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DOE OSTI2024

Suppressing metal corrosion through identification of optimal crystallographic plane for Zn batteries

Direct use of metals as battery anodes could significantly boost the energy density, but suffers from limited cycling. To make the batteries more sustainable, one strategy is mitigating the propensity for metals to form random morphology during plating through orientation regulation, e.g., hexagonal Zn platelets locked horizontally by epitaxial electrodeposition or vertically aligned through Zn/electrolyte interface modulation. Current strategies center around obtaining (002) faceted deposition due to its minimum surface energy. Here, benefiting from the capability of preparing a library of faceted monocrystalline Zn anodes and controlling the orientation of Zn platelet deposits, we challenge this conventional belief. We show that while monocrystalline (002) faceted Zn electrode with horizontal epitaxy indeed promises the highest critical current density, the (100) faceted electrode with vertically aligned deposits is the most important one in suppressing Zn metal corrosion and promising the best reversibility. Such uniqueness results from the lowest electrochemical surface area of (100) faceted electrode, which intrinsically builds upon the surface atom diffusion barrier and the orientation of the pallets. These new findings based on monocrystalline anodes advance the fundamental understanding of electrodeposition process for sustainable metal batteries and provide a paradigm to explore the processing–structure–property relationships of metal electrodes.

25 ENERGY STORAGE↗

DOE OSTI2021

Sustainability Trait Modeling of Field-Grown Switchgrass ( Panicum virgatum ) Using UAV-Based Imagery

Unmanned aerial vehicles (UAVs) provide an intermediate scale of spatial and spectral data collection that yields increased accuracy and consistency in data collection for morphological and physiological traits than satellites and expanded flexibility and high-throughput compared to ground-based data collection. In this study, we used UAV-based remote sensing for automated phenotyping of field-grown switchgrass (Panicum virgatum), a leading bioenergy feedstock. Using vegetation indices calculated from a UAV-based multispectral camera, statistical models were developed for rust disease caused by Puccinia novopanici, leaf chlorophyll, nitrogen, and lignin contents. For the first time, UAV remote sensing technology was used to explore the potentials for multiple traits associated with sustainable production of switchgrass, and one statistical model was developed for each individual trait based on the statistical correlation between vegetation indices and the corresponding trait. Also, for the first time, lignin content was estimated in switchgrass shoots via UAV-based multispectral image analysis and statistical analysis. The UAV-based models were verified by ground-truthing via correlation analysis between the traits measured manually on the ground-based with UAV-based data. The normalized difference red edge (NDRE) vegetation index outperformed the normalized difference vegetation index (NDVI) for rust disease and nitrogen content, while NDVI performed better than NDRE for chlorophyll and lignin content. Overall, linear models were sufficient for rust disease and chlorophyll analysis, but for nitrogen and lignin contents, nonlinear models achieved better results. As the first comprehensive study to model switchgrass sustainability traits from UAV-based remote sensing, these results suggest that this methodology can be utilized for switchgrass high-throughput phenotyping in the field.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Sustainability Trait Modeling of Field-Grown Switchgrass (Panicum virgatum) Using UAV-Based Imagery

CBI↗

DOE OSTI2023

Cascaded Sapphire Fiber Bragg Gratings Inscribed by Femtosecond Laser for Molten Steel Studies

This research reports a distributed fiber optic high-temperature sensing system tailored for applications in the steel industry and various other sectors. Recent advancements in optical sensor technology have led to the exploration of sapphire crystal fibers as a solution for sensing in harsh environments. Utilizing a femtosecond (fs) laser, cascaded fiber Bragg gratings (FBGs) were meticulously fabricated within a multimode sapphire optical fiber. These FBGs endowed the system with distributed sensing capabilities and underwent rigorous testing under extreme temperatures, reaching up to 1800 °C. Here, the study delves into the investigation of the FBG reflection spectrum, facilitated by the development of a sophisticated multimode demodulation system, which contributed to the attainment of precise temperature measurements with a performance accuracy of 99.9%. Demonstrating exceptional thermal stability, the sapphire FBGs endured temperatures of 1600 °C for a sustained duration of 22 h. Furthermore, this article explores the application of distributed temperature sensing employing multiple sapphire FBGs, showcasing their utility in temperature measurements related to molten steel studies.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

DoE as a “Digital Innovation” Sponsor of the WCRP OSC2023 (Final Report)

The WCRP Open Science Conference (https://wcrp-osc2023.org/) was a once-in-a-decade opportunity to jointly explore the transformative actions urgently needed to ensure a sustainable future. Held in Kigali, Rwanda on October 23 -27, 2023, it showcased advances in climate science, helped identify gaps and opportunities, and provided a forum for communities to jointly develop future activities. Scientists, practitioners, politicians, policy makers, intergovernmental agencies and NGOs showcased their work, learned from each other, and explored new ways to work together.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Chemical design of self-propelled Janus droplets

Solubilizing, self-propelling droplets have emerged as a rich chemical platform for the exploration of active matter, but isotropic droplets rely on spontaneous symmetry breaking to sustain motion. The introduction of permanent asymmetry, e.g., in the form of a biphasic Janus droplet, has not been explored as a comprehensive design strategy for active droplets, despite the widespread use of Janus structures in motile solid particles. Here, we uncover the chemomechanical framework underlying the self-propulsion of biphasic Janus oil droplets solubilizing in aqueous surfactant. We elucidate how droplet propulsion is influenced by the degree of oil mixing, droplet shape, and oil solubilization rates for a range of oil combinations. In addition, spatiotemporal control over droplet swimming speed and orientation is demonstrated through the application of thermal gradients applied via joule heating and laser illumination. Finally, we also explore the interactions between collections of Janus droplets, including the spontaneous formation of spinning multi-droplet clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Data for Rewiring Yeast Metabolism for Producing 2,3-Butanediol and Two Downstream Applications: Techno-Economic Analysis and Life Cycle Assessment of Methyl Ethyl Ketone (MEK) and Agricultural Biostimulant Production

Rising concerns for sustainability and global climate change have driven the development of sustainable production pathways for biofuels and chemicals from lignocellulosic biomass via integrated biological and chemical processes. We constructed an engineered Saccharomyces cerevisiae capable of producing 2,3-butanediol (2,3-BDO) from glucose without accumulating ethanol and glycerol, which hinder downstream processing of 2,3-BDO, through extensive metabolic reprogramming. Specifically, we introduced heterologous 2,3-BDO biosynthetic enzymes and deleted the major isozymes of ethanol and glycerol biosynthetic enzymes. In addition, we introduced an NAD+ regenerating Pyruvate-Malate (PM) cycle and enhanced the NAD+ regenerating capability of the PM cycle to resolve the redox imbalance from the deletion of ethanol and glycerol production pathways. The resulting engineered yeast produced 109.9 g/L of 2,3-BDO with a productivity of 1.0 g/L/h and a yield of 0.36 g/g glucose in a fed-batch fermentation. We also conducted techno-economic analysis (TEA) and life cycle assessment (LCA) of the production of methyl ethyl ketone (MEK) through catalytic dehydration of 2,3-BDO. A TEA based on the experimental results indicated that the minimum product selling price (MPSP) was estimated to be $1.90/kg. Regarding cradle-to-grave LCA, 100-year global warming potential (GWP100) and fossil energy consumption (FEC) were found to be 0.37 kg CO2 eq/kg and 3.1 MJ/kg, respectively. These results demonstrated the feasibility of cost-competitive and sustainable bio-based MEK production via yeast fermentation. In addition, we explored the possibility of using the fermentation broth containing 2,3-BDO as a biostimulant inducing drought tolerance in plants. As a result, the yeast 2,3-BDO fermentation broth can induce drought tolerance in Arabidopsis thaliana without a complicated purification process.

Economics↗

DOE OSTI2024

Implications of pond reliability on the techno-economic and life cycle environmental impacts of algal biofuels

Despite extensive research on algal bioproducts, there is limited understanding of how pond contamination affects their economics and environmental impacts. This work compared the costs and environmental impacts of algal biofuels across different pond failure scenarios. Pond failure was simulated by a reliability model based on pond mean-time-to-failure (MTTF). The reliability model was integrated with a process model to analyze the impacts of pond failure on the operations of algal farms and biorefineries. Process model outputs were used for techno-economic analysis and life cycle assessment to determine the minimum fuel selling price (MFSP), global warming potential (GWP), and freshwater consumption impacts of algal biofuels for five MTTF scenarios of 20, 54, 80,120, and 350 days, assuming an average mean-time-to-reset of 7 days. Results show that higher MTTFs reduce the cost and environmental impact of algal biofuels, but with diminishing returns. The average MFSPs for the 20-day, 54-day, and 350-day MTTF scenarios were $\$3.52$, $\$2.54$, and $\$2.10$ per liter of gasoline equivalent, respectively. The GWP for the same scenarios were 131, 96, and 83 g CO 2eq MJ –1 , respectively. This study highlights the significant impact of larger seed trains, required under low MTTFs, on the costs and greenhouse gas emissions of algal biofuels. Moreover, the work shows that algal biofuels fail to be cost-competitive with conventional fuels, even when productivities are increased from 17 to 35 g m –2 d –1 . Furthermore, this work is the first to explore the implications of pond failure on the sustainability of algal biofuels and provides valuable insights to algae farmers on how to reduce the costs and financial risks of algal cultivation through process design and pond management strategies.

09 BIOMASS FUELS↗

DOE OSTI2024

The phototrophic purple non‐sulfur bacteria Rhodomicrobium spp. are novel chassis for bioplastic production

Abstract Petroleum‐based plastics levy significant environmental and economic costs that can be alleviated with sustainably sourced, biodegradable, and bio‐based polymers such as polyhydroxyalkanoates (PHAs). However, industrial‐scale production of PHAs faces barriers stemming from insufficient product yields and high costs. To address these challenges, we must look beyond the current suite of microbes for PHA production and investigate non‐model organisms with versatile metabolisms. In that vein, we assessed PHA production by the photosynthetic purple non‐sulfur bacteria (PNSB) Rhodomicrobium vannielii and Rhodomicrobium udaipurense. We show that both species accumulate PHA across photo‐heterotrophic, photo‐hydrogenotrophic, photo‐ferrotrophic, and photo‐electrotrophic growth conditions, with either ammonium chloride (NH 4 Cl) or dinitrogen gas (N 2 ) as nitrogen sources. Our data indicate that nitrogen source plays a significant role in dictating PHA synthesis, with N 2 fixation promoting PHA production during photoheterotrophy and photoelectrotrophy but inhibiting production during photohydrogenotrophy and photoferrotrophy. We observed the highest PHA titres (up to 44.08 mg/L, or 43.61% cell dry weight) when cells were grown photoheterotrophically on sodium butyrate with N 2 , while production was at its lowest during photoelectrotrophy (as low as 0.04 mg/L, or 0.16% cell dry weight). We also find that photohydrogenotrophically grown cells supplemented with NH 4 Cl exhibit the highest electron yields – up to 58.89% – while photoheterotrophy demonstrated the lowest (0.27%–1.39%). Finally, we highlight superior electron conversion and PHA production compared to a related PNSB, Rhodopseudomonas palustris TIE‐1. This study illustrates the value of studying non‐model organisms like Rhodomicrobium for sustainable PHA production and indicates future directions for exploring PNSB metabolisms.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Reduction kinetics of hematite powder using argon/hydrogen plasma with prospects for near net shaping of sustainable iron

Direct reduction of iron ore using hydrogen plasma is being explored as a potential solution to decarbonize the iron and steel sector. The current state-of-the-art demonstrated reduction of hematite pellets via hydrogen plasma using Ar + 10% H 2 but had slow reduction kinetics, requiring 30 minutes of plasma exposure for complete reduction. Here we show that using hematite in a powder form, easily obtainable from beneficiated ore, results in 10× faster kinetics using plasma generated from Ar + 2% H 2 shielding gas compared to the current state-of-the art. Additionally, the increased kinetics using powders and a dilute hydrogen concentration can enable the use of advanced manufacturing techniques like blown powder directed energy deposition using a plasma tungsten arc welding torch to manufacture near net shape components directly from the ore concentrates. This ore to part approach will also reduce the emissions associated with downstream processes like rolling, forging, and machining, thereby further aiding in the sectorial decarbonization efforts.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Navigating Exascale Operational Data Analytics: From Inundation to Insight

In this paper, we address the challenges in achieving sustainable data-driven efficiency by providing a detailed exploration of the end-to-end operational data analytics (ODA) framework that evolved through two generations of supercomputer systems at the Oak Ridge Leadership Computing Facility (OLCF). This framework addresses large data streams ingested from heavily instrumented HPC environment that accumulates multi-terabytes per day. We outline the multifaceted data life cycle across HPC procurement, operations, and research & development, identifying key obstacles and design decisions that shape effective strategies in building and supporting data pipelines end-to-end. By sharing key insights and lessons learned from our experience, we offer recommendations for the HPC community on enabling sustainable operational data analytics and beyond. Our contributions aim to bridge the gap between potential and real benefits of operational data, guiding future efforts towards integrated and sustainable operational intelligence in high-performance computing environments.

Shin, Woong↗

DOE OSTI2024

Nitrogen fertilization effects on aged Miscanthus × giganteus stands: Exploring biomass yield, yield components, and biomass prediction using in–season morphological traits

For sustainable biomass production of Miscanthus × giganteus (hereafter miscanthus), understanding the impact of stand age and nitrogen (N) fertilization on biomass yield is crucial. This study investigated the effects of varying N fertilization rates (0, 56, 112, and 168 kg N ha –1 ) on yield components (tiller height, density, and weight) and their correlations with end-of-season biomass yield in miscanthus. We also explored end-of-season biomass yield prediction using in-season traits (canopy height, leaf area index, and leaf chlorophyll content [LCC]). The study was conducted at two sites in Illinois: a previously unfertilized 10-year-old miscanthus research stand at Urbana and a 16-year-old commercial stand at Pesotum with a history of annual 56N application. Results from 2018 to 2021 in Urbana and 2020 to 2021 in Pesotum showed increased biomass yields with N fertilization, varying by rate, year, and location. Biomass yield in Pesotum peaked at 56N, while in Urbana, it increased significantly at 112 kg N ha –1 . Biomass yield was strongly correlated with tiller height and weight measured at Urbana across N rates. Morphological traits measured every 2–3 weeks during the 2020 and 2021 growing seasons showed that canopy height was the strongest single predictor of miscanthus biomass yield, followed by LCC. Mid-August to September measurements of these traits were the best predictors of biomass yield. Multiple regressions involving the canopy height and LCC further improved yield predictions. We conclude that while N enhances biomass yields of aging miscanthus, the optimum rate depends on the site, environmental conditions, and management history.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Dynamic microbial assembly processes correspond to soil fertility in sustainable paddy agroecosystems

1. Microorganisms underpin the sustainability of agroecosystems, but we have a poor understanding of how the assembly processes that govern microbial community structure interact through time to maintain soil fertility. 2. Ancient rice paddies have a history of cultivation spanning hundreds or thousands of years and provide an ideal opportunity to explore relationships between community assembly processes and long-term agroecosystem sustainability. We used statistical null models to evaluate temporal patterns of bacterial community assembly processes across rice cultivation years and their associations with increases in soil fertility in paddy agroecosystems. 3. We found that stochasticity was a persistent force structuring paddy soil microbial communities, putatively due to frequent flooding that facilities dispersal. However, determinism gradually increased over centuries of agriculture and corresponded to increases in soil fertility. Accordingly, multifunctionality, calculated using enzymes catalyzing key soil functions in carbon, nitrogen, phosphorous and sulfur cycling significantly increased along rice cultivation years. We therefore propose that balanced assembly processes preserve a diverse array of traits that can dominate under various circumstances (stochasticity) while allowing for traits relevant to soil fertility to be selected for by soil fertility (determinism), thus supporting multifunctionality that underlies sustainable agroecosystems. 4. In total, our results highlight that knowledge on temporal microbial assembly processes, community composition, and ecological function in context of soil fertility is key to understanding ecological mechanisms maintaining agroecosystems sustainability.

Liu, Wenjing↗

DOE OSTI2025

Urban heat islands can influence the wind energy resource during heatwaves

Urban wind energy is critical for sustainable electricity generation in cities. However, little research has explored how the urban heat island (UHI) effect influences wind energy, particularly in heatwaves when energy demand surges. In this study, we examine wind energy distribution in the Boston–Providence metropolitan area during heatwaves, using Weather Research and Forecasting (WRF) model integrated with Building Energy Parameterization/Building Energy Model (BEP/BEM). Two scenarios, a realistic case and a hypothetical case without urban warmth, were compared to isolate UHI impacts. Results reveal that UHI induces a "wind energy loss zone" in this urban area, reducing wind power density (WPD) by 20–30 W/m 2 at 50–100 m, while suburban/rural areas exhibit a "wind energy gain zone," with WPD increases up to 40 W/m 2 at 150–200 m. These losses diminish with distance from urban centers and become negligible beyond main urban and suburban sprawl. Heatwave expands the urban "loss zone", while amplifying wind energy gains in suburban/rural areas, driven by stronger thermal gradients and weakened background winds that intensify air convergence in urban and urban-rural circulations, thereby exacerbating urban wind energy losses by 15–20 %. An analysis of 235 wind farms using turbine power curves reveals that built areas dependent on stand-alone or off-grid turbines face significant energy deficits during a heatwave. Wind energy drops by up to 25 %, while cooling-related building energy demand rises 30–40 % during a heatwave. These findings underscore the need for strategic urban wind energy planning to ensure reliable power during extreme heat.

Energy - Wind↗

DOE OSTI2021

KIF18b-dependent hypomethylation of PARPBP gene promoter enhances oxaliplatin resistance in colorectal cancer

Highlights: • High expression of PARPBP promotes oxaliplatin resistance of CRC. • KIF18b induces PARPBP expression by suppressing promoter methylation. • SP1 recruits DNMT3b to methylate PARPBP promoter. • KIF18b disturbs the recruitment of DNMT3b to PARPBP promoter. As the new platinum drug oxaliplatin has been widely used in clinical treatment of colorectal cancer (CRC), oxaliplatin resistance has become a burning problem. In this study, higher expression of PARP-1 binding protein (PARPBP) was detected in oxaliplatin-resistant CRC (OR-CRC) cells than in non-resistant cells. Further research showed that kinesin family member 18 b (KIF18b) induced the overexpression of PARPBP, sustaining oxaliplatin resistance in OR-CRC cells. Through exploring the PARPBP gene promoter, we found that SP1-recruited DNMT3b methylated PARPBP promoter to suppress transcription in CRC cells, and increased KIF18b attenuated the recruitment of DNMT3b to PARPBP promoter by directly interacting with SP1 in OR-CRC cells. Clinical analysis suggested a positive relationship between KIF18b and PARPBP in CRC tissues and indicated poor prognosis in CRC patients with high level of KIF18b or PARPBP. In summary, KIF18b-induced PARPBP contributes to the resistant phenotype of OR-CRC.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Seismic Ambient Noise Analyses Reveal Changing Temperature and Water Signals to 10s of Meters Depth in the Critical Zone

The critical zone sustains terrestrial life, but we have few tools to explore it efficiently beyond the first few meters of the subsurface. Using analyses of high-frequency ambient seismic noise from densely spaced seismometers deployed in the forested Shale Hills subcatchment of the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO), we show that temporal changes in seismic velocities at depths from ~1 m to tens of m can be detected. Furthermore, these changes are driven by variations at the land surface. The Moving-Window Cross-Spectral (MWCS) method was employed to measure seismic-velocity changes in coda waves at hourly resolution in 10 different frequency bands. We observed a diurnal signal, a seasonal signal, and a meteorological-event-based signal. These signals were compared to time-series measurements of precipitation, well water levels, soil moisture, soil temperature, air temperature, latent heat flux, and air pressure in the heavily instrumented catchment. Most of the velocity changes can be explained by variations in temperature that result in thermoelastic strains that propagate to depth. But some double minima in seismic velocity time-series observed after large rain events were attributed in part to the effects of water infiltration. These results show that high-frequency ambient noise data may in some locations be used to detect changes in the critical zone from ~1 to ~100 m or greater depth with hourly resolution. But interpretation of such data requires multiple environmental data sets to deconvolve the complex interrelationships among thermoelastic and hydrological effects in the subsurface critical zone.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Large CO 2 removal potential of woody debris preservation in managed forests

Limiting climate warming to 1.5 °C requires reductions in greenhouse gas emissions and CO 2 removal. While various CO 2 removal strategies have been explored to achieve global net-zero greenhouse gas emissions and account for legacy emissions, additional exploration is warranted to examine more durable, scalable and sustainable approaches to achieve climate targets. Here, in this study, we show that preserving woody debris in managed forests can remove gigatonnes of CO 2 from the atmosphere sustainably based on a carbon cycle analysis using three Earth system models. Woody debris is produced from logging, sawmill wastes and abandoned woody products, and can be preserved in deep soil to lengthen its residence time (a measure of durability) by thousands of years. Preserving annual woody debris production in managed forests has the capacity to remove 769–937 GtCO 2 from the atmosphere cumulatively (10.1–12.4 GtCO 2 yr −1 on average) from 2025 to 2100, if its residence time is lengthened for 100–2,000 years and after 5% CO 2 removal is discounted to account for CO 2 emission due to machine operation for wood debris preservation. This translates to a reduction in global temperatures of 0.35–0.42 °C. Given the large potential, relatively low cost and long durability, future efforts should be focused on establishing large-scale demonstration projects for this technology in a variety of contexts, with rigorous monitoring of CO 2 removal, its co-benefits and side-effects.

Luo, Yiqi [Cornell Univ., Ithaca, NY (United State↗

DOE OSTI2026

Accelerating catalytic advancements through the precision of high-throughput experiments & calculations

The growing demand for energy-efficient processes to support a sustainable future drives the need for research to rapidly explore chemical and material space through accelerated catalyst discovery initiatives. Recent breakthroughs in high-throughput experimental and computational methods are transforming the catalysis field, surpassing traditional approaches to manipulating variables in catalytic processes. Key advancements in innovation include the integration of machine learning for efficient catalyst screening, high-throughput experimentation, data-driven methodologies employing comprehensive databases, and in situ and in operando techniques for realistic observations. This progress has undoubtedly been intertwined with a collaborative framework across disciplines, reshaping catalyst discovery methods in both industry and academia. This Opinion article presents a multifaceted perspective from coauthors with expertise spanning various stages of the Technology Readiness Level spectrum, highlighting both opportunities and persistent challenges in integrating computational and experimental approaches in catalysis. These challenges span from obtaining high-quality experimental data, scaling simulations to industrially relevant materials and process conditions to navigating the complexity and predictive accuracy of computational models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗