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At least 343 records · Page 19

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DOE OSTI2020

Carbon isotope evidence for the substrates and mechanisms of prebiotic synthesis in the early solar system

Meteorites contain prebiotic, bio-relevant organic compounds including amino acids. Their syntheses could result from diverse sources and mechanisms and provide a window on the conditions and materials present in the early solar system. Here we constrain alanine’s synthetic history in the Murchison meteorite using site-specific 13 C/ 12 C measurements, reported relative to the VPDB standard. The δ 13 C VPDB values of -29 ± 10‰, 142 ± 20‰, and -36 ± 20‰ for the carboxyl, amine-bound, and methyl carbons, respectively, are consistent with Strecker synthesis of interstellar-medium-derived aldehydes, ammonia, and low-δ 13 C nebular or interstellar-medium-derived CN. We report experimentally measured isotope effects associated with Strecker synthesis, and use them to constrain the δ 13 C values of the alanine precursors, which we then use to construct a model that predicts the molecular-average δ 13 C values of 19 other organic compounds of prebiotic significance found in Murchison if they were made by our proposed synthetic network. Finally, most of these predictions agree with previous measurements, suggesting that interstellar-medium-derived aldehydes and nebular and/or pre-solar CN could have served as substrates for synthesis of a wide range of prebiotic compounds in the early solar system.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Evaluations of Connectors, Inlets, and Adapters on Side-Load and Withstand Force

This report examines the mechanical forces that direct current fast charging (DCFC) electric vehicle supply equipment (EVSE) connectors and electric vehicle (EV) inlet ports experience during normal usage. As we witness the fast and growing variety of EVs, charge port locations, and bigger and more powerful EVSE configurations including the SAE J3400 North American Charging Standard (NACS), which has increased the use of adapters with J3400 and J1772 compatibility. These new conditions contribute to increased mechanical forces due to their size, weight and lever arm effect, which creates the need to study and compare these forces to the limits on UL2251 and IEC 62196-1 standards. This report focuses solely on high power DC charging EVSE connectors, EV inlets and adapters for the specific compatibility cases on J3400 with J1772. We first describe the details of the 100N and the 750N side-load evaluations as described in the standards, then present the data obtained by replicating these tests to finally go into more detail on the findings and our recommendations.

100N↗

DOE OSTI2021

Toward a Generalizable Framework of Disturbance Ecology Through Crowdsourced Science

Disturbances fundamentally alter ecosystem functions, yet predicting their impacts remains a key scientific challenge. While the study of disturbances is ubiquitous across many ecological disciplines, there is no agreed-upon, cross-disciplinary foundation for discussing or quantifying the complexity of disturbances, and no consistent terminology or methodologies exist. This inconsistency presents an increasingly urgent challenge due to accelerating global change and the threat of interacting disturbances that can destabilize ecosystem responses. By harvesting the expertise of an interdisciplinary cohort of contributors spanning 42 institutions across 15 countries, we identified an essential limitation in disturbance ecology: the word ‘disturbance’ is used interchangeably to refer to both the events that cause, and the consequences of, ecological change, despite fundamental distinctions between the two meanings. In response, we developed a generalizable framework of ecosystem disturbances, providing a well-defined lexicon for understanding disturbances across perspectives and scales. The framework results from ideas that resonate across multiple scientific disciplines and provides a baseline standard to compare disturbances across fields. This framework can be supplemented by discipline-specific variables to provide maximum benefit to both inter- and intra-disciplinary research. To support future syntheses and meta-analyses of disturbance research, we also encourage researchers to be explicit in how they define disturbance drivers and impacts, and we recommend minimum reporting standards that are applicable regardless of scale. Finally, we discuss the primary factors we considered when developing a baseline framework and propose four future directions to advance our interdisciplinary understanding of disturbances and their social-ecological impacts: integrating across ecological scales, understanding disturbance interactions, establishing baselines and trajectories, and developing process-based models and ecological forecasting initiatives. Our experience through this process motivates us to encourage the wider scientific community to continue to explore new approaches for leveraging Open Science principles in generating creative and multidisciplinary ideas.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Engineering modular enzyme assembly: synthetic interface strategies for natural products biosynthesis applications

Covering: 2020 to 2025Natural products remain indispensable sources of therapeutic and bioactive compounds, yet traditional discovery strategies are constrained by compound rediscovery. Modular biosynthetic enzymes, such as type I polyketide synthases (PKSs) and type A non-ribosomal peptide synthetases (NRPSs), offer promising platforms for combinatorial biosynthesis owing to their programmable architectures. However, practical implementation is frequently limited by inter-modular incompatibility and domain-specific interactions. This review highlights recent advances in modular enzyme assembly enabled by synthetic interfaces-including cognate docking domains, synthetic coiled-coils, SpyTag/SpyCatcher, and split inteins-which function as orthogonal, standardized connectors to facilitate post-translational complex formation. These interfaces support rational investigations into substrate specificity, module compatibility, and pathway derivatization as well as general enzyme clustering applications beyond PKS and NRPS systems. Synthetic interfaces can be integrated with computational tools to support a more systematic and scalable framework for modular enzyme engineering by providing predictive insights into domain compatibility and interface design. These approaches within iterative design-build-test-learn workflows can accelerate the programmable assembly of biosynthetic systems and expand the accessible chemical space for natural products.

Kim, Gahyeon↗

DOE OSTI2026

Generalizable Web User Interface for Scalable and Streamlined Deployment of Building Energy Management Systems in Small and Medium-Sized Commercial Buildings

Small and medium-sized commercial buildings (SMCBs) comprise 94% of US commercial buildings yet face significant barriers to implementing building energy management systems despite advances in smart device technology. Existing solutions present critical limitations: cloud-based API solutions simplify deployment but create vendor lock-in constraints; commercial integrated software solutions ensure compatibility via standardized protocols but require substantial cost and technical expertise; open-source IoT platforms offer cost-effective vendor independence but provide insufficient standardized protocol support for commercial building automation. This research presents a generalizable web user interface framework that bridges the gap between evolving smart device capabilities and lagging software infrastructure for SMCBs. The proposed system integrates VOLTTRON open-source middleware with an automated configuration converter that transforms unified specifications written in YAML, a human-readable data-serialization format, into system-specific files, streamlining manual setup processes. The vendor-agnostic architecture supports industry-standard protocols (BACnet and Modbus) and semantic building models while providing adaptive web interfaces that dynamically adjust to various building configurations. Demonstrations through simulation-based testing and a field deployment show automatic interface adaptation across heterogeneous HVAC systems and multizone monitoring. The automated configuration converter also substantially reduces labor-intensive setup.

Chung, Jihoon [ORNL] (ORCID:0000000184880815)↗

DOE OSTI2026

Cybersecurity Standards, Certification, and Best Practices for DERs

Distributed energy resources (DERs) are becoming increasingly important to the electric grid, including solar energy systems. However, DERs also introduce new cybersecurity risks, including those posed by cloud computing. Standards harmonization is essential for ensuring that DERs are secure and can be safely integrated into the grid. This panel will discuss cyber standards harmonization for solar security. The panel will feature experts from the S2G Program, National Labs and Industry who will discuss the following topics: the cybersecurity risks and future benefits posed by ubiquitous solar energy systems, the development and implementation of cloud-based security solutions for DERs, including solar energy systems, the challenges and opportunities for harmonizing DER cybersecurity standards, and Cyber Informed Engineering and the solar security implementations The panel will also discuss the following specific initiatives: the S2G Program's DER Cybersecurity Framework, UL's DER Cybersecurity Certification Program, and IEEE 1547 Updates. The panel will conclude with a discussion of the future of standards harmonization for DER cybersecurity.

14 SOLAR ENERGY↗

DOE OSTI2026

Do Flashing and Sealant Materials Need to be Exposed to Extreme Cycling?

In the U.S., over 50% of homes were built before 1980, when minimal building codes existed. The aging of building envelopes can significantly contribute to the air leakage, moisture intrusion, and durability of buildings leading to higher energy demands. Although the durability of building materials and envelope systems has been studied extensively, the durability of specific components like window-wall flashing and sealants remains underexplored. Current standards such as ASTM, NIST, and AAMA primarily focus on durability testing considering the high temperatures only and require sealant testing on anodized aluminum panels, leaving questions about performance in cold or fluctuating temperatures unanswered. Current ASTM and AAMA standards provide guidelines for durability testing but predominantly focus on exposure to higher temperature conditions. It remains unclear how exposure to cold temperatures, or cycles of both hot and cold conditions, affect the durability of these materials. Furthermore, AAMA standards mandate that flashing materials be tested on anodized aluminum panels, which may not reflect real-world applications. Therefore, this initial study aims to explore this concern through testing by constructing two window-wall interface prototypes and applying five different flashing and sealant materials to their joints. These samples were subjected to extreme temperatures, ranging from −34 ℃ (−30 °F) to 50 ℃ (122 °F), over a 28-day period (fourteen cycles of 24 hours), with daily visual inspections to document any signs of deterioration such as wrinkling, distortion, or warping. The study has two main objectives: (1) to determine whether flashing and sealant materials lose their durability and strength when exposed to varying climate conditions, specifically cold climates, and (2) to assess whether the interaction of these materials with different substrates (e.g., lumber, PVC, insulation) affects their durability and strength under varying climate conditions. The findings demonstrate how aging impacts the durability of window-wall systems interfaces, justifying future research that potentially could lead to the development of new testing protocols if significant defects are identified.

Palani, Hevar [ORNL] (ORCID:0000000220211994)↗

DOE OSTI2023

Improving materials property predictions for graph neural networks with minimal feature engineering *

Graph neural networks (GNNs) have been employed in materials research to predict physical and functional properties, and have achieved superior performance in several application domains over prior machine learning approaches. Recent studies incorporate features of increasing complexity such as Gaussian radial functions, plane wave functions, and angular terms to augment the neural network models, with the expectation that these features are critical for achieving a high performance. Here, we propose a GNN that adopts edge convolution where hidden edge features evolve during training and extensive attention mechanisms, and operates on simple graphs with atoms as nodes and distances between them as edges. As a result, the same model can be used for very different tasks as no other domain-specific features are used. With a model that uses no feature engineering, we achieve performance comparable with state-of-the-art models with elaborate features for formation energy and band gap prediction with standard benchmarks; we achieve even better performance when the dataset size increases. Although some domain-specific datasets still require hand-crafted features to achieve state-of-the-art results, our selected architecture choices greatly reduce the need for elaborate feature engineering and still maintain predictive power in comparison.

42 ENGINEERING↗

DOE OSTI2026

The need for standardization and improved open (meta)data practices in metaproteomics

Metaproteomics enables functional insight into microbial communities by identifying and quantifying proteins in complex samples. Yet, heterogeneous analytical workflows and the lack of standardization across experimental and bioinformatics stages hinder reproducibility and comparability, limiting integration with other omics data. We here present a community-developed reporting checklist tailored to the specific needs of metaproteomics. We also outline current efforts to enable structured and interoperable metadata capture, drawing on standards from proteomics and microbiome research wherever possible. By promoting transparent reporting and advancing metadata practices, our recommendations aim to align metaproteomics more closely with FAIR principles and support reproducible and interoperable research practices.

Armengaud, Jean [Universite Paris-Saclay, France]↗

DOE OSTI2024

Progress in development of characterization capabilities to evaluate candidate materials for direct air capture applications

As part of U.S. national efforts to combat the detrimental effect of global climate change, the National Institute of Standards and Technology (NIST) was recently tasked to support efforts in direct air capture (DAC) of carbon dioxide research and deployment. In order to develop test procedures, materials, and documentary standards, key characterization methods relevant to DAC materials have been investigated and used to identify desirable properties for a potential Standard Reference Material (SRM). Select amine-supported materials that previously showed potential for DAC applications have been characterized using commonly available laboratory methods. Further insights into the adsorption characteristics have been gained from developing and applying more specialized characterization tools ideal for probing low concentrations of carbon dioxide. A broad suite of capabilities that examine relevant properties under appropriate conditions gives the most profound insights into a material's specific performance. We advocate for even more specialized capabilities to be developed and standardized to quantitatively monitor the interactions of CO 2 with molecular species in complex and often disordered systems to advance DAC and support carbon dioxide reduction (CDR) in general.

carbon dioxide↗

DOE OSTI2021

Design Considerations for Fast Charging Lithium Ion Cells for NMC/MCMB Electrode Pairs

Lithium ion cells that can be quickly charged are of critical importance for the continued and accelerated penetration of electric vehicles (EV) into the consumer market. Considering this, the U.S. Department of Energy (DOE) has set a cell recharge time goal of 10–15 min. The following study provides an investigation into the effect of cell design, specifically negative to positive matching ratio (1.2:1 vs. 1.7:1) on fast charging performance. By using specific charging procedures based on negative electrode performance, as opposed to the industrial standard constant current constant voltage procedures, we show that the cells with a higher N:P ratio can be charged to ~16% higher capacity in the ten-minute time frame. Cells with a higher N:P ratio also show similar cycle life performance to those with a conventional N:P ratio, despite the fact that these cells experience a much higher irreversible capacity loss, leading to a lower reversible specific capacity.

25 ENERGY STORAGE↗

DOE OSTI2023

HT Model Dataset

This website contains the dataset that was used for writing the manuscript "HT Model: Using the Molecular Transformer for predicting hydrotreating reactions" (PNNL-SA-186589) The dataset includes a collection of hydrotreating reactions compiled from 41 peer-reviewed literature sources. These sources contain experimental data related to hydrotreating reactions. These reactions involve the reaction of chemical compounds with hydrogen gas in the presence of a catalyst to remove heteroatoms or to convert specific functional groups. The dataset contains reactions both with and without reaction conditions. Reaction conditions refer to the specific parameters under which the reaction takes place, such as temperature and pressure. For each reaction, the dataset includes both SMILES and SELFIES representations. SMILES (Simplified Molecular Input Line Entry System) and SELFIES (SELF-referencIng Embedded Strings) are two popular notations used to represent chemical structures in a compact and standardized format. The dataset was created with the aim of training a predictive model, specifically using the Molecular Transformer architecture.

bioprocessing, hydrotreating, deep learning algori↗

DOE OSTI2022

Qubit Assignment Using Time Reversal

As quantum computers with large numbers of qubits become increasingly available, experiments executed on a given device may not utilize all available qubits. In this case, the outcome of executing a quantum program will depend on the ability to efficiently select a subset of high-performing physical qubits. For any given quantum program and device there are many ways to assign physical qubits for execution of the program, and assignments will differ in performance due to the variability in quality across qubits and entangling operations on a single device. Evaluating the performance of each assignment using fidelity estimation introduces significant experimental overhead and will be infeasible for many applications, while relying on standard device benchmarks provides incomplete information about the performance of any specific program. Furthermore, the number of possible assignments grows combinatorially in the number of qubits on the device and in the program, motivating the use of heuristic optimization techniques. We demonstrate a practical solution to the problem of qubit assignment by using simulated annealing with a cost function based on the Loschmidt echo, a diagnostic that measures the reversibility of a quantum process. We provide theoretical justification for this choice of cost function by demonstrating that the optimal qubit assignment coincides with the optimal qubit assignment based on state fidelity in the weak error limit, and we provide experimental justification using diagnostics performed on Google’s superconducting qubit devices. We then establish the performance of simulated annealing for qubit assignment using classical simulations of noisy devices as well as optimization experiments performed on a quantum processor. Our results demonstrate that the use of Loschmidt echoes and simulated annealing provides a scalable and flexible approach to optimizing qubit assignment on near-term hardware.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Visualization Quality Assessment

Understanding how inaccuracies in visualizations affect users’ perception and understanding of scientific data is hard. Inaccuracies in visualizations are quite common and could arise from a range of sources such as errors in the original dataset arising from compression artifacts, errors in the capturing device, noise during transmission of the data, effects due to the algorithm being used to convert data to visualization images, images generated from neural networks, and sources we have yet to discover. Many image quality assessment metrics have been developed to quantify image errors. However, these are usually focused on “natural images” rather than visualizations of scientific data. Common image quality assessment metrics (IQAs) include MSE, PSNR, perceptual metrics such SSIM, FSIM as well as perceptual metrics using deep learning approaches. However, a critical part of understanding how errors are perceived by humans, and subsequently developing more accurate quality assessment metrics, is through user evaluation studies. The goal of this software is to develop a visualization quality assessment (VQA) process that will enable the generation of VQAs that can be used to quantify errors in scientific data visualizations. The VQA development process will include software to support user evaluation experimental design, analysis of visualization differences against standard quality metrics, and the ability to develop additional VQA metrics specific to scientific visualization images.

Grosset, Andre↗

DOE OSTI2025

Ocpp 2.0.1. Interim Kpi Calculator

The project is split into four pieces. The first is a raw OCPP log parser. The second is a file splitter. The third is a message parser. The final piece is the Interim KPI calculator. The OCPP log parser was created from two different formats of raw OCPP 2.0.1 data. Its intended purpose is to extract device IDs and OCPP event messages from nontabular text logs. The parser looks for specific substrings in the logs to identify which of the two "standards" it should select from. The KPI generator does not perform any of its calculations in parallel. Instead, we opt for a naive batching approach. The splitter takes the file generated from the parser and creates many smaller files for each of the device IDs in the dataset. This allows the pandas queries in the log formatter to be iterate over a significantly smaller slice of data, increasing performance significantly. The message parser step takes messages from each of the files (containing distinct device IDs) and breaks the message out into pieces. The final result is a file with different columns specifying different attributes of the JSON message. The file is an aggregation of all different devices. This is the most complex portion of the code. The KPI calculator takes the parsed messages, as a single file, and calculates the KPI from that data. An excel file is produced with four sheets. These contain the metrics for Session Success, Charge Start Success, Charge End Success, and Charge Start Time. It includes the metrics for the different equations in the Interim KPI Implementation Guide as well as a weighted sum of the different equations for each KPI (excluding Charge End Success and Charge Start Time).

Quinn, Casey↗

DOE OSTI2021

Engineering well-expressed, V2-immunofocusing HIV-1 envelope glycoprotein membrane trimers for use in heterologous prime-boost vaccine regimens

HIV-1 vaccine immunofocusing strategies may be able to induce broadly-reactive neutralizing antibodies (NAbs). Here, we engineered a panel of diverse, membrane-resident native HIV-1 trimers vulnerable to two broad targets—the V2 apex and fusion peptide (FP). Selection criteria included i) high expression and ii) infectious function, so that trimer neutralization sensitivity can be profiled in pseudovirus (PV) assays. Initially, we boosted the expression of 17 candidate trimers by truncating gp41 and introducing a gp120-gp41 SOS disulfide to prevent gp120 shedding. "Repairs" were made to fill glycan holes and eliminate other strain-specific aberrations. A new neutralization assay allowed PV infection when our standard assay was insufficient. Trimers with exposed V3 loops, a target of non-NAbs, were discarded. To try to increase V2-sensitivity, we removed clashing glycans and modified the C-strand. Notably, a D167N mutation improved V2-sensitivity in several cases. Glycopeptide analysis of JR-FL trimers revealed near complete sequon occupation and that filling the N197 glycan hole was well-tolerated. In contrast, sequon optimization and inserting/removing glycans at other positions frequently had global "ripple" effects on glycan maturation and sequon occupation throughout the gp120 outer domain and gp41. V2 MAb CH01 selectively bound to trimers with small high mannose glycans near the base of the V1 loop, thereby avoiding clashes. Knocking in a rare N49 glycan was found to perturb gp41 glycans, increasing FP NAb sensitivity—and sometimes improving expression. Finally, a biophysical analysis of VLPs revealed that i) ~25% of particles bear Env spikes, ii) spontaneous particle budding is high and only increases 4-fold upon Gag transfection, and iii) Env+ particles express ~30–40 spikes. Taken together, we identified 7 diverse trimers with a range of sensitivities to two targets to allow rigorous testing of immunofocusing vaccine concepts.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

The Effect of Compressibility and Outer Boundaries on Incipient Viscous Fingering

The knowledge of the effects of instability and heterogeneity on displacements, primarily enhanced oil recovery, and carbon dioxide storage are well known, although they remain difficult to predict. Here, the usual recourse to modeling these effects is through numerical simulation. Simulation remains the gold standard for prediction; however, its results lack generality, being case-specific. There are also several analytic models for displacements that are usually more informative than simulation results. However, these methods apply to steady-state, incompressible flow.

02 PETROLEUM↗

DOE OSTI2020

Roles of Carburization and Oxidation on Transition-Metal Catalyzed Surface Reactions

Many industrial chemical transformation processes are based on reactions catalyzed by transition metals. In some cases the nano-size particles used as catalysts are synthesized simultaneously or right before the initiation of the main catalytic reaction. Synthesis treatments involve complex processes such as reductions followed by calcinations in oxygenated environments coupled to the presence of gases used for the main reaction. Synthesis details are crucial because they have important consequences on the catalyst shape, size, and chemical composition, and may also affect the structure and composition of the catalyst support. All these effects may alter the main catalyzed reaction in unexpected ways. This work focuses on the synthesis of the overall catalytic system that includes catalyst and support taking place in parallel with the initial stages of the main catalyzed reaction. Two important processes are characterized: carburization and oxidation of the transition metal catalyst during synthesis or initial stages of the main reaction. The objective is to understand how the coking mechanism coupled to surface oxidation and changes in the substrate influence the dry reforming of methane taken as a model reaction. The approach uses first principles computational methods to investigate the catalyst synthesis and characterization and catalytic reaction mechanisms. These studies are complemented with experimental characterization done by the group of Dr. Renu Sharma at the National Institute of Standards and Technology (unfunded collaborator) using high resolution transmission electron microscopy. Specific goals are to identify the role of the synthesis process on the initial nanocatalyst structure and composition, and to determine how that structure and composition may evolve after being exposed to the reactants atmosphere. These studies facilitate a systematic analysis of conditions where the nanoparticle composition can be optimized regarding activity and stability. Moreover, the fundamental study of catalyst/support interactions yields valuable insights for other catalytic processes and is a first step toward controlled nanocatalyst synthesis.

36 MATERIALS SCIENCE↗