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Efroymson, R. A., M. H. Langholtz, K. L. Kline, D. de la Torre Ugarte, C. Hellwinckel, T. R. Hawkins, E. S. Parish, et al. 2024. “Chapter 6: Sustainability and Good Practices.” In 2023 Billion‐Ton Report. M. H. Langholtz (Lead). Oak Ridge, TN: Oak Ridge National Laboratory. doi: 10.23720/BT2023/2316172.
Davis, R., A. Coleman, A. Badgett, et al. 2024. “Chapter 7: Emerging Resources: Microalgae, Macroalgae, and Point-Source Carbon Dioxide Waste Streams.” In 2023 Billion‐Ton Report. M. H. Langholtz (Lead). Oak Ridge, TN: Oak Ridge National Laboratory. doi:10.23720/BT2023/2316174.
Microalgae is a unique biomass resource that does not need to compete for land and water with other biomass feedstocks because it can be cultivated on low-quality unencumbered land using noncompetitive water types including saline and wastewater. It is included as a complementary resource alongside other biomass feedstocks reported in this study, albeit at higher biomass production costs reflective of more capital-intensive farming operations than typical for terrestrial biomass. Higher biomass costs can be offset by the potential to produce value-added coproducts unique to compositional constituents of microalgae. Relative to BT16, this chapter reflects the latest analysis from the 2022 Algae Harmonization Update, which uses the latest parameterized and high-performing saline algal strain, second-generation carbon capture of point-source waste CO2 and high-pressure pipeline transport resolved to specific point-source types, saline water sourcing up to 40,000 mg/L total dissolved solids for source and makeup water salinity, blowdown water treatment and recycle, and brine disposal handling. National-scale algal biomass availability potential was calculated at 152 million tons/yr ash-free dry weight (AFDW) (191 million tons/yr dry weight) at an average biomass productivity of 26.2 g/m2 -day AFDW (about 50 tons/acre/yr dry weight).1 The algal biomass was cultivated on 3.9 million acres of multi-criteria screened and potentially available land for CONUS and fixed 268 million tons of waste CO2 based on biomass uptake. The algae biomass can be produced at an average MBSP of $674/ton AFDW ($536/ton dry weight) in 2020 dollars,2 corresponding to a total energy potential of 3.3 quads/yr at an average MBSP of $31.2/MMBtu (higher-heating-value [HHV] basis).
Chapter 7.2 — Coleman, A., K. Davis, J. DeAngelo, T. Saltiel, B. Saenz, L. Miller, K. Champion, E. Harrison, and A. Otwell. 2024. “Chapter 7.2: Macroalgae.” In 2023 Billion‐Ton Report. M. H. Langholtz (Lead). Oak Ridge, TN: Oak Ridge National Laboratory. doi: 10.23720/BT2023/2316176.
Chapter 7.3 — Badgett, A., G. Cooney, J. Hoffmann, and A. Milbrandt. 2024. “Chapter 7.3: CO2 Emissions from Stationary Sources.” In 2023 Billion‐Ton Report. M. H. Langholtz (Lead). Oak Ridge, TN: Oak Ridge National Laboratory. doi: 10.23720/BT2023/2316177.
U.S. Department of Energy. 2024. “Chapter 8: Looking Forward and Next Steps.” In 2023 Billion‐Ton Report. M. H. Langholtz (Lead). Oak Ridge, TN: Oak Ridge National Laboratory. doi: 10.23720/BT2023/2316179.
New rideshare and shared mobility services have transformed urban mobility in recent years. Such services have the potential to improve efficiency and reduce costs by allowing users to share rides in high-capacity vehicles and vans. Most transit agencies already operate various ridepooling services, including microtransit and paratransit. However, the objectives and constraints for implementing these services vary greatly between agencies and can be challenging. First, off-the-shelf ridepooling formulations must be adapted for real-world conditions and constraints. Second, the lack of modular and reusable software makes it hard to implement and evaluate new ridepooling algorithms and approaches in real-world settings. We demonstrate a modular on-demand public transportation scheduling software for microtransit and paratransit services. The software is aimed at transit agencies looking to incorporate state-of-the-art rideshare and ridepooling algorithms in their everyday operations. We provide management software for dispatchers and mobile applications for drivers and users and conclude with results from the demonstration in Chattanooga, TN.
This dataset includes processed and raw data from the Vanderbilt Alumni Hall Building (VAH) located on the University of Vanderbilt Campus in Nashville, TN. VAH is a mixed use commercial building (LEED Gold Certified) that consists of classrooms, meeting rooms, office rooms, conference rooms, an exercise room, and others. This dataset spans one year of time-series data from 2019 and includes measurements corresponding to whole building electrical power, thermal power, zone level thermal power, set-point, indoor temperature, humidity, water and air side supply and return temperatures and flow rates as CSV files. In addition to the measurements, a metadata .json file, and a .ttl file to visualize the data as per BRICK schema are also included.
BLUP and mean yields of selected top 25 high yielding half-sib families. The yield BLUP were estimated using mixed linear models. The family column indicates the families with progeny column showing the corresponding progenies to selected families. ‘Wat’ here has been used to denote Watkinsville, ‘Tif’ for Tifton and ‘TN’ for Tennessee.
This data set provides the respiration and soil microbial biomass data from a series of short and long-term laboratory incubation experiments with 13C labeled substrates to examine how plant communities (forest vs. grassland), edaphic properties, and microbial communities influence C cycling and the long-term fate of C in soil systems. Paired forest and grassland soils from four locations were incubated with 13C labeled glucose in a short-term (144 hours) study while 13C labeled cellulose was added to soils used in the long-term (729 days) study. Soil respiration, microbial biomass, and soil 13C values were monitored throughout the study. Soils were collected from paired forest and grassland locations in the following states in the United States of America: Tennessee (TN), Ohio (OH), Iowa (IA), and Missouri (MO). This dataset contains one data file in comma-separate (*.csv) format.
Traditional aquaculture ponds are one of the most vulnerable ecosystems; thus, ecological aquaculture is increasingly valued for its beneficial ecological properties and ecosystem services. However, little is known about ecological aquaculture of largemouth bass with submerged vegetation. Here, we designed three ecological ponds of cultured largemouth bass with submerged macrophytes (the EM group) and three ponds with traditional aquaculture (the M group) to reveal the response of water quality, and phytoplankton and bacterial communities, to submerged macrophyte bioremediation during a 90-day culture period. We observed that Cyanobacterial outbreak occurred in the M group ponds from day 7 to the end of the experiment; however, there were no Cyanobacterial blooms in the EM group ponds throughout the culture period. Compared with the M group ponds, the EM group ponds, which had submerged hydrophytes, had significantly decreased concentrations of TP, TN, and COD Mn , but significantly increased DO concentrations throughout the experimental period. Moreover, ecological aquaculture with submerged macrophytes showed strong effects on the phytoplankton and bacterial community compositions. In particular, the M group ponds had higher phytoplankton density and mainly included Cyanobacteria, whereas the EM group had lower phytoplankton density and mainly included Chlorophyta. Moreover, higher alpha diversity, as determined by Ace and Simpson index values, was detected for bacterial communities in the EM group ponds. Furthermore, PCoA clearly grouped the bacterial communities according to the two culture modes throughout the culture period. These results indicate that ecological aquaculture with submerged macrophytes can improve water quality, control Cyanobacterial blooms, and affect the diversity and composition of bacterial communities. These valuable effects seem to be beneficial and consistent to maintaining aquaculture ecosystem stability.
Escalating wildfire frequency and severity, exacerbated by shifting climate patterns, pose significant ecological and economic challenges. Prescribed burns, a common forest management tool, aim to mitigate wildfire risks and protect biodiversity. Nevertheless, understanding the impact of prescribed burns on soil and microbial communities in temperate mixed forests, considering temporal dynamics and slash fuel types, remains crucial. Our study, conducted at the University of Tennessee Forest Resources AgResearch and Education Center in Oak Ridge, TN, employed controlled burns across various treatments, and the findings indicate that low-intensity prescribed burns have none or minimal short-term effects on soil parameters but may alter soil nutrient concentrations, as evidenced by significant changes in porewater acetate, formate, and nitrate concentrations. These burns also induce shifts in microbial community structure and diversity, with Proteobacteria and Acidobacteria increasing significantly post-fire, possibly aiding soil recovery. In contrast, Verrucomicrobia showed a notable decrease over time, and other specific microbial taxa correlated with soil pH, porewater nitrate, ammonium , and phosphate concentrations. Our research contributes to understanding the intricate relationships between prescribed fire, soil dynamics, and microbial responses in temperate mixed forests in the Southern Appalachian Region, which is valuable for informed land management practices in the face of evolving environmental challenges.
The main driven force of the electronic nematic phase in iron-based superconductors is still under debate. Here, we report a comprehensive study on the nematic fluctuations in a non-superconducting iron pnictide system BaFe 1.9-x Ni 0.1 Cr x As 2 by electronic transport, angle-resolved photoemission spectroscopy (ARPES), and inelastic neutron scattering (INS) measurements. Previous neutron diffraction and transport measurements suggested that the collinear antiferromagnetism persists to x = 0.8, with similar Néel temperature TN and structural transition temperature Ts around 32 K, but the charge carriers change from electron type to hole type around x = 0.5. In this study, we have found that the in-plane resistivity anisotropy also highly depends on the Cr dopings and the type of charge carriers. While ARPES measurements suggest possibly weak orbital anisotropy onset near Ts for both x = 0.05 and x = 0.5 compounds, INS experiments reveal clearly different onset temperatures of low-energy spin excitation anisotropy, which is likely related to the energy scale of spin nematicity. These results suggest that the interplay between the local spins on Fe atoms and the itinerant electrons on Fermi surfaces is crucial to the nematic fluctuations of iron pnictides, where the orbital degree of freedom may behave differently from the spin degree of freedom, and the transport properties are intimately related to the spin dynamics.
Cross-Laminated Timber (CLT) panels have many structural benefits but do not have much thermal resistance. We have developed a solution to insulate CLT structures that uses high-performance insulation panels that provide R-values up to R40/inch. The CLT panels are made of layers of wood laminates (three, five, seven or more). The solution replaces some of the wood laminates in the CLT production with the insulation panels in a staggered fashion so that the wood laminates maintain contact throughout the panel, ensuring the CLT panel’s structural integrity. The insulated CLT panels have factory-installed water-resistive barriers reducing the installation time by eliminating installing insulation and water-resistive barriers on site. Per simulations, the CLT/insulation panel achieved code-required insulation levels with commonly available insulation materials. The significance of the thermal mass of CLT/insulation hybrid building envelopes was quantified by comparing the whole building energy performance and peak demand of traditional low mass and CLT wall assemblies resulting in up to 7% reduction in peak demand for cooling in Knoxville, TN, in a multifamily building. Buildings contribute over 40 percent of carbon emissions. The proposed CLT/insulation hybrid building envelope addresses both operational and embodied carbon by having high thermal resistances due to the embedded insulation sections and eliminating the use of high embodied carbon materials such as steel and concrete. The carbon benefit is estimated.
We report the magnetic properties and magnetic structure determination for a linear-chain antiferromagnet, MnBi 2 Se 4 . The crystal structure of this material contains chains of edge-sharing MnSe 6 octahedra separated by Bi atoms. The magnetic behavior is dominated by intrachain antiferromagnetic (AFM) interactions, as demonstrated by the negative Weiss constant of –74 K obtained by the Curie–Weiss fit of the paramagnetic susceptibility measured along the easy-axis magnetization direction. The relative shift of adjacent chains by one-half of the chain period causes spin frustration due to interchain AFM coupling, which leads to AFM ordering at TN = 15 K. Neutron diffraction studies reveal that the AFM ordered state exhibits an incommensurate helimagnetic structure with the propagation vector k = (0, 0.356, 0). The Mn moments are arranged perpendicular to the chain propagation direction (the crystallographic b axis), and the turn angle around the helix is 128°. The magnetic properties of MnBi2Se4 are discussed in comparison to other linear-chain antiferromagnets based on ternary mixed-metal halides and chalcogenides.
The Oak Ridge National Laboratory High Flux Isotope Reactor (HFIR) is an 85 MWt flux trap-type research reactor that supports key research missions, including isotope production, materials irradiation, and neutron scattering. The core consists of an inner and an outer fuel element containing 171 and 369 involute-shaped plates, respectively. The thin fuel plates consist of a U 3 O 8 -Al dispersion fuel (highly enriched), an aluminum-based filler, and aluminum cladding. The fuel meat thickness is varied across the width of the involute plate to reduce thermal flux peaks at the radial edges of the fuel elements. Some deviation from the designed fuel meat shaping is allowed during manufacturing. A homogeneity scan of each fuel plate checks for potential anomalies in the fuel distribution by scanning the surface of the plate and comparing the attenuation of the beam to calibration standards. While typical HFIR simulations use homogenized fuel regions, explicit models of the plates were developed under the Low-Enriched Uranium Conversion Program. These explicit models typically include one inner and one outer fuel plate with nominal fuel distributions, and then the plates are duplicated to fill the space of the corresponding fuel element. Therefore, data extracted from these simulations are limited to azimuthally averaged quantities. To determine the reactivity and physics impacts of an as-built outer fuel element and generate azimuthally dependent data in the element, 369 unique fuel plate models were generated and positioned. This model generates the three-dimensional (i.e., radial–axial–azimuthal) plate power profile, where the azimuthal profile is impacted by features within the adjacent control element region and beryllium reflector. For an as-built model of the outer fuel element, plate-specific homogeneity data, 235 U loading, enrichment, and channel thickness measurements were translated into the model, yielding a much more varied azimuthal power profile encompassed by uncertainty factors in analyses. These models were run with the ORNL-TN and Shift Monte Carlo tools, and they contained upwards of 500,000 cells and 100,000 unique tallies.
Optimal constructions of classical LDPC codes can be obtained by choosing the Tanner graph uniformly at random among biregular graphs. We introduce a class of codes that we call ``diffusion codes'', defined by placing each edge connecting bits and checks on some graph, and acting on that graph with a random SWAP network. By tuning the depth of the SWAP network, we can tune a tradeoff between the amount of randomness -- and hence the optimality of code parameters -- and locality with respect to the underlying graph. For diffusion codes defined on the cycle graph, if the SWAP network has depth $\sim Tn$ with $T> n^{2β}$ for arbitrary $β>0$, then we prove that almost surely the Tanner graph is a lossless ``smaller set'' vertex expander for small sets up size $δ\sim \sqrt T \sim n^β$, with bounded bit and check degree. At the same time, the geometric size of the largest stabilizer is bounded by $\sqrt T$ in graph distance. We argue, based on physical intuition, that this result should hold more generally on arbitrary graphs. By taking hypergraph products of these classical codes we obtain quantum LDPC codes defined on the torus with smaller-set boundary and co-boundary expansion and the same expansion/locality tradeoffs as for the classical codes. These codes are self-correcting and admit single-shot decoding, while having the geometric size of the stabilizer growing as an arbitrarily small power law. Our proof technique establishes mixing of a random SWAP network on small subsystems at times scaling with only the subsystem size, which may be of independent interest.
In this case study, we will describe the design and assembly of a cyber security test range we have built at Oak Ridge National Laboratory in Oak Ridge, TN, USA. The range is designed to provide a flexible environment to evaluate cyber security tools—particularly those involving AI/ML—in a way that provides realistic environments and where we can control the experiments to determine the strengths and weaknesses of the tools. We have designed in the ability to repeat the evaluations, so additional tools can be evaluated and compared at a later time. The system is one that can be scaled up or down for experiment sizes. At the time of the conference we will have completed two full-scale, national, government challenges on this range. These challenges are evaluating the performance and operating costs for AI/ML-based cyber security tools for application into large, government-sized environments. These evaluations will be described, in order to provide motivation and context for various design decisions and adaptations we have made. The first challenge measured end-point security tools against 100K malware samples chosen across a range of types. The second is network detection of attempted penetration and exploitations with varying levels of covertness in a high-volume, business network. The scale of each of these challenges is requiring us to create automation systems to repeat the experiments identically for each tool. Preventing there being easy signs of malicious activity for the AI/ML tools to focus on has been a particularly interesting and challenging aspect of designing and executing these challenge events. After the events, the range continues to be used for other research such as adversarial machine learning where the repeatability, scale, and automation required for the national challenge events become essential elements for research.