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State and Alternative Fuel Provider Fleet Program, Model Year 2023 Annual Report

The Energy Policy Act of 1992 (EPAct) was enacted in part to reduce the nation's dependence on imported petroleum. Provisions of EPAct require certain fleets to acquire alternative fuel vehicles (AFVs). The U.S. Department of Energy administers these requirements through its State and Alternative Fuel Provider Fleet Program, Federal Fleet Requirements, and Alternative Fuel Designation Authority. This report summarizes activities under the program during model year 2023.

33 ADVANCED PROPULSION SYSTEMS

Reversible Nanocomposite by Programming Amorphous Polymer Conformation Under Nanoconfinement

Nanoconfinements are utilized to program how polymers entangle and disentangle as chain clusters to engineer pseudo bonds with tunable strength, multivalency, and directionality. When amorphous polymers are grafted to nanoparticles that are one magnitude larger in size than individual polymers, programming grafted chain conformations can "synthesize" high-performance nanocomposites with moduli of ≈25GPa and a circular lifecycle without forming and/or breaking chemical bonds. These nanocomposites dissipate external stresses by disentangling and stretching grafted polymers up to ≈98% of their contour length, analogous to that of folded proteins; use both polymers and nanoparticles for load bearing; and exhibit a non-linear dependence on composition throughout the microscopic, nanoscopic, and single-particle levels.

Chen, Tiffany

Microbial spies and bloggers: programming cells to convert environmental information into discernible signals

Microbes regulate their dynamic behaviors using the chemical and physical characteristics of their environment. The ability of microbes to continuously convert this physicochemical information into biochemical information and to use organic matter in the environment as a power source makes these organisms attractive as chassis for building sensors. However, most biosensors have severe limitations when considering applications in hard-to-image settings like soils, sediments, and wastewater. Emerging technologies at the interface of biomolecular design, microbiome engineering, and synthetic biology offer new tools to program cells and communities as biosensors for these settings. Here, in this review, we describe innovations in biosensor outputs that are enabling new applications in complex environments, including reporters that are read out using electrochemical, gas chromatography, hyperspectral imaging, and next-generation sequencing methods. We also discuss computational advances that are accelerating the diversification of sensing components by mining metagenomics data for new transcriptional regulators and by designing allosteric protein switches that directly regulate reporter outputs using analytes. We highlight emerging opportunities for programming undomesticated microbes in communities to function as distributed sensors in the environment. Finally, we discuss the need for responsible biosensor development and to modernize regulatory frameworks to support evidence-based assessment of environmental biosensors.

analyte

Multi-parametric analysis for mixed integer linear programming: An application to transmission upgrade and congestion management

Upgrading the capacity of existing transmission lines is essential for meeting the growing energy demands, facilitating the integration of renewable energy, and ensuring the security of the transmission system. This study focuses on the selection of lines whose capacities and by how much should be expanded from the perspective of the Independent System Operators (ISOs) to minimize the total system cost. We employ advanced multi-parametric programming and an enhanced branch-and-bound algorithm to address complex mixed-integer linear programming (MILP) problems, considering multi-period time constraints and physical limitations of generators and transmission lines. To characterize the various decisions in transmission expansion, we model the increased capacity of existing lines as parameters within a specified range. This study first relaxes the binary variables to continuous variables and applies the Lagrange method and Karush-Kuhn-Tucker (KKT) conditions to obtain optimal solutions and identify critical regions associated with active and inactive constraints. Moreover, we extend the traditional branch-and-bound (B&B) method by determining the problem’s upper and lower bounds at each node of the B&B decision tree, helping to manage computational challenges in large-scale MILP problems. Here, we compare the difference between the upper and lower bounds to obtain an approximate optimal solution within the decision-makers’ tolerable error range. In addition, the first derivative of the objective function on the parameters of each line is used to inform the selection of lines for easing congestion and maximizing social welfare. Finally, the capacity upgrades are selected by weighing the reductions in system costs against the expense of upgrading line capacities. The findings are supported by numerical simulations and provide transmission-line planners with decision-making guidance.

24 POWER TRANSMISSION AND DISTRIBUTION

Benders Decomposition Using Graph Modeling and Multi-Parametric Programming

Benders decomposition is a widely used method for solving large and structured optimization problems, but its performance is affected by the repeated solution of subproblems. We propose a flexible and modular algorithmic framework for accelerating Benders decomposition. Specifically, we express the problem structure by using a graph-theoretic modeling abstraction in which nodes represent optimization subproblems and edges represent connectivity between subproblems. A key innovation of our approach is that we embed multiparametric programming (mp) surrogates for node subproblems, which maps the exact analytical map of the subproblem solution space. The use of mp surrogates allows us to replace subproblem solves with fast look-ups and function evaluations for primal and dual variables during the iterative Benders process. We formally show the equivalence between classical Benders cuts and those derived from the mp solution. We implement our framework in the open-source PlasmoBenders.jl software package. To demonstrate the capabilities of the proposed framework, we apply it to a two-stage stochastic programming problem, which aims to make optimal capacity expansion decisions under market uncertainty. We evaluate both single-cut and multicut variants of Benders decomposition and show that the use of mp surrogates achieves substantial speedups in subproblem solve time, while preserving the convergence guarantees of Benders decomposition. We highlight advantages in solution analysis and interpretability that is enabled by mp critical region tracking; specifically, we show that these reveal how decisions evolve geometrically across the Benders search. Our results aim to demonstrate that combining surrogate modeling with graph modeling offers a promising and extensible foundation for structure-exploiting decomposition. In addition, by decomposing the problem into more tractable subproblems, the proposed approach also aims to overcome scalability issues of mp. Finally, the use of mp surrogates provides a unifying and modular optimization framework that enables the representation of heterogeneous node subproblems as modeling objects with a homogeneous structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Navigating Large Chemical Spaces Using Graph Theory and Integer Programming

Navigating and analyzing large chemical spaces are necessary to accelerate the design and discovery of new molecules and chemical processes. In this work, we introduce a computational framework that integrates graph theory and integer programming to enable the efficient navigation of large chemical spaces. Our framework represents the chemical space as a graph, wherein nodes represent molecules and edges represent the degree of similarity or connectivity based on domain-specific information. Using the graph representation, we identify representative molecules by computing the so-called minimum dominating set (MDS), which in our context is the minimum set of molecules that is connected to all other molecules. We present a suite of solution strategies for the MDS problem including heuristic and rigorous integer programming (IP) approaches. We show that these approaches allow us to capture physicochemical properties and domain-specific logic and constraints, facilitating the identification of molecules with the target properties. We demonstrate the effectiveness of the proposed approach by navigating the chemical space of per- and polyfluoroalkyl substances (PFAS); this comprises approximately 15,000 molecular structures. We compare our framework against traditional dimensionality reduction and clustering methods such as t-SNE and K-means clustering.

Chemical structure

Nanoscale Ferroelectric Programming of van der Waals Heterostructures

We demonstrate an approach to creating nanoscale potentials in van der Waals layers integrated with a buried programmable ferroelectric layer. Using ultra-low-voltage electron beam lithography (ULV-EBL), we can program the ferroelectric polarization in Al 1–x B x N (AlBN) thin films, generating structures with sizes as small as 35 nm. We demonstrate the ferroelectric field effect with a graphene/vdW stack on AlBN by creating a p–n junction. This resist-free, high-resolution, contactless patterning method offers a new pathway to integrate ferroelectric films with a wide range of two-dimensional layers including transition-metal dichalcogenides (TMD), enabling arbitrary programming and top-down creation of multifunctional devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Rooftop solar and energy storage programs can remediate energy-limiting behaviors of energy insecure households in the United States

Energy insecurity, or the inability to afford energy needs, affects most low-income households in the United States and leads to risky choices and additional insecurities including food and health. Although there are government programs designed to provide relief from energy insecurity, eligibility is usually determined by household income, and those with incomes close to the threshold face uncertainty or may be left out. In many cases, these households turn to energy-limiting behaviors as a strategy to lower their electric utility bills. Here we explore the relationship between energy insecurity and energy-limiting behaviors and investigate alternative solutions such as energy storage and rooftop solar. This analysis demonstrates that solar and energy storage can offset two-thirds of the bill savings that households could attain through severe energy-limiting behavior. These systems could complement existing energy assistance programs to provide long-term bill relief, enabling occupants to live in their homes with comfort and dignity.

Kerby, Jessica R. [Pacific Northwest National Labo

Programming entropy production hotspots via interaction patterning

Dissipation in soft matter and living systems is highly heterogeneous, giving rise to complex local entropy production patterns. Recent work has identified the connection between local entropy production and locally extractable amount of work. This suggests that locally produced entropy can be recovered to power nanorobots and biological machines, prompting the need for efficient strategies to modulate and fine-tune local entropy production. In this work, we propose to program entropy production hotspots by leveraging local interaction patterns and test this approach in simulations of a fluid driven through a nanopore or past an obstacle. Here, the results show that patterning the surface of the pore with a repulsive patch gives rise to an entropy production hotspot around the patch, while an attractive patch leads to an entropy production cold spot. Varying the strength of the interaction and width of the patch enables modulating the hotness and extent of the hot spot. In flows past interaction patterned-obstacles, we show that the combined effects of steric hindrance and attraction allows to program a specific entropy production map, thereby opening the door to the precise powering of nanomachines.

Desgranges, Caroline [University of Massachusetts,

Structural switching dynamically controls the doubly pseudoknotted Rous sarcoma virus–programmed ribosomal frameshifting element

A hallmark of retrovirus replication is the translation of two different polyproteins from one RNA through programmed –1 frameshifting. This is a mechanism in which the actively translating ribosome is induced to slip in the 5′ direction at a defined codon and then continues translating in the new reading frame. Programmed frameshifting controls the stoichiometry of viral proteins and is therefore under stringent evolutionary selection. Forty years ago, the first frameshifting stimulatory element was discovered in the Rous sarcoma virus. The ~120 nt RNA segment was predicted to contain a pseudoknot, but its 3D structure has remained elusive. Now, we have determined cryoEM and X-ray crystallographic structures of this classic retroviral element, finding that it adopts a butterfly-like double-pseudoknot fold. One “wing” contains a dynamic pyrimidine-rich helix, observed crystallographically in two conformations and in a third conformation via cryoEM. The other wing encompasses the predicted pseudoknot, which interacts with a second unexpected pseudoknot through a toggle residue, A2546. This key purine switches conformations between structural states and tunes the stability of interacting residues in the two wings. We find that its mutation can modulate frameshifting by as much as 50-fold, likely by altering the relative abundance of different structural states in the conformational ensemble of the RNA. Taken together, our structure–function analyses reveal how a dynamic double pseudoknot junction stimulates frameshifting by taking advantage of conformational heterogeneity, supporting a multistate model in which high Shannon entropy enhances frameshifting efficiency.

Science & Technology - Other Topics

Advancing Fusion Research and Development at TAE Technologies Through INFUSE Program

The U.S. Department of Energy’s Innovation Network for Fusion Energy (INFUSE) program serves as a crucial catalyst by fostering public-private partnership that accelerates technological innovation for fusion energy research and development (R&D) in the private sector. Further, this article provides a comprehensive overview of the technical goals and accomplishments of projects awarded to TAE Technologies through the INFUSE program since 2019. We offer high-level perspectives on how these projects have contributed to fusion energy R&D, and we address key challenges encountered during these collaborations.

field-reversed configuration

Too dim, too bright, and just right: Systems analysis of the Chlamydomonas diurnal program under limiting and excess light

Photosynthetic organisms coordinate their metabolism and growth with diurnal light, which can range in intensity from limiting to excessive. Little is known about how light intensity impacts the diurnal program in Chlamydomonas reinhardtii, or how diurnal rhythms in gene expression and metabolism shape photoprotective responses at different times of day. To address these questions, we performed a systems analysis of synchronized Chlamydomonas populations acclimated to low, moderate, and high diurnal light. Transcriptomic and proteomic data revealed that the Chlamydomonas rhythmic gene expression program is resilient to limiting and excess light: genome-wide, waves of transcripts, and proteins peak at the same times in populations acclimated to stressful light intensities as in populations acclimated to moderate light. Yet, diurnal photoacclimation gives rise to hundreds of gene expression changes, even at night. Time course measurements of photosynthetic efficiency and pigments responsive to excess light showed that high light-acclimated cells partially overcome photodamage in the latter half of the day prior to cell division. Although gene expression and photodamage are dynamic over the diurnal cycle, Chlamydomonas populations acclimated to low and high diurnal light maintain altered photosystem abundance, thylakoid architecture, and non-photochemical quenching capacity through the night phase. This suggests that cells remember or anticipate the light intensities that they have typically encountered during the day. The integrated data constitute an excellent resource for understanding photoacclimation in eukaryotes under environmentally relevant conditions.

Dupuis, Sunnyjoy

Investigating Resilience of Loops in HPC Programs: A Semantic Approach with LLMs

Soft errors have become one of the major concerns for the error resilience of the HPC applications as those errors may cause HPC applications to generate serious outcomes such as silent data corruptions (SDCs). Protecting the applications from soft errors is an essential while challenging task. Among different approaches, obtaining a profound understanding of the resilience proneness of an application is very important to devise efficient error detection and recovery strategies. Given the scale of the HPC applications both in the code size and execution time, there are often cases that the error propagation analysis on such applications would produce a massive volume of unstructured data, which requires a significant amount of efforts, to process and to obtain indicating actions towards error protection. In this paper, we present a control-flow based visual analysis framework to help the users conduct error propagation analysis and identify the critical sections of a program that may have a higher likelihood of leading to erroneous outcomes when affected by the control flow related errors. We also design and implement the scalable visualization framework - ResilienceVis that efficiently and effectively visualizes the affected program states under errors and the propagation traces for an application in a user-friendly manner, and eventually, we combine the analysis and visualization to exhibit the error-proneness of the different sections of applications.

Jiang, Hailong

Open-source simulation program for extreme ultraviolet and soft x-ray sources based on high-harmonic generation

Light sources based on high-harmonic generation (HHG) underpin ultrafast spectroscopy experiments across a large range of photon energies, spanning from the extreme ultraviolet to the soft x-ray. To this day, their design, implementation, and improvement presens unique challenges, but can be aided by numerical tools. Here we present a new simulation program designed for this purpose, which takes both macroscopic and microscopic aspects of high-harmonic generation into account and is therefore applicable across the broad range of parameters which HHG based light sources are today utilized. The program is validated by comparison with published experimental results and by calculating harmonic emission in four common experimental configurations.

Femtosecond lasers

2022 Bull E-Bike Pilot Program Study

In 2022, the City of Durham conducted an e-bike pilot program study to learn more about how electric bikes (e-bikes) could improve the transportation experience in the "Bull City" (a.k.a., Durham, North Carolina). The study used pedal-assist e-bikes, which feature an electric motor and battery to help power the bike. The motor amplifies the power behind each pedal stroke, augmenting the energy you put into the bike. #### Data Collection Agency The City of Durham's Transportation Department conducted the study. #### Survey Methodology Program participants used electric-assist e-bikes for at least 4 weeks between August and November 2022 in exchange for sharing information about their experiences, including tracking their travel via a smartphone app. In addition to the e-bike, participants received maintenance support along with a helmet, bike lock, and other accessories. Data collection was enabled by the [NLR OpenPATH platform](https://www.nlr.gov/transportation/openpath.html). #### Survey Records and Data Survey records include a total of 76 participants. The dataset contains 3 months of partially automated travel diaries, combining sensed and surveyed travel behavior data—patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from participants. The number of total trips was 6,488, the number of e-bike trips was 2,183, and the number of e-bike miles traveled was 5,450.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Analysis of Tank 38H (HTF-38-24-53, -56) and Tank 43H (HTF-43-24-54, -55) Samples for Support of the Enrichment Control and Corrosion Control Programs

Savannah River National Laboratory analyzed samples from Tank 38H and Tank 43H to support the Enrichment Control Program (ECP) and Corrosion Control Program (CCP). The results indicate the concentrations of most soluble species in the Tank 38H surface sample increased from the previous Tank 38H surface sample. The current Tank 38H subsurface sample shows similar Na, free hydroxide, and anions in comparison to the previous subsurface sample. However, the 38H subsurface sample shows lower concentrations of Al, Ca, Fe, Mn, and Si in comparison to the previous Tank 38H subsurface sample. Measurement of the wt.% insoluble solids in the Tank 38H subsurface sample and associated uncertainty analysis indicates that the calculated average wt.% insoluble solids is 0.45 ± 0.75 wt.%. Significant differences in the concentrations of major components between the Tank 38H surface and subsurface samples indicate significant stratification of solution species between these two locations within Tank 38H.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W

LANL Meteorology Program Self-Assesment 2024 Update

The DOE Meteorological Coordinating Council (DMCC) conducted an initial LANL Meteorological (Met) Program Assist Visit in August 2006 (DMCC 2006). A follow-up assist visit in August 2015 assessed progress (DMCC 2015), and in June 2023, the DOE Meteorological Subcommittee (DMSC), successor to the DMCC, conducted a second follow-up assist visit (DMSC 2023), in which the Met Program was evaluated relative to the following 8 high-level questions.

54 ENVIRONMENTAL SCIENCES