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At least 37 records · Page 2

Controller area network decoder (CAN-D)

A system and method for decoding an unknown automotive controller area network (“CAN”) message definitions. CAN data vehicle signal mappings are typically held in secret and varied by automotive model and year. Without knowledge of the mappings, the wealth of real-time vehicle data hidden in the automotive CAN packets is uninterpretable—impeding research, after-market tuning, efficiency and performance monitoring, fault diagnosis, and privacy-related technologies. This technology can ascertain the CAN signals' boundaries (start bit and length), endianness (byte ordering), signedness (binary-to-integer encoding) from raw CAN data. This allows conversion of CAN data to time series. Interpreting the translated CAN data's physical meaning and finding a linear mapping to standard units (e.g., knowing the signal is speed and scaling values to represent units of miles per hour) can be achieved for many signals by leveraging diagnostic standards to obtain real-time measurements of in-vehicle systems. The system and method can be integrated into lightweight hardware enabling an OBD-II plugin for real-time in-vehicle CAN decoding or run on standard computers. The system can output a standard DBC file with the signal definition information.

Verma, Kiren E.↗

System for controller area network payload decoding

A system for decoding an unknown automotive controller area network (“CAN”) message definitions. CAN data vehicle signal mappings are typically held in secret and varied by automotive model and year. Without knowledge of the mappings, the wealth of real-time vehicle data hidden in the automotive CAN packets is uninterpretable—impeding research, after-market tuning, efficiency and performance monitoring, fault diagnosis, and privacy-related technologies. This system can ascertain the CAN signals' boundaries (start bit and length), endianness (byte ordering), signedness (binary-to-integer encoding) from raw CAN data. This allows conversion of CAN data to time series. Interpreting the translated CAN data's physical meaning and finding a linear mapping to standard units (e.g., knowing the signal is speed and scaling values to represent units of miles per hour) can be achieved for many signals by leveraging diagnostic standards to obtain real-time measurements of in-vehicle systems. The system can be integrated into lightweight hardware enabling an OBD-II plugin for real-time in-vehicle CAN decoding or run on standard computers. The system can output a standard DBC file with the signal definition information.

Verma, Kiren E.↗

Analysis of hydrogen infrastructure for the feasibility, economics, and sustainability of a fuel cell powered data center

Data centers used for internet data services, cloud computing, and/or data storage consume vast amounts of electricity and are increasing rapidly in capacity. Consequently, their power consumption has raised concerns about energy sustainability and environmental impacts. Large-scale, on-site renewable energy could help reduce data centers’ carbon footprint; however, wind and solar power alone cannot provide an uninterrupted power supply to computer servers due to their natural variability. Instead, reliable power integration can be achieved by using fuel cells powered by hydrogen from sustainable resources (e.g., wind and solar energy). Establishing a hydrogen infrastructure will be critical for realizing these benefits and establishing fuel cells as a viable power source for data centers. Here, to facilitate the development of novel carbon-free fuel cell data enters, this paper presents renewable power integrated with hydrogen infrastructures in four scenarios to provide reliable hydrogen supply from production to storage. Various paths were analyzed toward a hydrogen supply infrastructure by determining the proper component sizes and calculating the cost of meeting the server load. We used a microgrid modeling software, Hybrid Optimization of Multiple Energy Resources (HOMER), and studied the feasibility of fuel cell powered data centers employing renewable hydrogen. The modeling results show various renewable integration configurations to meet reliable and sustainable power requirement under four scenarios for a carbon-free data center.

08 HYDROGEN↗

21 cm Power Spectrum Analysis of North Celestial Pole Observations with the Tianlai Dish Pathfinder Array

The Tianlai Dish Pathfinder Array (TDPA) is a radio interferometer designed to test techniques for 21 cm intensity mapping in the post-reionization Universe as a means of measuring large-scale cosmic structure. Using nine nights of observations targeting the North Celestial Pole field, totaling approximately 107 hr of integration time, we analyze data in the frequency range 700–800 MHz (corresponding to redshift z ∼ 0.9). We do the data format conversion, radio frequency interference flagging, calibration, imaging and point source subtraction, and foreground removal via Singular Value Decomposition. The spherically averaged power spectrum Δ 2 (k) is obtained. Furthermore, this work successfully establishes and validates a comprehensive data analysis framework for the TDPA. We identify key improvements including sky model refinement, increased integration time, and pipeline optimization that will enable future detection of the 21 cm signal through auto-correlation and cross-correlation with optical galaxy surveys.

cosmology: large-scale structure of universe↗

Community Data Mining Approach for Surface Complexation Database Development

This paper presents a comprehensive data-to-model workflow, including a findable, accessible, interoperable, reusable (FAIR) community sorption database (newly developed LLNL Surface Complexation/Ion Exchange (L-SCIE) database) along with a data fitting workflow to efficiently optimize surface complexation reaction constants with multiple surface complexation model (SCM) constructs. This workflow serves as a universal framework to mine, compile, and analyze large numbers of published sorption data as well as to estimate reaction constants for parameterizing reactive transport models. Here the framework includes (1) data digitization from published papers, (2) data unification including unit conversions, and (3) data-model integration and reaction constant estimation using geochemical software PHREEQC coupled with the universal parameter estimation code PEST. We demonstrate our approach using an analysis of U(VI) sorption to quartz based on a first L-SCIE implementation, concluding that a multisite SCM construct with carbonate surface species yielded the best fit to community data. Surface complexation reaction constants extracted from this approach captured all available sorption data available in the literature and provided insight into previously published reaction constants and surface complexation model constructs. The L-SCIE sorption database presented herein allows for automating this approach across a wide range of metals and minerals and implementing novel machine learning approaches to reactive transport in the future.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

NP-MRD: the Natural Products Magnetic Resonance Database

The Natural Products Magnetic Resonance Database (NP-MRD) is a comprehensive, freely available electronic resource for the deposition, distribution, searching and retrieval of nuclear magnetic resonance (NMR) data on natural products, metabolites and other biologically derived chemicals. NMR spectroscopy has long been viewed as the ‘gold standard’ for the structure determination of novel natural products and novel metabolites. NMR is also widely used in natural product dereplication and the characterization of biofluid mixtures (metabolomics). All of these NMR applications require large collections of high quality, well-annotated, referential NMR spectra of pure compounds. Unfortunately, referential NMR spectral collections for natural products are quite limited. It is because of the critical need for dedicated, open access natural product NMR resources that the NP-MRD was funded by the National Institute of Health (NIH). Since its launch in 2020, the NP-MRD has grown quickly to become the world's largest repository for NMR data on natural products and other biological substances. It currently contains both structural and NMR data for nearly 41,000 natural product compounds from >7400 different living species. All structural, spectroscopic and descriptive data in the NP-MRD is interactively viewable, searchable and fully downloadable in multiple formats. Extensive hyperlinks to other databases of relevance are also provided. The NP-MRD also supports community deposition of NMR assignments and NMR spectra (1D and 2D) of natural products and related meta-data. The deposition system performs extensive data enrichment, automated data format conversion and spectral/assignment evaluation.

59 BASIC BIOLOGICAL SCIENCES↗

Data for Catalytic Strategy for Conversion of Triacetic Acid Lactone to Potassium Sorbate

This study shows a new route to produce potassium sorbate (KS) from triacetic acid lactone (TAL), which is a chemical platform that can be biologically synthesized from natural sources. Sorbic acid and its potassium salt (KS) are widely used as preservatives in foods and pharmaceuticals. Three steps are used to produce KS from TAL: 1) hydrogenation of TAL into 4-hydroxy-6-methyltetrahydro-2-pyrone (HMP), 2) dehydration of HMP to parasorbic acid (PSA), and 3) ring-opening and hydrolysis of PSA to KS. TAL can be fully hydrogenated over Ni/SiO2 to give near quantitative yields of HMP. A three-step reaction kinetics model was developed for dehydration of HMP into PSA. This model was used to show that the highest PSA yield occurs at low temperatures. An experimental PSA yield of 84.2% with respect to TAL was obtained which agreed with the prediction of the reaction kinetics model. KOH was used as a coreactant for the ring-opening hydrolysis of PSA to produce >99.9% yield of KS from PSA. Tetrahydrofuran (THF) was used to purify the TAL derived-KS (TAL-KS). The TAL-KS had a KS purity of 95.5%. The overall yield of TAL-KS with respect to TAL was calculated to be 77.3%. TAL-KS produced in this study had similar antimicrobial activities as commercial KS.

Catalysis↗

Reaching the Excitonic Limit in 2D Janus Monolayers by In Situ Deterministic Growth

Abstract Named after the two‐faced Roman god of transitions, transition metal dichalcogenide (TMD) Janus monolayers have two different chalcogen surfaces, inherently breaking the out‐of‐plane mirror symmetry. The broken mirror symmetry and the resulting potential gradient lead to the emergence of quantum properties such as the Rashba effect and the formation of dipolar excitons. Experimental access to these quantum properties, however, hinges on the ability to produce high‐quality 2D Janus monolayers. Here, these results introduce a holistic 2D Janus synthesis technique that allows real‐time monitoring of the growth process. This prototype chamber integrates in situ spectroscopy, offering fundamental insights into the structural evolution and growth kinetics, that allow the evaluation and optimization of the quality of Janus monolayers. The versatility of this method is demonstrated by synthesizing and monitoring the conversion of SWSe, SNbSe, and SMoSe Janus monolayers. Deterministic conversion and real‐time data collection further aid in conversion of exfoliated TMDs to Janus monolayers and unparalleled exciton linewidth values are reached, compared to the current best standard. The results offer an insight into the process kinetics and aid in the development of new Janus monolayers with high optical quality, which is much needed to access their exotic properties.

2D materials↗

Conversion of Site-Specific Meteorological Data for use in CAP-88 PC

CAP-88 PC is a commonly used radiological atmospheric dispersion model. This US EPA-approved model is used to demonstrate compliance with atmospheric emission regulations for radionuclides. While the model includes a large library of meteorological data for use across the United States, there are applications when users may wish to use onsite meteorological data as an input to the CAP-88 PC model. Here, in this work, we present a work-around process for preparing and converting onsite data for use in CAP-88 PC. However, the use of local data should provide a more realistic estimate of doses to members of the public in the immediate vicinity of a facility, although the regulatory agency having jurisdiction may not accept the use of local data for compliance. Additionally, the historical meteorological records from 20+ years ago (at a site many kilometers away) might not be representative of current local weather patterns, highlighting another benefit of using local meteorological data.

54 ENVIRONMENTAL SCIENCES↗

Biochemical Conversion of Lignocellulosic Biomass to Hydrocarbon Fuels and Products (2021 State of Technology and Future Research)

The annual State of Technology (SOT) assessment is an essential activity for biochemical platform research. It allows the impact of research progress to be quantified in terms of economic improvements in the overall cellulosic biofuel production process for a particular conversion pathway. As such, initial benchmarks can be established for currently demonstrated performance and progress can be tracked towards out-year goals to ultimately demonstrate cost-competitive cellulosic biofuel technology. The purpose of this report is to benchmark the latest experimental developments across a number of potential bioconversion pathways as quantified by modeled minimum fuel selling prices (MFSPs), as a measure of current status relative to those final targets. For this state of technology, TEA models were run for two separate biological conversion pathways to fuels, based on available data for integrated biomass deconstruction and hydrolysate processing; namely carboxylic acids (primarily butyric acid) and diols (2,3-butanediol [BDO]), reflecting NREL's recently-published 2018 biochemical design report focused on those two pathways. The models were run across three scenarios for lignin utilization, namely combustion, conversion to coproducts based on "base case" performance with biomass hydrolysate, and conversion to coproducts based on "high" performance demonstrated with model lignin monomer components. A key improvement reflected in the 2021 SOT is centered around making use of the latest lignin conversion data, which over the past year focused primarily on production of ß-ketoadipate (BKA) as a more optimal molecule compared to the closely-related adipic acid coproduct of prior recent focus, both in terms of superior product properties and biology, as well as reduced processing complexity (reducing two steps for sequential production of muconate followed by hydrogenation to adipic acid down to a single step for direct production of BKA). This update translated to a roughly 17% increase in mass yield of final coproduct output at a nearly four-fold increase in fermentation productivity on lignin monomers relative to prior 2020 SOT benchmarks for muconic/adipic acid production.

09 BIOMASS FUELS↗

Oscilloscope Data Push Program

This paper details the development of a Python program designed to automate the data acquisition and conversion for an oscilloscope for the purposes of a one-off/temporary data acquisition system for users that readily need data, and do not have the option of obtaining a Data Acquisition (DAQ) solution. Creating DAQ systems for analyzing a system requires expensive electronics and a dedicated team of engineers for support. Traditionally, manual data collection and processing are time consuming and prone to error. By automating these processes, the cost, efficiency and accuracy of data handling are improved upon. This project involves the creation of a program that interacts with the oscilloscope. During this interaction, there are various functions being performed such as the acquisition of waveform data via floating points, generating plots with the acquired wave points, and storing of floating points in a CSV file format for future reference and plotting purposes. While the initial aim of the project included continuous logging to a cloud database, this was deferred due to time constraints. The results portrayed an almost-instant rate of data collection with a buffer time, showcasing the potential for further integration and real-time data processing.

Osei-Tutu, Jason↗

The Perils of AI-Assisted Time Conversion Critical Errors in J2000 Time to UNIX/UTC Conversions Using AI Assistants (Technical Memorandum)

This memo addresses a critical issue encountered when using AI assistants for time system conversions, specifically converting data tagged with J2000 seconds through UNIX time to UTC. Initial AI responses to this common conversion task were fundamentally incorrect, with errors exceeding 37 seconds - enough to cause significant issues in many applications. This document demonstrates the problem, quantifies the error, and provides best practices for using AI tools safely in technical work. Both Claude 4.5 Sonnet and ChatGPT GPT-5.5 Thinking gave the same answer.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

High-Reliability Systems and the Control of National Security Data and Information

High-reliability systems are characterized by catastrophic implications in the event of failure. These implications can include substantive damage to the environment, social order, and loss of life. Examples of high-reliability systems include nuclear submarines, nuclear reactors, the electric grid, and nuclear weapons. Due to the catastrophic implications of failure, there are heightened awareness and control mechanisms surrounding related data and information. However, defining the difference between data and information is often ambiguous across scholarly disciplines and in United States policy and legislation. For high-reliability systems, the implications of ambiguity between data and information may affect the security of United States interests and even cost lives. For security, data are raw facts or figures without context, while information is the compilation or articulation of data that forms context. Security depends on clarity in the differences between data and information and how to control them. Control is necessary to ensure that data and information are not unintentionally released to foreign governments, the public, or those without need-to-know. A primary concern in the practice of security is the control of data to avoid the unintended conversion to information. Intra-institutionally, this control is highly complex given the amalgam of legacy data systems and the numerous and constantly evolving nature of modern data systems that were not necessarily designed to be integrated. The complexity of this concern is augmented when institutions are part of interinstitutional collaborations or networks of public-private partnerships that share data and information. Additionally, institutions that share data as a function of policy and legislative action— particularly formally integrated data and information system infrastructures—may be at higher security risk. This paper will present an intra-institutional paradigm that utilizes and integrates concepts from numerous disciplines to frame a critical and underspecified practical issue in security—controlling for the unintended conversion of data to information.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

High-Reliability Systems and the Control of National Security Data and Information

High-reliability systems are characterized by catastrophic implications in the event of failure. These implications can include substantive damage to the environment, social order, and loss of life. Examples of high-reliability systems include nuclear submarines, nuclear reactors, the electric grid, and nuclear weapons. Due to the catastrophic implications of failure, there are heightened awareness and control mechanisms surrounding related data and information. However, defining the difference between data and information is often ambiguous across scholarly disciplines and in United States policy and legislation. For high-reliability systems, the implications of ambiguity between data and information may affect the security of United States interests and even cost lives. For security, data are raw facts or figures without context, while information is the compilation or articulation of data that forms context. Security depends on clarity in the differences between data and information and how to control them. Control is necessary to ensure that data and information are not unintentionally released to foreign governments, the public, or those without need-to-know. A primary concern in the practice of security is the control of data to avoid the unintended conversion to information. Intra-institutionally, this control is highly complex given the amalgam of legacy data systems and the numerous and constantly evolving nature of modern data systems that were not necessarily designed to be integrated. The complexity of this concern is augmented when institutions are part of inter-institutional collaborations or networks of public-private partnerships that share data and information. Additionally, institutions that share data as a function of policy and legislative action—particularly formally integrated data and information system infrastructures—may be at higher security risk. This paper will present an intra-institutional paradigm that utilizes and integrates concepts from numerous disciplines to frame a critical and underspecified practical issue in security—controlling for the unintended conversion of data to information.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Production of 1,3-Butadiene from Renewable Oxygenated Feedstocks (Abstract)

Reproduce and ascertain additional experimental catalyst performance data for 1-step conversion of oxygenated feedstocks to butadiene. Experimental data will also be obtained for a 2-step processing configuration where we will tailor the PNNL catalyst originally developed for 1-step processing by tailoring the Lewis acidity and metal properties, with a limited number of experiments. We will measure preliminary catalyst performance results for producing Butadiene from the two oxygenated feedstocks. Additionally, we will produce 30 g of butadiene that will be sent to the client for use in producing polybutadiene. Finally, experimental results will inform techno-economic analysis (TEA) modeling. TEA will focus on identifying the most economically favorable processing route to BD from either oxygenated feedstock. We will also project GHG emissions associated with each of the process models being considered for BD production, and compare such results to GHG emissions when produced from conventional methods (e.g., cracking of naphtha) using values from the literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Particle Scale Impacts on Deconstruction Energy of Pine Residues

The goal of this Case Study was to quantify the impacts of variable moisture and ash on hammer mill throughput and energy consumption and on generation of fines that are not able to be fed to conversion, as compared to a status quo Base Case system. Also considered was convertible carbon content (minimum carbon specification) and maximum ash content and the delivered feedstock cost impacts of not being able to feed residue not meeting both specifications to the conversion reactor. Laboratory data on the impacts of input particle size and moisture content on the exit particle size were received from FCIC Subtask 5.2: Preprocessing, High Temperature Conversion Preprocessing from their single particle impact population balance modeling study (Tiasha Bhattacharjee, INL). Additional throughput and energy consumption data were obtained from FCIC Subtask 5.2 (Jordan Klinger, INL) for the same grinder with a 6 mm screen in place. These data were utilized to develop the necessary response surface equations to perform throughput analysis using discrete event simulation. Because the ash contents in the separated fines had not been analyzed in the laboratory at the time of the model runs, we chose to assume that the ash distributed proportionally with total mass into the overs and unders in the disk screen following grinding.

energy consumption↗

Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS

The Marine Algae Industrialization Consortium (MAGIC) was formed to address pressing challenges in the commercialization of microalgae as a source of biofuel. The “Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS” project formally addressed two US Department of Energy Bioenergy Technologies Office (BETO) goals: (1) Model the sustainable supply of 1 million metric tonnes ash free dry weight (AFDW) cultivated algal biomass and (2) Demonstrate valuable co-products produced along with biofuel intermediates to increase value of algal biomass by 30%. To achieve these goals, the project demonstrated and validated high-value co-products to drive down the cost of biofuel by increasing the value of algae “co-products” towards increasing the selling price of total algae biomass as one of the key drivers of economics and adoption. This was accomplished through five core, interdependent tasks including: (1) strain selection to identify and deliver strains for mass culture, (2) mass culture using a hybrid cultivation system and following key operating parameters for downstream applications to provide algae feedstock, (3) recovery and conversion to evaluate two alternative methods to separate dry algae biomass into oil and residuals for downstream testing, (4) product assessment to determine biofuel, aquafeed or poultry feed product efficacy using algae biomass fractions as well as to provide critical performance data for valuation and (5) commercialization to use technoeconomic and life cycle assessments (TEA/LCA) as iterative design and assessment tools including consideration of target markets, competitors, and distribution channels to guide product assessment, development and valuation. A total of 46 peer-review publications, many open-access, provide detail of much of the work carried out and the results of the tasks. Additional reports and presentations provide other technical and public engagement material. At a high level, using a variety of approaches, more than 1000 marine microalgae strains were evaluated to ultimately identify the seven winners that were down-selected to be grown in mass culture. Strain selection demonstrated that there were no ‘super strains’ and that each candidate had strengths and limitations for specific products, growth conditions or operational considerations. Mass culture growth of these seven strains at >5000 L / 29 m 2 scale found that four them were suitable for product assessment. More than 250 kg of biomass was produced across hundreds of pond runs along with thousands of cultivation entries on the growth and biomass characteristics as well as environmental parameters. In the process, dozens of standard operating procedures were generated as was custom software to process and analyze cultivation data. Recovery and conversion of algae biomass demonstrated that a hexane solvent based extraction protocol was most effective at recovering oil (biocrude) from algae and four strains were processed to produce oil and lipid extracted algae (residuals) for downstream testing. Membrane-based oil separation was less successful, but may still be applicable to other commercial applications in the future. Product testing demonstrated that algae biocrude is of high quality and hydrotreating generated numerous fractions of high quality composition for fuel and lubricate based applications. Aquafeed studies performed at a variety of scales showed that both whole and defatted (lipid extracted algae) microalgae were suitable as a feed ingredient, but that the specifics of the fed animal and biochemical composition of the algae are critical factors when determining formulation. Similarly, poultry studies on whole and defatted microalgae generally showed positive outcomes on animal growth and health, with some microalgae providing enhanced nutritional composition of the animal product. Economic and life cycle assessments covered a wide range of possible commercialization and sustainability scenarios. Replacement value, improved product value added, consumer values marketing added valuation and improved animal health were considered as alternatives for microalgae valuation. Using the open pond system, algae productivity was identified as the key driver of commercialization economics, but combination of co-products (e.g. animal feed) with biofuel production substantially increased the total selling price of algae. Modeled microalgae selling price exceeded $\$$1500/tonne and could generate competitive biofuel selling prices below $\$$5 gallon gas equivalents using realistic algal productivities. Short (process scale) and longer (decadal trends) sustainability assessments show that marine microalgae can enhance the sustainability of energy production and lead to other realized benefits in water, fertilizer and land use for other sectors (e.g. agriculture). This project successfully demonstrated all of the components of an end-to-end process from mass microalgae cultivation and dewatering, to recovery and conversion of algae biomass components, to final product demonstration and process valuation; the combined results provide a framework for future commercialization of algae based biofuels.

09 BIOMASS FUELS↗