s most complex pigments to biosynthesize and derivatize. This pigment is vital for survival and also paradoxically toxic if overproduced or released from a protective protein scaffold. Therefore, along with the mass production of Chl, organisms also invest in mechanisms to control its degradation and recycling. One important enzyme that is involved in these latter processes is chlorophyllase. This enzyme is employed by numerous photosynthetic organisms to hydrolyze the phytol tail of Chl. Although traditionally thought to catalyze the first step of Chl degradation, recent work suggests that chlorophyllase is instead employed during times of abiotic stress or conditions that produce reactive oxygen species. However, the molecular details regarding how chlorophyllases are regulated to function under such conditions remain enigmatic. Here, we investigate the Arabidopsis thaliana chlorophyllase isoform AtCLH2 using site-directed mutagenesis, mass spectrometry, dynamic light scattering, size-exclusion multiangle light scattering, and both steady-state enzyme kinetic and thermal stability measurements. Through these experiments, we show that AtCLH2 exists as a monomer in solution and contains two disulfide bonds. One disulfide bond putatively maps to the active site, whereas the other links two N-terminal Cys residues together. These disulfide bonds are cleaved by chemical or chemical and protein-based reductants, respectively, and are integral to maintaining the activity, stability, and substrate scope of the enzyme. This work suggests that Cys residue oxidation in chlorophyllases is an emerging regulatory strategy for controlling the hydrolysis of Chl pigments.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Achievements of actively controlled divertor detachment compatible with sustained high confinement core in DIII-D and EAST

The compatibility of efficient divertor detachment with high-performance core plasma is vital to the development of magnetically controlled fusion energy. The joint research on the EAST and DIII-D tokamaks demonstrates successful integration of divertor detachment with excellent core plasma confinement quality, a milestone towards solving the critical plasma–wall-interaction (PWI) issue and core-edge integration for ITER and future reactors. In EAST, actively controlled partial detachment with T et,div ~ 5 eV around the strike point and H 98 > 1 in different H-mode scenarios including the high β P H-mode scenario have been achieved with ITER-like tungsten divertor, by optimizing the detachment access condition and performing detailed experiments for core-edge integration. For active long-pulse detachment feedback control, a 30 s H-mode operation with detachment-control duration being 25 s has been successfully achieved in EAST. DIII-D has achieved actively controlled fully detached divertor with low plasma electron temperature (T et,div ≤ 5 eV across the entire divertor target) and low particle flux (degree of detachment, DoD > 3), simultaneously with very high core performance (β N ~3, β P > 2 and H 98 ~ 1.5) in the high βP scenario being developed for ITER and future reactors. The high-β P high confinement scenario is characterized by an internal transport barrier (ITB) at large radius and a weak edge transport barrier (ETB, or pedestal), which are synergistically self-organized. Both the high-β P scenario and impurity seeding facilitate divertor detachment. The detachment access leads to the reduction of ETB, which facilitates the development of an even stronger ITB at large radius in the high β P scenario. Thus, this strong large radius ITB enables the core confinement improvement during detachment. In conclusion, these significant joint DIII-D and EAST advances on the compatibility of high confinement core and detached divertor show a great potential for achieving a high-performance core plasma suitable for long-pulse operation of fusion reactors with controllable steady-state PWIs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

CsO x Nanostructures on Au(111): Morphology- and Size-dependent Activity for the Water–Gas Shift Reaction

Alkali oxides are typically used as promoters of heterogeneous catalysts for the water–gas shift (WGS; H 2 O + CO → H 2 + CO 2 ) reaction. On Au(111), CsO x exhibits diverse nanostructures at varying coverages, as revealed by scanning tunneling microscopy. Clusters of cesium oxide (Cs 2 O 2 ) nucleate at elbow sites of the Au(111) herringbone when θ Cs is less than 0.1 ML. Subsequently, these clusters transform into two-dimensional (2D) islands (Cs 2 O, Cs 2 O 2 , CsO 2 ) as the cesium coverage increases (θ Cs > 0.1 ML). Both types of CsO x nanostructures enable the WGS process on Au(111). The highest activity was seen for the cesium oxide clusters which facilitated the partial dissociation of water and binding of CO. The CO ads and OH ads groups were not strongly bound and probably reacted to yield a short-lived HOCO intermediate that led to gaseous H 2 and CO 2 . The 2D islands of CsO x also enabled the WGS but their efficiency was reduced due to the formation of cesium hydroxide compounds (limiting mobility of OH groups) and the generation of CO 3 and C species (blocking of active centers). The fact that the performance of the CsO x /Au(111) catalysts changed dramatically with variations in the chemical properties of the CsO x nanostructures indicates that the alkali oxide was an integral part of the active phase, playing a central role in the activation and conversion of the reactants. To attach the label of “promoter” to CsO x is a simplification that does not help in the design and optimization of catalysts for C1 chemistry. In conclusion, to achieve a rational design, one must consider the structural and chemical properties of the alkali oxide.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Integrated structural dynamics uncover new modes of B12 photoreceptor activation

**SACLA** A crystallographic pump-power titration was first carried-out with pump laser fluences of 12, 30, 60 and 120 uJ.cm-2 and a time delay of 3 us. Then, a time-series was performed with a pump-laser fluence of 30 uJ.cm-2 (~2.4 absorbed photon per chromophore) and time-delays of 10 ns, 300 ns, 3 µs, 100 us and 3 ms. Finally, two time-delays (10 ns and 3 us) were collected with a pump laser fluence of 12 uJ.cm-2. Raw images, crystFEL streams and merged mtzs are available for all collected dat **SwissFEL** A time series with a pump laser fluence of 30 mJ.cm-2 was performed at time delys of 3 µs and 10 ms. Raw images, crystFEL streams and merged mtzs are available for all collected datasets. Refined detector geometry for each experimental campaign is also provided (crystFEL format)

RIOS-SANTACRUZ, Ronald↗