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At least 289 records · Page 16

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DOE OSTI2026

Industrial deposition of wavelength-shifting films for liquid argon photon detection systems

The Deep Underground Neutrino Experiment (DUNE) Phase-II Far Detector is considering an approximately 2000 m 2 photon detection system to achieve a target mean light yield of 180 PE/MeV. Meeting this requirement demands scalable, cost-effective, and high-quality wavelength-shifter (WLS) coatings capable of converting 127 nm liquid-argon scintillation light into visible photons with controlled and reproducible optical performance. We report on the successful realization of an industrial physical vapor deposition (PVD) process forp-terphenyl (pTP) coatings, adapted from vacuum deposition techniques developed for OLED display manufacturing, to produce uniform WLS layers on large-area inorganic substrates, a task traditionally challenged by adhesion and uniformity issues at organic-inorganic interfaces. Surface characterization by profilometry and spectroscopic measurements demonstrates edge-region thickness variation below 10% and emission spectra consistent with high-quality pTP reference samples. The industrial process demonstrates reproducibility, scalability, and significantly reduced production time compared to laboratory-based methods, while maintaining optical characteristics consistent with established pTP reference samples. These results establish a viable pathway for mass production of high-performance pTP coatings for DUNE FD3 and future neutrino experiments, from a coating manufacturing and process standpoint. Detector-level performance validation, including quantitative VUV conversion efficiency measurements at 127 nm, is identified as future work.

47 OTHER INSTRUMENTATION↗

DOE OSTI2026

Pathways of bio-jet adoption in the US aviation industry with implications for the overall transportation and energy sectors: an integrated, multi-sectoral analysis of future scenarios

Bio-jet adoption has emerged as an attractive option to complement and supplement the use of refined fossil liquid fuels in the aviation industry in the US. However, there are significant uncertainties surrounding the costs of bio-jet including but not limited to costs of feedstock, transformation costs and the competition with co-products of bio-jet that may be demanded elsewhere in the transportation or energy sectors. This study models alternative trajectories of bio-jet adoption in the US aviation industry by 2050 through the use of a global integrated multi sector dynamics model. Three bio-jet production and consumption pathways are presented- soybean oil to jet, corn ethanol to jet (ETJ) and Fisher–Tropsch-based bio-jet, with each pathway explicitly considering the co-production of renewable diesel and renewable gasoline alongside the bio-jet. Without explicit actions or technology changes to offset the technology cost of bio-jet, scenarios where bio-jet displaces refined liquids result in higher aviation fuel prices (ranging from a 25% increase to 120% increase by mid-century) and lower demand (ranging from −14% to −43%). Corn ethanol will play an important role in the US if large scale amounts of bio-jet are to be produced with smaller effects on demand and prices. While scenarios with high levels of bio-jet availability without the availability of ETJ in the US can significantly reduce emissions in the aviation sector, these reductions are achieved more through the reduction in overall aviation fuel demand rather than technology adoption.

09 BIOMASS FUELS↗

DOE OSTI2024

Energy and nutrient recovery from municipal and industrial waste and wastewater—a perspective

This publication highlights the latest advancements in the field of energy and nutrient recovery from organics rich municipal and industrial waste and wastewater. Energy and carbon rich waste streams are multifaceted, including municipal solid waste, industrial waste, agricultural by-products and residues, beached or residual seaweed biomass from post-harvest processing, and food waste, and are valuable resources to overcome current limitations with sustainable feedstock supply chains for biorefining approaches. The emphasis will be on the most recent scientific progress in the area, including the development of new and innovative technologies, such as microbial processes and the role of biofilms for the degradation of organic pollutants in wastewater, as well as the production of biofuels and value-added products from organic waste and wastewater streams. The carboxylate platform, which employs microbiomes to produce mixed carboxylic acids through methane-arrested anaerobic digestion, is the focus as a new conversion technology. Nutrient recycling from conventional waste streams such as wastewater and digestate, and the energetic valorization of such streams will also be discussed. The selected technologies significantly contribute to advanced waste and wastewater treatment and support the recovery and utilization of carboxylic acids as the basis to produce many useful and valuable products, including food and feed preservatives, human and animal health supplements, solvents, plasticizers, lubricants, and even biofuels such as sustainable aviation fuel.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Expanding the genetic toolset: using serine recombinases to integrate riboregulatory elements into industrially relevant microbial chassis

To realize the full potential of biomanufacturing, the breadth of industrial microbes used to consume diverse feedstock and generate bioproducts needs to expand. As such, portable tools are required that can be used by multiple hosts for straightforward genomic manipulation and precise gene expression. Here, we demonstrate the co-utilization of two synthetic biology tools to achieve these goals: cis-repressors (CRs) and serine recombinase-assisted genome engineering (SAGE). CRs are small, noncoding RNAs that are placed upstream of the target gene to modulate bacterial translation rates at varying, discrete levels. SAGE uses site-specific serine recombinases to catalyze highly efficient, unidirectional insertion of DNA into the chromosome of diverse organisms. We used SAGE to integrate a suite of CRs into the industrially relevant hosts Pseudomonas putida, Corynebacterium glutamicum, and Cupriavidus necator. Using a fluorescent reporter as a readout of CR functionality, we found that CR performance across these backgrounds was similar—providing a range of translational repression up to 100-fold. Overall, these results demonstrate the high portability of CRs across bacterial genetic backgrounds, which ideally can be used in future microbial engineering efforts pertinent to biomanufacturing.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Bimodal Visualization of Industrial X-Ray and Neutron Computed Tomography Data

Advanced manufacturing creates increasingly complex objects with material compositions that are often difficult to characterize by a single modality. Our collaborating domain scientists are going beyond traditional methods by employing both X-ray and neutron computed tomography to obtain complementary representations expected to better resolve material boundaries. However, the use of two modalities creates its own challenges for visualization, requiring either complex adjustments of bimodal transfer functions or the need for multiple views. Together with experts in nondestructive evaluation, we designed a novel interactive bimodal visualization approach to create a combined view of the co-registered X-ray and neutron acquisitions of industrial objects. Using an automatic topological segmentation of the bivariate histogram of X-ray and neutron values as a starting point, the system provides a simple yet effective interface to easily create, explore, and adjust a bimodal visualization. Here, we propose a widget with simple brushing interactions that enables the user to quickly correct the segmented histogram results. Our semiautomated system enables domain experts to intuitively explore large bimodal datasets without the need for either advanced segmentation algorithms or knowledge of visualization techniques. We demonstrate our approach using synthetic examples, industrial phantom objects created to stress bimodal scanning techniques, and real-world objects, and we discuss expert feedback.

image segmentation↗

DOE OSTI2024

Economic and environmental bottlenecks in the industrial‐scale production of lipid‐derived biofuels from oleaginous yeasts: A review of the current trends and future prospects

Abstract Concerns about climate change and the reliance on fossil fuel reserves have motivated researchers to identify new renewable sources of energy. Biomass holds the potential to replace fossil‐derived products with biofuels and bio‐based chemicals. Plant‐derived lipids are promising sources of biofuels; however, the production of plant oil often leads to the release of massive amounts of carbon dioxide due to deforestation and land‐use change. The production of biofuels via plant oils (such as soybean) also competes with food production and in turn, impacts biodiversity. To mitigate these issues, the production of lipids from oleaginous yeasts could be an excellent alternative by incorporating these microbes into biorefineries utilizing agricultural or forest residues. Eventually, these microbial lipids could be potential sources for producing lipid‐derived biofuels. However, the current conventional methods for the production and recovery of lipids from oleaginous microbes suffer from economic and ecological challenges that affect its industrial‐scale expansion. This review highlights the major economic and environmental bottlenecks for the production of lipid‐derived biofuels from oleaginous yeasts. It also provides perspectives on the strategies that could be adapted on economic and ecological fronts to assist the expansion of the production of microbial lipid‐derived biofuels at an industrial scale.

Agriculture↗

DOE OSTI2024

Glaciation of liquid clouds, snowfall, and reduced cloud cover at industrial aerosol hot spots

The ability of anthropogenic aerosols to freeze supercooled cloud droplets remains debated. Here, in this work, we present observational evidence for the glaciation of supercooled liquid-water clouds at industrial aerosol hot spots at temperatures between -10° and -24°C. Compared with the nearby liquid-water clouds, shortwave reflectance was reduced by 14% and longwave radiance was increased by 4% in the glaciation-affected regions. There was an 8% reduction in cloud cover and an 18% reduction in cloud optical thickness. Additionally, daily glaciation-induced snowfall accumulations reached 15 millimeters. Glaciation events downwind of industrial aerosol hot spots indicate that anthropogenic aerosols likely serve as ice-nucleating particles. However, rare glaciation events downwind of nuclear power plants indicate that factors other than aerosol emissions may also play a role in the observed glaciation events.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Tantalum-stabilized ruthenium oxide electrocatalysts for industrial water electrolysis

The iridium oxide (IrO 2 ) catalyst for the oxygen evolution reaction used industrially (in proton exchange membrane water electrolyzers) is scarce and costly. Although ruthenium oxide (RuO 2 ) is a promising alternative, its poor stability has hindered practical application. Here, we used well-defined extended surface models to identify that RuO 2 undergoes structure-dependent corrosion that causes Ru dissolution. Tantalum (Ta) doping effectively stabilized RuO 2 against such corrosion and enhanced the intrinsic activity of RuO 2 . In an industrial demonstration, Ta-RuO 2 electrocatalyst exhibited stability near that of IrO 2 and had a performance decay rate of ~14 microvolts per hour in a 2800-hour test. At current densities of 1 ampere per square centimeter, it had an overpotential 330 millivolts less than that of IrO 2 .

Zhang, Jiahao [Sichuan Univ., Chengdu (China); Uni↗

DOE OSTI2025

Data for Influence of Particle Size on NIR Spectroscopic Characterization of Sorghum Biomass for the Biofuel Industry

NIR spectroscopy is a rapid and accurate green technology for high-throughput biomass characterization, including sorghum ( Sorghum bicolor ), a promising energy crop for the biofuel industry. This study assessed the influence of particle size on NIR spectroscopic analysis (wavelength range: 867–2535 nm) of sorghum biomass composition. Grown under field conditions, a total of 113 types of genetically diverse sorghum accessions were dried, ground, and sieved (<250, 250–600, 600–850, and > 850 µm particle size) for developing partial least square regression (PLSR) prediction models for moisture, ash, extractive, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin (ASL + AIL). Overall, smaller particle sizes provided better model performance, while no single particle size provided the best performance for all the selected components. With only 9 selected bands and 4 latent variables (LVs), the best PLSR model was obtained for moisture with particle size of 600–850 µm with the square root of the coefficient of determination (R) of 0.85, the ratio of prediction to deviation (RPD) of 2.2, and the root mean square error (RMSE) of 0.46 % in external validation. Similar model performances were also obtained for ash, extractive, glucan, and xylan. This study showed that size reduction could effectively improve NIR spectroscopic analysis for lipid-producing sorghum biomass for the biofuel industry.

Biomass Analytics↗

DOE OSTI2025

Animal movement estimation and network-based epidemic modeling: Illustration for the swine industry in Iowa (US)

Animal movement plays a critical role in disease transmission between farms. However, in the United States, the lack of available animal shipment data, sometimes coupled with a lack of detailed information about farm demographics and characteristics, presents great challenges for epidemic modeling and prediction. In this study, we proposed a new method based on the maximum entropy to generate “synthetic” animal movement networks, considering available statistics about the premises operation type, operation size, and the distance between premises. We illustrated our method for the swine movement networks in Iowa and performed network analyses to gain insights into the swine industry. We then applied the generated networks to a network-based epidemic model to identify potential system vulnerabilities in terms of disease transmission. The model was parameterized for African Swine Fever (ASF) as the US swine industry is quite concerned about this disease. Results show that premises with a central role in the network are more vulnerable to disease outbreaks and play an important role in disease spread. Simulations with outbreaks starting from random farms reveal no significant large outbreaks, indicating the system’s relative robustness against arbitrary disease introductions. However, outbreaks originating from high out-degree farms can lead to large epidemic sizes. This underscores the importance for stakeholders and policymakers to continue improving animal movement records and traceability programs in the US and the value of making that data available to epidemiologists and modelers to better understand risk and inform strategies aimed to cost-effectively prevent and control disease transmission. Our approach could be easily adapted to estimate movement networks in other animal production systems and to inform disease spread models for various infectious diseases.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Exploring Continuous Seismic Data at an Industry Facility Using Unsupervised Machine Learning

Seismic data recorded at industrial sites contain valuable information on anthropogenic activities. With advances in machine learning and computing power, new opportunities have emerged to explore the seismic wavefield in these complex environments. We applied two unsupervised machine learning algorithms to analyze continuous seismic data collected from an industrial facility in Texas, United States. The Uniform Manifold Approximation and Projection for Dimension Reduction algorithm was used to reduce the dimensionality of the data and generate 2D embeddings. Then, the Hierarchical Density-Based Spatial Clustering of Applications with Noise method was employed to automatically group these embeddings into distinct signal clusters. Our analysis of over 1400 hr (around 59 days) of continuous seismic data revealed five and seven signal clusters at two separate stations. At both stations, we identified clusters associated with background noise and vehicle traffic, with the latter’s temporal patterns aligning closely with the facility’s work schedule. Furthermore, the algorithms detected signal clusters from unknown sources and underline the ability of unsupervised machine learning for uncovering previously unrecognized patterns. Our analysis demonstrates the effectiveness of unsupervised approaches in examining continuous seismic data without requiring prior knowledge or pre-existing labels.

58 GEOSCIENCES↗

DOE OSTI2024

PROGRESS ON MAGNETRON R&DS FOR INDUSTRIAL PARTICLE ACCELERATORS

The magnetron as an efficient RF source for a compact industrial SRF accelerator has been developed. The per-formance of injection phase lock on two independent magnetron transmitters operated at 915MHz, in CW mode with maximum power of 75kW each has been demon-strated to satisfy this application. This industrial type magnetron has AC transformer and the SCR rectifier on the DC anode power supply. Output power spectrum with phase locking can achieve noise reduction of -21.2 dBc at the 1st 60 Hz, -28.0 dBc at 1st 180 Hz with only -22.6 dBc injection power. Further control studies for 2×75 kW, 915 MHz power combing by WR975 magic-tee at Jefferson Lab (JLab) and for 4×1.2 kW, 2.45 GHz power combing by WR340 magic-tee at General Atomics (GA).

Rimmer, R.↗

DOE OSTI2024

CW copper injector for SRF industrial cryomodules

Compact SRF industrial linacs can provide unique parameters of the beam (>1 MW and >1-10 MeV) hardly achievable by normal conducting linacs within limited space. SRF technology was prohibitively expensive until the development of conduction cooling which opened the way for compact stand alone SRF systems suitable for industrial and research applications. Limited cooling capacity puts strict requirements on the beam parameters with zero losses of the beam on the SRF cavity walls. This implies strict requirements on the beam energy to be accepted by the cryomodule and most importantly the beam bunching with zero particles in between. We designed a CW normal conducting RF injector which consists of a gridded RF gun integrated with a first cell of a copper booster cavity to satisfy these requirements. Here we present a complete design of a booster cavity including beam dynamics, RF, thermomechanical and engineering design.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

Efficient continuous-wave normal conducting accelerator for industrial applications

A normal conducting, high power, high efficiency copper linear accelerator prototype is being developed for industrial applications. The system will be powered by low-cost high-efficiency magnetron RF sources and will use a gridded thermionic cathode electron gun. Leveraging the significant accelerator expertise at JLab and industry partners, these technologies will be combined to deliver high-power (>100 kW) electron beams with energies of 1 MeV or higher that are cost-effective to produce and operate. The design is modular such that energy and power can be increased by adding additional sections as required. The status of the design, prototype fabrication and plans for a beam demonstration at JLab are described.

Accelerator Physics↗

DOE OSTI2024

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↗

DOE OSTI2024

Review of In Situ Sensing for Directed Energy Deposition for Industrial Part Quality Assessment

As the use additive manufacturing (AM) processes continues to grow in critical industries, improved quality assurance methods are becoming increasingly sought after for qualification and certification of AM components. Traditional nondestructive evaluation of printed components is often unable to supply the required confidence in print quality to justify qualification and certification, but the layer-by-layer nature of AM provides unprecedented opportunities for in situ quality inspection. This document summarizes recent developments in process monitoring research specifically related to Directed Energy Deposition (DED). Particular attention is given to three aspects of the highlighted manuscripts: (1) the type of sensors used, (2) features extracted from each sensor modality, and (3) analysis of extracted features for AM quality assessment. Based on the review of the state-of-the-art, several observations have been made. First, none of the reviewed works have applied their trained models to real part geometries, with many of the works relying on single track experiments, thin-walled structures, and cubes. Similarly, there have not been any works demonstrating model generalizability, i.e., a model trained on data from one build allows for fruitful analysis of data from another build. Many works used machine learning techniques to distinguish different process regimes (i.e., normal, keyholing, lack-of-fusion), but very few papers have investigated stochastic variation in an already “optimized” process. Sensor fusion approaches are also limited in the DED sensing literature, but the few works that have employed such techniques have demonstrated the benefits. Finally, registration of in situ data to the build coordinate system is of paramount importance to producing industrially relevant in situ monitoring systems. Data registration allows direct correlations between process anomalies detected in the process monitoring data to localized departures in part quality, but such techniques are generally lacking in the current literature.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Industrial Carbon Capture from a Cement Facility Using the Cryocap FG Process (FE0032136)

The project's objective was to execute and complete front-end engineering and design (FEED) studies for commercial-scale, carbon capture projects that separate 95% of the total CO2 emissions at an industrial facility, producing at least 100,000 metric tonnes/year of CO2 for sequestration. The industrial facility selected is the Holcim (US) Ste. Genevieve cement manufacturing facility (the largest single kiln line in the world), while the carbon capture system selected is Pressure Swing Adsorption system (PSA) assisted Cryocap™ technology developed by Air Liquide. The impact of the project on Environmental Justice and the regional economy was also analyzed.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2025

Integrating an Industrial Source and Commercial Algae Farm with Innovative CO 2 Transfer Membrane and Improved Strain Technologies

This report describes the overall findings of the research project “Integrating an Industrial Source and Commercial Algae Farm with Innovative CO 2 Transfer Membrane and Improved Strain Technologies”. The motivation and goal for this project were to increase the carbon utilization efficiency (CUE) and areal productivity for algal cultivations, thereby reducing CO 2 costs to cultivation operations and improving economics. This was achieved through a combination of enhanced delivery of inorganic carbon and improved strains of Nannochloropsis oceanica capable of higher rates of bicarbonate uptake and metabolism. The project succeeded in these goals. First, a bubble-free, membrane-based technology was developed for delivering CO 2 to cultivations, which increased the CUE from the 15-20% that is standard in the industry to more than 65%. In addition, N. oceanica was modified to express a bicarbonate transporter protein, BicA, which enabled the cells to grow more quickly. In addition, advances were made in the protein engineering of carbonic anhydrase (CA) for enhanced stability and catalytic performance, the computational fluid dynamics modeling of algal cultivation systems, and in the life-cycle assessment and technoeconomic analysis of algal production. Together, these outcomes contribute to advancing algal cultivation as an economically viable platform for production of fuels, materials, and other chemical products. The project results aid in addressing the dual challenges of reducing atmospheric CO 2 levels and achieving green energy solutions.

09 BIOMASS FUELS↗