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At least 163 records · Page 9

Results for the Fourth Quarter Calendar Year 2020 Tank 50 Salt Solution Sample

In this Technical Report, the chemical and radionuclide contaminant results from the Fourth Quarter Calendar Year 2020 (CY20) sample of Tank 50 salt solution are presented in tabulated form. The information from this characterization will be used by Savannah River Remediation (SRR) for the transfer of aqueous waste from Tank 50 to the Saltstone Production Facility (SPF), where the waste will be treated and disposed in the Saltstone Disposal Facility. This Technical Report compares results, where applicable, to SPF Waste Acceptance Criteria (WAC) Limits and Targets. The chemical and radionuclide contaminant results from the characterization of the Fourth Quarter CY20 sampling of Tank 50 were requested by SRR personnel via a Task Technical Request (TTR) and details of the testing are presented in the Savannah River National Laboratory (SRNL) Task Technical and Quality Assurance Plan (TTQAP). This Technical Report is part of Deliverable 2 relating to Task 1 from the SRR request. Data pertaining to the regulatory limits for Resource Conservation and Recovery Act (RCRA) metals per Task 2 from the SRR request, will be obtained semi-annually for the 1QCY21 and 3QCY21 Tank 50 samples. However, data pertaining to the regulatory limits for Resource Conservation and Recovery Act (RCRA) metals for this current 4QCY20 Tank 50 sample will be obtained and documented per the special analysis associated with the vault classification sample as described in the associated TTQAP.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Improved recovery of cell-cycle gene expression in Saccharomyces cerevisiae from regulatory interactions in multiple omics data

Gene expression is regulated by DNA-binding transcription factors (TFs). Together with their target genes, these factors and their interactions collectively form a gene regulatory network (GRN), which is responsible for producing patterns of transcription, including cyclical processes such as genome replication and cell division. However, identifying how this network regulates the timing of these patterns, including important interactions and regulatory motifs, remains a challenging task. Results We employed four in vivo and in vitro regulatory data sets to investigate the regulatory basis of expression timing and phase-specific patterns cell-cycle expression in Saccharomyces cerevisiae . Specifically, we considered interactions based on direct binding between TF and target gene, indirect effects of TF deletion on gene expression, and computational inference. We found that the source of regulatory information significantly impacts the accuracy and completeness of recovering known cell-cycle expressed genes. The best approach involved combining TF-target and TF-TF interactions features from multiple datasets in a single model. In addition, TFs important to multiple phases of cell-cycle expression also have the greatest impact on individual phases. Important TFs regulating a cell-cycle phase also tend to form modules in the GRN, including two sub-modules composed entirely of unannotated cell-cycle regulators ( STE12-TEC1 and RAP1-HAP1-MSN4 ). Conclusion Our findings illustrate the importance of integrating both multiple omics data and regulatory motifs in order to understand the significance regulatory interactions involved in timing gene expression. This integrated approached allowed us to recover both known cell-cycles interactions and the overall pattern of phase-specific expression across the cell-cycle better than any single data set. Likewise, by looking at regulatory motifs in the form of TF-TF interactions, we identified sets of TFs whose co-regulation of target genes was important for cell-cycle expression, even when regulation by individual TFs was not. Overall, this demonstrates the power of integrating multiple data sets and models of interaction in order to understand the regulatory basis of established biological processes and their associated gene regulatory networks.

59 BASIC BIOLOGICAL SCIENCES↗

Data for Hydrothermal Pretreatment for Valorization of Genetically Engineered Bioenergy Crop for Lipid and Cellulosic Sugar Recovery

Lipids accumulated in the vegetative tissues of cellulosic feedstocks can be a potential raw material for biodiesel and bioethanol production. In this work, bagasse of genetically engineered sorghum was subjected to liquid hot-water pretreatment at 170, 180, and 190 °C for different reaction time. Under the optimal pretreatment condition (170 °C, 20 min), the residue was enriched in glucan (57.39 ± 2.63 % w/w) and xylan (13.38 ± 0.49 % w/w). The total lipid content of the pretreated residue was 6.81% w/w, similar to that observed in untreated bagasse (6.30% w/w). Pretreatment improved the enzymatic digestibility of bagasse, allowing a recovery of 79% w/w and 86% w/w of glucose and xylose, respectively. The pretreatment and enzymatic saccharification resulted in a 2-fold increase in total lipid in enzymatic residue compared to the original bagasse. Thus, pretreatment and enzymatic hydrolysis enabled high sugar recovery while concentrating triglycerides and free fatty acids in the residue.

Conversion↗

Data for "Evaluating the industrial potential of emerging biomass pretreatment technologies in bioethanol production and lipid recovery from transgenic sugarcane"

The selection of pretreatment methods is critical to achieving high product yields during bioconversion of lignocellulosic biomass. Hydrothermal, soaking-in-aqueous ammonia, and ionic liquid pretreatment methods are viable candidates for minimizing sugar decomposition, permitting the effective hydrolysis of structural carbohydrates, and producing a fermentable substrate suitable for achieving industrial ethanol titers and yields. In this study, the effect of these three pretreatment methods on non-modified sugarcane cultivar CP88-1762 and two transgenic lipid-accumulating sugarcane lines, oilcane 1565 and oilcane 1566, were investigated and compared in terms of lipid recovery, sugar yield, and ethanol yields within the lignocellulosic biomass conversion pipeline. Fed-batch enzymatic hydrolysis at high solid loading yielded hydrolysates capable of supporting industrial bioethanol titers across all conditions. The highest sugar yields were obtained on ammonia-pretreated biomass hydrolysate (253.73 g L−1), followed by hydrothermally pretreated hydrolysate (213.10 g L−1) and ionic liquid-pretreated hydrolysate (154.20 g L−1). Commercially viable ethanol titers of 100.62 g L−1, 64.47 g L−1, and 52.95 g L−1 were achieved from ammonia, hydrothermal, and ionic liquid pretreated hydrolysate with the corresponding ethanol productivities of 2.08 g L−1 h−1, 0.53 g L−1 h−1, and 0.36 g L−1 h−1. The lower acetic acid concentration in ammonia-pretreated hydrolysate may have enhanced its fermentability relative to the hydrothermal pretreatment condition, as indicated by the differences in ethanol titer and productivity. Lower sugar yields and ethanol productivities under the ionic liquid conditions likely resulted from the inhibitory effect of cholinium lysinate. Oilcane 1565 and oilcane 1566 bagasse accumulated over 16- and 3 times higher lipids than the non-modified sugarcane CP88-1762. The total fatty acid content in the oilcane samples was reduced in ammonia and ionic liquid-pretreated bagasse relative to the hydrothermal pretreatment condition. While all pretreatment techniques tested are industrially viable, the observed differences in titer, productivity, and lipid content indicate that careful selection and validation of upstream processing methods can contribute to improved economic and environmental outcomes.

biomass analytics↗

A chemical-recovery-free ammonium sulfite-based alkali pretreatment of corn stover for low-cost sugar production via fertilizer use of waste liquor

The production of cellulosic sugars is a pivotal strategy for advancing biomass bioconversion. This study evaluated the pretreatment of corn stover using ammonium sulfite and potassium hydroxide to develop comprehensive data on sugar, lignin, chemicals, and overall mass recovery profiles in a batch reactor at 80 °C. The results indicated significant improvements in delignification, deacetylation, enzymatic digestibility, and overall sugar yield. Specifically, pretreating corn stover with a solution of 40 wt% potassium hydroxide and 15 wt% ammonium sulfite at 80 °C for 2 h achieved 78.9 % lignin removal and 82.1 % acetyl removal, resulting in a total sugar yield exceeding 87.5 % with an enzyme loading of 12.5 mg protein/g-glucan plus xylan. The pretreated spent liquor, containing ammonium, potassium, sulfur, biomass-derived organics, and inorganics, demonstrated substantial potential as a fertilizer. The techno-economic analysis projected a minimum sugar selling price of $0.285 per pound, supporting the ongoing development and implementation of chemical-recovery-free pretreatment technology.

09 BIOMASS FUELS↗

Degradation and Accelerated Recovery of Surface Passivation in n+, p+, and Intrinsic Poly-Si/SiOx Passivating Contacts for Silicon Solar Cells

We report on the degradation and recovery of surface passivation of fired poly-Si/SiOx passivating contacts with hydrogen containing Al2O3 during annealing in the dark and under illumination. Upon firing to a peak temperature of 670 degrees C, the iVoc for symmetric test structures with n+, p+, and intrinsic poly-Si/SiOx contacts decreases due to a loss of surface passivation. Upon further annealing over the temperature range of 200-350 degrees C in the dark, depending on the type of doping, the surface passivation either shows further degradation followed by recovery, or direct recovery to the initial iVoc. Annealing at higher temperatures and/or higher illumination intensities accelerates the kinetics for both degradation and recovery processes. We show that the degradation and recovery processes are thermally activated and proceed identically in subsequent firing and annealing steps showing their cyclic nature. We present a series reaction model to explain the kinetics of degradation and recovery processes for n+ and intrinsic poly-Si/SiOx contacts. By fitting the model's rate expressions to the data, the determined effective activation energy barriers for degradation and recovery for n+ poly-Si/SiOx contacts in the dark are 1.24 and 1.51 eV, which are lowered under 7.5 Suns illumination to 0.76 and 1.15 eV, respectively.

14 SOLAR ENERGY↗

Data for The Effects of Sequential Hydrothermal-Mechanical Refining Pretreatment on Cellulose Structure Changes and Sugar Recoveries

The recalcitrance of lignocellulosic biomass necessitates an efficient pretreatment protocol for operating a successful cellulosic biorefinery. It is critical to improve cellulose accessibility for hydrolysis and fermentation by altering the plant cell wall’s physical structure and chemical composition. Sequential hydrothermal-mechanical refining pretreatment (HMR) allows efficient recovery of cellulosic sugars without utilizing any hazardous chemicals. HMR has been successfully applied to Liberty switchgrass, a bioenergy cultivar released by the USDA, and now it is being applied to oilcane, a recently developed transgenic sugarcane variety engineered to accumulate lipids in its vegetative tissues. Sugar yields of oilcane bagasse (OCB) and switchgrass (SG) treated with HMR are 96.4% and 75.4%, respectively. This study sought to correlate cellulosic sugar yields with structural changes within the cell wall caused by HMR on two distinct bioenergy crops. Simon’s staining technique for the specific surface area analysis showed that HMR increased the specific surface area of pretreated biomass residues by 80-112%. In addition, ATR-FTIR was performed to determine the effects of HMR on physical structures based on the total crystallinity index (TCI) and hydrogen bonding intensity (HBI). Irrespective of biomass type, HMR decreased the initial crystalline cellulose contents of untreated biomass residues by 3.5% and reduced TCI and HBI by 7-13%. The study found that sugar yields were negatively correlated to reducing values of hydrogen bonding intensity, crystalline cellulose content, and total crystallinity index.

Biomass Analytics↗

Data for Natural Deep Eutectic Solvents (NADES) Assisted Deconstruction of Oilcane Bagasse for High Lipid and Sugar Recovery

In a novel approach, metabolically engineered sugarcane “Oilcane” has been investigated for fractionation of lipid and cellulose-rich pulp, using certain Natural deep eutectic solvents (NADES). The exploration of eco-friendly solvents are at the forefront of harnessing the biofuel potential of modern bioenergy crops. For this, six combinations of NADES were prepared using choline chloride (ChCl) as HBA and lactic acid (LA), oxalic acid (OA) and glycerol (Gly) as HBD and were further explored for pretreatment of oilcane bagasse in a molar ratio of 1:1 and 1:2. The impact of NADES ratio, biomass loading (10–50%), residence time (1–2 h), and temperature (90–140 °C) were evaluated for delignification, lipid content, sugar release after enzymatic hydrolysis. The finding demonstrated that under the optimal condition of ChCl: LA (1:2 molar ratio), 140 °C with 2 h retention time, the lipid content in the pre-treated substrate was increased to 2.5-fold (∼8% w/w) and > 80% glucose yield was achieved after 72 h of hydrolysis of pre-treated bagasse. High solid loading (∼50%) during pretreatment resulted in a similar glucose yield. Furthermore, recycling studies demonstrated that nearly 95 to 98% NADES could be recycled after each pretreatment for up to five consecutive cycles without any significant loss in chemical structure as confirmed by 1H NMR and FT IR. FT IR and XRD analyses of native and pre-treated biomass were performed to visualize the morphological changes during NADES pretreatment and their impact on sugar yield. The findings of the study may be used to establish NADES-based biorefinery for the valorization of lipids, and carbohydrates for fuels and chemicals production.

Conversion↗

Subsurface Energy Systems Mapping Inquiry Tool (MapIT)

The Subsurface Energy Systems Mapping Inquiry Tool (MapIT) is an online web mapping tool designed to help users discover available public-sourced data to facilitate data exploration for subsurface energy exploration and characterization efforts for resource identification (e.g. critical minerals, hydrocarbons, geothermal) as well as injection of geologic sequestration of carbon dioxide (e.g. enhanced oil recovery, saline storage, etc.). Modules within the tool curate data related to geology, faults, fractures, injection and confining zones, hydrologic information, groundwater, groundwater wells, geomechanical and petrophysical data, and geochemical data. User documentation on how to use the tool is also provided. Data have been collected from authoritative national, state, and local sources and made available in this tool. The data is also available as a data catalog and Esri Geodatabase at: https://edx.netl.doe.gov/dataset/mapit-database Disclaimer: There is no guarantee of completeness or appropriateness for individual user’s requirements. Use of this tool is solely at the discretion of the user. See full Federal Disclaimer for further information (https://netl.doe.gov/home/disclaimer). This project was funded by the United States Department of Energy, National Energy Technology Laboratory, in part, through a site support contract. Neither the United States Government nor any agency thereof, nor any of their employees, nor the support contractor, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. https://www.netl.doe.gov/home/disclaimer

Carbon Sequestration↗

Rapid Evaluation and Response to Impacts on Critical End-Use Loads Following Natural Hazard-Driven Power Outages: A Modular and Responsive Geospatial Technology

The disparate nature of data for electric power utilities complicates the emergency recovery and response process. The reduced efficiency of response to natural hazards and disasters can extend the time that electrical service is not available for critical end-use loads, and in extreme events, leave the public without power for extended periods. This article presents a methodology for the development of a semantic data model for power systems and the integration of electrical grid topology, population, and electric distribution line reliability indices into a unified, cloud-based, serverless framework that supports power system operations in response to extreme events. An iterative and pragmatic approach to working with large and disparate datasets of different formats and types resulted in improved application runtime and efficiency, which is important to consider in real time decision-making processes during hurricanes and similar catastrophic events. This technology was developed initially for Puerto Rico, following extreme hurricane and earthquake events in 2017 and 2020, but is applicable to utilities around the world. Given the highly abstract and modular design approach, this technology is equally applicable to any geographic region and similar natural hazard events. In addition to a review of the requirements, development, and deployment of this framework, technical aspects related to application performance and response time are highlighted.

24 POWER TRANSMISSION AND DISTRIBUTION↗

AlphaFold -assisted structure determination of a bacterial protein of unknown function using X-ray and electron crystallography

Macromolecular crystallography generally requires the recovery of missing phase information from diffraction data to reconstruct an electron-density map of the crystallized molecule. Most recent structures have been solved using molecular replacement as a phasing method, requiring an a priori structure that is closely related to the target protein to serve as a search model; when no such search model exists, molecular replacement is not possible. New advances in computational machine-learning methods, however, have resulted in major advances in protein structure predictions from sequence information. Methods that generate predicted structural models of sufficient accuracy provide a powerful approach to molecular replacement. Taking advantage of these advances, AlphaFold predictions were applied to enable structure determination of a bacterial protein of unknown function (UniProtKB Q63NT7, NCBI locus BPSS0212) based on diffraction data that had evaded phasing attempts using MIR and anomalous scattering methods. Using both X-ray and micro-electron (microED) diffraction data, it was possible to solve the structure of the main fragment of the protein using a predicted model of that domain as a starting point. The use of predicted structural models importantly expands the promise of electron diffraction, where structure determination relies critically on molecular replacement.

molecular replacement↗

Physics-Informed Evolutionary Strategy Based Control for Mitigating Delayed Voltage Recovery

Here, in this work we propose a novel data-driven, real-time power system voltage stability control method based on the physics-informed guided meta evolutionary strategy (ES). The main objective is to quickly provide an adaptive control strategy to secure system voltage stability. The problem is challenging due to the high-dimensional feature of the power system model and the fast-changing and uncertain nature of power system operation scenarios. To this end, a model-free and derivative-free guided ES method is applied. The method is further combined with a meta-learning strategy to make the learnt control policy automatically adapted to unseen operation conditions and fault scenarios, which is highly desired for real-time emergency control. Last but not least, physical knowledge is embedded in the above method through a trainable action mask technique to rule out unnecessary load shedding actions for better learning and control performance. Case studies on the IEEE 300-bus system and comparisons with other state-of-the-art benchmark methods verify the superiority of the proposed physics-informed guided meta ES method in realizing fast and adaptive power system voltage stability control.

42 ENGINEERING↗

Acute stress reduces population-level metabolic and proteomic variation

Abstract Background Variation in omics data due to intrinsic biological stochasticity is often viewed as a challenging and undesirable feature of complex systems analyses. In fact, numerous statistical methods are utilized to minimize the variation among biological replicates. Results We demonstrate that the common statistics relative standard deviation (RSD) and coefficient of variation (CV), which are often used for quality control or part of a larger pipeline in omics analyses, can also be used as a metric of a physiological stress response. Using an approach we term Replicate Variation Analysis (RVA), we demonstrate that acute physiological stress leads to feature-wide canalization of CV profiles of metabolomes and proteomes across biological replicates. Canalization is the repression of variation between replicates, which increases phenotypic similarity. Multiple in-house mass spectrometry omics datasets in addition to publicly available data were analyzed to assess changes in CV profiles in plants, animals, and microorganisms. In addition, proteomics data sets were evaluated utilizing RVA to identify functionality of reduced CV proteins. Conclusions RVA provides a foundation for understanding omics level shifts that occur in response to cellular stress. This approach to data analysis helps characterize stress response and recovery, and could be deployed to detect populations under stress, monitor health status, and conduct environmental monitoring.

59 BASIC BIOLOGICAL SCIENCES↗

Utah FORGE: Slide-Hold-Slide Experiments on Westerly Granite at Temperatures up to 250 Degrees C

Laboratory slide-hold-slide tests were conducted in a conventional triaxial deformation configuration on 1-inch diameter cylindrical cores of Westerly granite bisected by a sawcut oriented at 30 degrees from vertical. Tests were conducted at a constant confining pressure of 30 MPa with a 10 MPa pore fluid pressure. The pore fluid was deionized water. Experiments were conducted at temperatures of 22, 100, 200, and 250 C. This data was collected to examine fault strength recovery in hydrothermal conditions.

15 GEOTHERMAL ENERGY↗

Carbon Utilization and Storage Partnership of the Western United States

This technical report documents research conducted under DOE Award No. DE-FE0031837 focused on evaluating the feasibility of carbon capture, utilization, and storage (CCUS) systems in the central and western United States. The project integrated geologic characterization, reservoir simulation, infrastructure modeling, and economic analysis to assess CO₂ storage potential near industrial sources and develop strategies for transport and sequestration. The work included subsurface modeling, risk assessment, monitoring and verification (MRV) planning, and evaluation of regulatory pathways such as EPA Underground Injection Control (UIC) Class VI permitting and IRS 45Q tax credit eligibility. Results demonstrate the viability of multiple storage approaches, including saline formations, enhanced coalbed methane recovery, and basalt mineralization, supported by data-driven workflows and regional analyses. The project also produced permitting templates, technology transfer activities, and stakeholder engagement efforts to support deployment readiness. These findings contribute to the development of scalable, economically viable CCUS systems and provide a repeatable framework for future carbon management projects.

20 FOSSIL-FUELED POWER PLANTS↗

Dynamical Packing in the Habitable Zone: The Case of Beta CVn

Uncovering the occurrence rate of terrestrial planets within the habitable zone (HZ) of their host stars has been a particular focus of exoplanetary science in recent years. The statistics of these occurrence rates have largely been derived from transiting planet discoveries, and have uncovered numerous HZ planets in compact systems around M-dwarf host stars. Here we explore the width of the HZ as a function of spectral type, and the dynamical constraints on the number of stable orbits within the HZ for a given star. We show that, although the Hill radius for a given planetary mass increases with larger semimajor axis, the width of the HZ for earlier-type stars allows for more terrestrial planets in the HZ than late-type stars. In general, dynamical constraints allow ∼6 HZ Earth-mass planets for stellar masses ≳0.7M {sub ⊙}, depending on the presence of farther out giant planets. As an example, we consider the case of Beta CVn, a nearby bright solar-type star. We present 20 yr of radial velocities (RV) from the Keck/High Resolution Echelle Spectrometer (HIRES) and Automated Planet Finder (APF) instruments and conduct an injection-recovery analysis of planetary signatures in the data. Our analysis of these RV data rule out planets more massive than Saturn within 10 au of the star. These system properties are used to calculate the potential dynamical packing of terrestrial planets in the HZ and show that such nearby stellar targets could be particularly lucrative for HZ planet detection by direct imaging exoplanet missions.

79 ASTRONOMY AND ASTROPHYSICS↗

Chemically Enabled CO 2 -Enhanced Oil Recovery in Multi-Porosity, Hydrothermally Altered Carbonates in the Southern Michigan Basin - Task 2 Topical Report

This attachment A is a detailed Topical Report for Task 2 (Advanced Field Characterization and Machine Learning Based Data Integration) under the project "Chemically Enabled CO 2 -Enhanced Oil Recovery in Multi-Porosity, Hydrothermally Altered Carbonates in the Southern Michigan Basin." The overall project activity and finding, including the field pilot testing of CO 2 injection are summarized in the companion Final Technical Report The Advanced Field Characterization and Machine Learning Based Data Integration task (Task 2) involved a systematic geologic characterization of the Trenton-Black River (TBR) play in the SMB which included the development of comprehensive datasets, advanced data analytics, risk assessment, and piggyback field characterization. These activities aimed to address the complex carbonate systems by evaluating the extent of fractures, dolomitization, facies, and reservoir properties with the primary objective of informing the static and dynamic modeling, field injection test, and providing input into the development strategy plan. The task was divided into four subtasks: • Subtask 2.1 – Data compilation, review, and analysis • Subtask 2.2 – Risk Assessment • Subtask 2.3 – Advanced Field Characterization • Subtask 2.4 – Integrated Physics-Based Machine Learning and Advanced Data Analytics

02 PETROLEUM↗

VirION2: a short- and long-read sequencing and informatics workflow to study the genomic diversity of viruses in nature

Microbes play fundamental roles in shaping natural ecosystem properties and functions, but do so under constraints imposed by their viral predators. However, studying viruses in nature can be challenging due to low biomass and the lack of universal gene markers. Though metagenomic short-read sequencing has greatly improved our virus ecology toolkit—and revealed many critical ecosystem roles for viruses—microdiverse populations and fine-scale genomic traits are missed. Some of these microdiverse populations are abundant and the missed regions may be of interest for identifying selection pressures that underpin evolutionary constraints associated with hosts and environments. Though long-read sequencing promises complete virus genomes on single reads, it currently suffers from high DNA requirements and sequencing errors that limit accurate gene prediction. Here we introduce VirION2, an integrated short- and long-read metagenomic wet-lab and informatics pipeline that updates our previous method (VirION) to further enhance the utility of long-read viral metagenomics. Using a viral mock community, we first optimized laboratory protocols (polymerase choice, DNA shearing size, PCR cycling) to enable 76% longer reads (now median length of 6,965 bp) from 100-fold less input DNA (now 1 nanogram). Using a virome from a natural seawater sample, we compared viromes generated with VirION2 against other library preparation options (unamplified, original VirION, and short-read), and optimized downstream informatics for improved long-read error correction and assembly. VirION2 assemblies combined with short-read based data (‘enhanced’ viromes), provided significant improvements over VirION libraries in the recovery of longer and more complete viral genomes, and our optimized error-correction strategy using long- and short-read data achieved 99.97% accuracy. In the seawater virome, VirION2 assemblies captured 5,161 viral populations (including all of the virus populations observed in the other assemblies), 30% of which were uniquely assembled through inclusion of long-reads, and 22% of the top 10% most abundant virus populations derived from assembly of long-reads. Viral populations unique to VirION2 assemblies had significantly higher microdiversity means, which may explain why short-read virome approaches failed to capture them. These findings suggest the VirION2 sample prep and workflow can help researchers better investigate the virosphere, even from challenging low-biomass samples. Our new protocols are available to the research community on protocols.io as a ‘living document’ to facilitate dissemination of updates to keep pace with the rapid evolution of long-read sequencing technology.

Long-reads↗