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At least 127 records · Page 7

Injection data analysis using material balance time for CO 2 storage capacity estimation in deep closed saline aquifers

Estimating the ultimate storage capacity of deep saline aquifers is important to address the formation potential to store the envisioned large volumes of CO 2 . Injection data (i.e. injection rate, bottomhole pressure, and cumulative injected volume of CO 2 ) are routinely recorded during storage operations. These data contain valuable information on the subsurface (e.g. the reservoir pore volume and the formation storage capacity) that can be extracted. In this paper, we present a two-step graphical technique to infer the pore volume and the ultimate storage capacity of closed saline aquifers by analyzing the available injection data. First, the pore volume is inferred through adapting the concept of the material balance time. Material balance time is an approximate superposition time function developed to interpret production data from oil and gas wells operating at variable pressure/rate conditions during the boundary-dominated flow period. Using material balance techniques, the ultimate storage capacity is then estimated through linear extrapolation of the average pressure trend to the maximum allowable pressure the formation can withstand. The average pressure is not available in practice, but is can be obtained from the injection data. Two approaches are presented in this study to calculate the average pressure; namely the rigorous and the approximate approaches. Unlike the rigorous approach, the approximate approach does not require a prior knowledge of some reservoir properties (e.g. relative permeability, absolute permeability, formation porosity and thickness) to calculate the average pressure. To investigate its potential and reliability in analyzing CO 2 injection data, the proposed technique is applied to four synthetic cases representing different well operating conditions. Results indicate that the approximate approach consistently overestimates the actual (simulated) storage capacity as compared to the rigorous approach. The agreement - between the inferred and the simulated reservoir pore volume, and between the analytical and numerical estimates of storage capacity - validates the potential application of the technique to CO 2 storage in closed saline aquifers. The technique is further substantiated through application to a field data set utilized from a commercial-scale geological storage (CGS) project. Finally, field data interpretation shows that the proposed technique can be utilized to identify the degree of hydraulic continuity and reservoir compartmentalization within a target formation by interpreting the corresponding pressure and rate responses.

02 PETROLEUM↗

Ferrimagnetic spin waves in honeycomb and triangular layers of Mn{sub 3}Si{sub 2}Te{sub 6}.

A detailed analysis of the ferrimagnetic ground state of Mn 3 Si 2 Te 6 has been performed using inelastic neutron scattering. Although the proposed valence of the nominal Mn 2+ ions would have quenched orbital angular momentum, a significant exchange anisotropy exists in Mn 3 Si 2 Te 6 . This apparent exchange anisotropy is a manifestation of a weak spin-orbit coupling in the layered material. We employ a detailed simulation of the spin-wave spectrum coupling traditional refinement of dispersion parameters to image analysis techniques, while including Monte Carlo simulations of the instrumental resolution to accurately identify the exchange couplings to the third nearest neighbor. An independent validation of our results is made by comparing our final Hamiltonian to heat capacity measurements.

Sala, G.↗

Modeling the impact of extreme summer drought on conventional and renewable generation capacity: Methods and a case study on the Eastern U.S. power system

Across recent years, there has been a growing prevalence of extreme weather events throughout the United States, posing significant challenges to the reliable and resilient operation of power systems. Specifically, summer droughts threaten to severely reduce available generation capacity to meet regional electricity demand, potentially leading to power outages. This underscores the importance of accurate resource adequacy (RA) assessment to ensure the reliable operation of the nation’s energy infrastructure. Accurately evaluating the usable capacity of regional generation fleets is a challenging undertaking due to the intricate interactions between power systems and hydro-climatic systems. Here, this paper proposes a systematic and analytical framework to evaluate the impacts of extreme summer drought events on the available capacity of various generating technologies, incorporating both meteorological and hydrologic factors. The framework provides detailed plant-level capacity derating models for hydroelectric, thermoelectric, and renewable power plants, facilitating evaluations with high temporal and spatial resolution. The application of the proposed impact assessment framework to the 2025 generation fleet of the real-world power system within the PJM and SERC regions of the United States yields insightful results. By analyzing the daily usable capacity of 6,055 at-risk generators across the study region, it shows that the summer capacity deration is most significant for hydroelectric and once-through thermal power plants, followed by recirculating thermal power plants and combustion turbines. In the event of the recurrence of the 2007 southeastern summer drought event in the near future, the generation fleet could experience a substantial reduction in available capacity, estimated at approximately 8.5 GW, compared to typical summer conditions. The sensitivity analysis reveals that the usable capacity of the generation fleet would suffer an even more significant decrease under conditions of increasingly severe summer droughts. The proposed approach and the findings of this study provide valuable methodologies and insights, empowering stakeholders to bolster the resilience of power systems against the potentially devastating effects of future extreme drought events.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Tutorial: Lessons Learned for Behavior Analysts from Data Scientists

Big data is a computing term used to refer to large and complex data sets, typically consisting of terabytes or more of diverse data that is produced rapidly. The analysis of such complex data sets requires advanced analysis techniques with the capacity to identify patterns and abstract meanings from the vast data. The field of data science combines computer science with mathematics/statistics and leverages artificial intelligence, in particular machine learning, to analyze big data. This field holds great promise for behavior analysis, where both clinical and research studies produce large volumes of diverse data at a rapid pace (i.e., big data). This article presents basic lessons for the behavior analytic researchers and clinicians regarding integration of data science into the field of behavior analysis. We provide guidance on how to collect, protect, and process the data, while highlighting the importance of collaborating with data scientists to select a proper machine learning model that aligns with the project goals and develop models with input from human experts. Here, we hope this serves as a guide to support the behavior analysts interested in the field of data science to advance their practice or research, and helps them avoid some common pitfalls.

42 ENGINEERING↗

Gravity Well Commercial Economics Assessment: Potential Revenue and Cost: Cooperative Research and Development (Final Report)

In the Gravity Well Revenue Study, we evaluate the potential revenue from energy storage using historical energy-only electricity prices, forward-looking projections of hourly electricity prices, and actual reported revenue. This analysis examines the impact of storage duration and round-trip efficiency, as well as the location of the storage, on storage revenue within the current and projected U.S. power system. We also investigated the impact of round-trip efficiency on storage revenue. We found that the relationship between storage revenue and round-trip efficiency is nonlinear. The value of improved round-trip efficiency declines as round-trip efficiency increases. In the Gravity Well Future Cost Study, we applied learning curves to predict the future cost trajectory of Gravity Wells (GrWs). Two types of analysis were implemented. The first was a bottom-up analysis that used historical learning rates for cost components, such as motors and gearboxes, and cost categories (e.g., engineering and design, etc.) to determine the learning-by-doing based single-factor learning curve. The single factor learning curve expresses the relationship between the cost of GrW and the number of units deployed (or the cumulative capacity). In the second analysis, we predicted future GrW costs via a top-down approach. This approach accounts for historical cost trends in other renewable energy and storage technologies, which have similarities with GrWs. Using a multifactor learning curve that accounts for both intrinsic (cumulative capacity) and extrinsic (the elasticity in the price of steel) factors, we estimated the future cost of GrWs.

25 ENERGY STORAGE↗

Qualification of SAS4A/SASSYS-1 for Sodium-Cooled Fast Reactor Authorization and Licensing (Final CRADA Report)

This project focuses on assessment and qualification of the SAS4A/SASSYS-1 advanced reactor safety analysis code and its capacity to fulfill requirements associated with license/authorization of a sodium-cooled fast reactor (SFR). Specific objectives of this proposal include: development of a formal documentation requirements matrix that complies with a vendor’s NQA-1 program to identify needs for qualification documentation; completion of software methods qualification gap analysis to identify and close gaps in the verification and validation basis of the software; generation of an Acceptance Test Report to confirm compliance with the software requirements specification; and closure of gaps in Software Design Description (SDD) to assist with the eventual generation of a Modeling Licensing Topic Report (LTR).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Aberrant FBXW7-mediated ubiquitination and degradation of ZMYND8 enhances tumor progression and stemness in bladder cancer

ZMYND8, an epigenetic regulator, was identified as a common oncogene across various tumors. However, little was reported about the association between ZMYND8 and bladder cancer. Besides, aberrant mechanisms that contribute to abnormal ZMYND8 expressions still remain unclear. In the current study, we first found that ZMYND8 protein levels were significantly elevated in Bca samples versus normal tissues, but not the mRNA levels. We then utilized the Cell Counting Kit-8 (CCK-8) assay, clone formation assay and transwell analysis to confirm that ZMYND8 could remarkably promote the tumor progression in vitro, including growth capacity and migration. Bioinformatic predictive analysis revealed that E3 ubiquitin ligase FBXW7 interacts directly with ZMYND8 and degrades ZMYND8 in a polyubiquitination manner. Low FBXW7 was a hazard factor for promoting and depending on accumulated ZMYND8 proteins to promote Bca progression. Gene set enrichment analysis (GSEA) further indicated that ZMYND8 was notably associated with stemness process, which was well functionally validated. Lastly, ZMYND8 deficiency was observed to inhibit tumor growth of Bca in vivo, revealing a promising translational significance in Bca treatment. In conclusion, our study for the first time provided evidence for a novel mechanism of FBXW7/ZMYND8 axis in Bca, providing therapeutic vulnerability for individualized cancer treatment.

60 APPLIED LIFE SCIENCES↗

Disorder-induced local strain distribution in Y-substituted TmVO 4

We report an investigation of the effect of substitution of Y for Tm in Tm 1-x ⁢Y x VO 4 via low-temperature heat capacity measurements, with the yttrium content x varying from 0 to 0.997. Because the Tm ions support a local quadrupolar (nematic) moment, they act as reporters of the local strain state in the material, with the splitting of the ion's non-Kramers crystal field ground state proportional to the quadrature sum of the in-plane tetragonal symmetry-breaking transverse and longitudinal strains experienced by each ion individually. Analysis of the heat capacity, therefore, provides detailed insights into the distribution of local strains that arise as a consequence of the chemical substitution. These local strains suppress long-range quadrupole order for x > 0.22, and result in a broad Schottky-like feature for higher concentrations. Heat capacity data are compared to expectations for a distribution of uncorrelated (random) strains. For dilute Tm concentrations, the heat capacity cannot be accounted for by randomly distributed strains, demonstrating the presence of significant strain correlations between sites. For intermediate Tm concentrations, these correlations must still exist, but the data cannot be distinguished from that which would be obtained from a two-dimensional Gaussian distribution. The crossover between these limits is discussed in terms of the interplay of key lengthscales in the substituted material. Furthermore, the central result of this work, namely that local strains arising from chemical substitution are not uncorrelated, has implications for the range of validity of theoretical models based on random effective fields that are used to describe such chemically substituted materials, particularly when electronic nematic correlations are present.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Using multiple high-resolution datasets to benchmark the energy exascale earth system model (E3SM) for renewable resource assessment

The United States is accelerating its shift toward a renewable energy system. However, renewable resources, which harness energy from the Earth system, are susceptible to both present-day climate variability and future climate change. For example, variations in regional climate can alter renewable energy production patterns and site viability. The use of high-resolution climate model projections can therefore facilitate and may be critical to long-term planning of renewable energy investments. However, climate models must first be validated for renewable resource assessment. This research employs multiple high-spatiotemporal-resolution datasets to assess the capability of the Department of Energy’s (DOE) Energy Exascale Earth System Model version 2 North American Regionally Refined Model (E3SMv2-NARRM) for predicting multi-year climatological values of solar and wind energy capacity factors in the continental U.S., with a focus on regional and seasonal variability. Present-day E3SMv2-NARRM simulations are compared with reported utility-scale production data obtained from the Energy Information Administration (EIA). In addition, E3SMv2-NARRM data are evaluated against non-climate benchmark models from the National Renewable Energy Laboratory, including the Wind Integration National Dataset Toolkit and the National Solar Radiation Database (NSRDB), as well as three wind energy datasets from PLUSWIND. Our analysis indicates that solar capacity factors from E3SM closely match those from the NSRDB dataset. However, both datasets tend to overestimate values by 10% in comparison to EIA data. Furthermore, biases in wind capacity factors within E3SM are notably pronounced in the West Coast regions, where the seasonal cycle diverges from EIA data.

Energy forecasting, Capacity factor, Renewable ene↗

Anodic Interfacial Evolution in Extremely Fast Charged Lithium-Ion Batteries

Interfacial reaction mechanisms at the anode/separator interface play a central role in the performance and safety of lithium-ion batteries during fast charging. We report a mechanistic study on the evolution and interactions of the aging mechanisms at the anode/separator interface in lithium cobalt oxide/graphite pouch cells charged with variable charging rates (1–6C) over 10 cycles. In situ electrochemical measurements, including voltage relaxation, Coulombic efficiency, and direct current internal resistance, indicated an incremental lithium loss until the C rates were ≤5C. A substantial capacity fade is observed in the first few cycles of fast charging, but the magnitude of capacity fade progressively diminishes with the number of cycles, indicating a suppression in the lithium deposition mechanism. Post-mortem film thickness, X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (SEM) analyses were performed to elucidate the evolution of electrolyte decomposition, the solid–electrolyte interface (SEI), lithium plating, and film fracture mechanisms with C rate. XPS measurements confirmed an increasing lithium concentration in an SEI film with an increase in the C rate. SEM images showed a growth of dendritic lithium on the anode surface from 1C to 3C. Precrack formation leading to an interfacial film fracture was observed at higher C rates. Furthermore, a differential analysis of the discharge capacity indicated a possible two-phase delithiation from the anode and reduced cathodic lithiation due to lithium loss at high C rates.

36 MATERIALS SCIENCE↗

Beyond magnons in Nd 2 ScNbO 7 : An Ising pyrochlore antiferromagnet with all-in–all-out order and random fields

We report the low-temperature magnetic properties of Nd 3+ pyrochlore Nd 2 ScNbO 7 . Susceptibility and magnetization show an easy-axis moment, and heat capacity reveals a phase transition to long-range order at T N =371(2) mK with a fully recovered ΔS=Rln(2), 53% of it recovered for T>T N . Elastic neutron scattering shows a long-range all-in all-out magnetic order with low-Q diffuse elastic scattering. Inelastic neutron scattering shows a low-energy flat band, indicating a magnetic Hamiltonian similar to Nd 2 Zr 2 O 7 . Nuclear hyperfine excitations measured by ultra-high-resolution neutron backscattering indicate a distribution of static electronic moments below T N , which may be due to B-site disorder influencing Nd crystal electric fields. Analysis of heat-capacity data shows an unexpected T-linear or T 3/2 term which is inconsistent with conventional magnon quasiparticles, but is consistent with fractionalized spinons or gapless local spin excitations. We use legacy data to show similar behavior in Nd 2 Zr 2 O 7 . Comparing local static moments also reveals a suppression of the nuclear Schottky anomaly in temperature, evidencing a fraction of Nd sites with nearly zero static moment, consistent with exchange-disorder-induced random singlet formation. Finally, taken together, these measurements suggest an unusual fluctuating magnetic ground state which mimics a spin liquid, but may not actually be one.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Subsurface H 2 Storage: A Williston Basin Commercial-Scale Resource Study

Poster for the 2024 NETL Resource Sustainability Project Review Meeting, Pittsburgh, Pennsylvania, April 2-4, 2024. This poster presents a commercial‑scale assessment of subsurface hydrogen storage potential in the North Dakota portion of the Williston Basin, evaluating saline formations, depleted oil and gas reservoirs, and salt formations. The study integrates laboratory characterization, reservoir simulation, and basinwide analysis to assess storage capacity, injectivity, recovery, and risks related to geochemical, microbial, and wellbore interactions. Results support the feasibility of large‑volume, secure hydrogen storage and provide a framework to guide future hydrogen commercialization and infrastructure development.

08 HYDROGEN↗

Cu Doping Increases Capacity Retention in LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) by Altering the Potential of the Ni-Based Redox Couple and Inhibiting Particle Pulverization

To discern the influence of Cu 2+ as a dopant on both the structural and electrochemical characteristics of LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622), Cu 2+ (aq) was added to the coprecipitation synthesis from the constituent ions. At 5 mol % Cu 2+ , a single-phase Cu-NMC product results, evidenced by an increase in d-spacing along the [003] and [104] directions and a slight increase in the crystal volume of the R–3m hexagonal (rock-salt superstructure) lattice. XRD data and high-resolution TEM imaging support Cu 2+ doping primarily on the transition metal 3b Wyckoff sites. Here, galvanostatic cycling of Cu-NMC shows a reversible gravimetric capacity of 102 mAh/g compared to 136 mAh/g for undoped NMC. Despite the lower capacity, the discharge capacity retention of Cu-NMC is 89% after 100 cycles compared to only 70% for NMC. XPS analysis reveals that this lower capacity is due to an increase in the concentration of Ni 3+ ions at the surface, while XRD data collected at the top and bottom of charge show a smaller decrease in crystalline domain size for Cu-NMC (40.5% decrease) compared to NMC (74.7% decrease), translating to pulverization of the secondary particles.

25 ENERGY STORAGE↗

Lithium inventory tracking as a non-destructive battery evaluation and monitoring method

Tracking the active lithium (Li) inventory in an electrode shows the true state of a Li battery, akin to a fuel gauge for an engine. However, non-destructive Li inventory tracking is currently unavailable. Here, in this work, we used the theoretical capacity of a transition metal oxide to convert capacity into a Li inventory analysis. The Li inventory in electrodes was tracked reliably to show how battery formulations and test methods affect performance. Contrary to capacity, Li inventory tracking reveals stoichiometric variations near the electrode–electrolyte interface. Verifiable results rationalized differences in measurements, clarifying and reducing interferences from cell formulations and experimental manipulations. By tracing four variables from formation to end-of-life, we characterize electrode and cell performance with a thermodynamic framework. Accurate rationalization of subtle differences in Li inventory utilization promises precise battery engineering, evaluation, failure analysis and risk mitigation. The method could be applicable from cell design optimization and fabrication to battery management, improving battery performance and reliability.

25 ENERGY STORAGE↗

Limited potential of irrigation to prevent potato yield losses in Germany under climate change

Climate models project higher temperatures and a substantial net water deficit during the summer months over Germany until the end of the 21st century. The agricultural sector is particularly vulnerable to changing weather and climate conditions. In this study, we examine the role of irrigation for potato yields as a climate change adaptation measure in Northeast Lower Saxony (Germany). The region represents the largest irrigated area in Germany and is one of the main growing areas of potatoes. We develop a statistical multivariate regression model to investigate whether regional climate and irrigation data at the monthly and county level are suitable to describe potato yield variability from 1978 to 2018. Irrigation is estimated based on the climatic water balance and crop water demand. These estimates are calibrated against irrigation data from local agencies to account for realistic monthly water withdrawals. We analyze future yield changes based on climate model projections for the 21st century and different irrigation scenarios. We find that the potato yield will decrease significantly by 18% on average until 2050 with climate projection uncertainty of ±6.4% under the high emission scenario RCP 8.5 and without irrigation. Irrigation at current levels could compensate for about 54% of these yield losses. Doubling the amount of irrigation minimizes yield losses by as much as 80%. Under the low (middle) emission scenario RCP 2.6 (RCP 4.5), potato yield are projected to decrease moderately by 4.5% ± 3.4% (5.4% ± 2.8%) with irrigation at current levels. We show that the yield losses mainly originate from higher temperatures during the summer. Our analysis indicates that the capacity of irrigation to minimize yield losses is limited. Strengthening climate change mitigation efforts may be more effective in preventing yield losses. However, the effect of elevated CO 2 might buffer the high yield losses, especially in RCP 8.5. The studies supports farmers and decision makers in assessing future risks in potato yields. It can guide policymakers in allocating economic resources to cope with climate change.

60 APPLIED LIFE SCIENCES↗

Vibrational Entropy Contribution to Mixing Free Energy of Ni-Rich LiNi 1- y Co y O 2

First principles density-functional-theory calculations are performed of the mixing free energy of the layered oxide LiNi 1-y Co y O 2 , a model Li-ion-battery cathode material, at 1000 K. Analysis of internal energy, LN exchange, configurational entropy and vibrational entropy are combined to obtain the net mixing free energy. The vibrational entropy requires a more indirect treatment than the other terms; analysis based on heat capacity is presented here, to show that the vibrational entropy is of comparable magnitude to the configurational entropy, and it tends to promote solid-solution behavior in LiNi 1-y Co y O 2 .

25 ENERGY STORAGE↗

Rapid charging made practical in graphite-based lithium batteries: surface-acoustic wave turbulent electrolyte mixing to overcome diffusion limited charging rates [Final Report]

One of the key limits in rapidly recharging a lithium-ion battery is the depletion of lithium ions within the electrolyte adjacent the anode during charging and long diffusion time to overcome this depletion. It also causes dendrite formation, inefficient use of the lithium, and battery degradation over many charge-discharge cycles. Because the liquid electrolyte remains quiescent and unmixed, this depletion layer’s depth rapidly grows to match the anode-cathode separation distance at even modest charge rates. The solution proposed by PI Prof. James Friend and Co-PI Prof. Ping Liu, both from the University of California, San Diego, is to mix the electrolyte and minimize the Li+ ion concentration gradient during charging. Even in the presence of the separator, the charging rate could then be significantly increased. They propose to accomplish this using surface acoustic wave (SAW)-driven acoustic streaming, a technique employing 10-mW fingernail-sized solid-state devices from the telecommunications industry to drive turbulent mixing to submicron length scales in a manner completely compatible with the typical 20700 and 18650 cells used in electric vehicles. 0.1. Turbulent acoustic streaming mixes the electrolyte during charging—even with separator Our proposed 100-MHz SAW device used to recirculate the electrolyte is compatible with lithium- ion battery electrochemistry, as it is made in our lab of single-crystal lithium niobate. Their solution is straightforward to drive from a DC power source alongside the signal provided during battery charging. The device is only needed during charging and does not consume power dur- ing battery discharge. Uniquely, SAW generates extreme accelerations of over 1 billion meters per second squared in the fluid, driving turbulent mixing from centimeter to submicron length scales, even through the porous separator materials that tend to be used in batteries, all while avoiding interfering with the anode’s solid electrolyte interphase layer that forms during use. By employing novel fluid mechanics, the investigators are proposing a new direction for battery research away from direct use of materials science and electrochemistry. The chemistry agnostic solution may be employed in any battery chemistry that makes use of liquid electrolytes, providing a broader transformative benefit to the battery research community. They are to produce a series of prismatic and 20700-cell sized 2 Ah batteries capable of being charged and discharged at least 500 times without more than 20% loss in battery capacity, and to provide analysis tools useful to the battery research and development community for adopting this approach for other battery chemistries and configurations.

25 ENERGY STORAGE↗