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At least 865 records · Page 48

GeoAI advances in specific landform mapping

Landform mapping (also referred to as geomorphology or geomorphometry) can be divided into two domains: general and specific (Evans 2012). Whereas general landform mapping categorizes all elements of the study area into landform classes, such as ridges, valleys, peaks, and depressions, the mapping of specific landforms requires the delineation (even if fuzzy) of individual landforms. The former is mainly driven by physical properties such as elevation, slope, and curvature. The latter, however, must consider the cognitive (human) reasoning that discriminates individual landforms in addition to these physical properties (Arundel and Sinha 2018). Both mapping forms are important. General geomorphometry is needed to understand geological and ecological processes and as boundary layer input to climate and environmental models. Specific geomorphometry supports such activities as disaster management and recovery, emergency response, transportation, and navigation. In the United States, individual landforms of interest are named in the U.S. Geological Survey (USGS) Geographic Names Information System, a point dataset captured specifically to digitize geographic names from the USGS Historical Topographic Map Collection (HTMC). Named landform extent is represented only by the name placement in the HTMC. Recent work has investigated CNN-based deep learning methods to capture these extents in machine-readable form. These studies first relied on physical properties (Arundel et al. 2020) and then included the HTMC as a band in RGB images in limited testing (Arundel et al. 2023). Results from the HTMC dataset surpassed those using just physical properties and using the HTMC alone performed best due to the hillshading and elevation (contour) data incorporated into the topographic maps. However, results fell short of an operational capacity to map all named landforms in the United States. Thus, our current work expands upon past research by focusing on the HTMC and physical information as inputs and the named landform label extents. Specifically, we propose to leverage pre-trained foundation models for segmentation and optical character recognition (OCR) models to jointly map landforms in the United States. Our approach aims to bridge the disparities among the independent information sources to facilitate informed decision-making. The modeling pipeline performs (1) segmentation using the physical information and (2) information extraction using OCR, in parallel. Then a computer vision approach merges the two branches into a labeled segmentation. References: Arundel, Samantha T., Wenwen Li, and Sizhe Wang. 2020. “GeoNat v1.0: A Dataset for Natural Feature Mapping with Artificial Intelligence and Supervised Learning.” Transactions in GIS 24 (3): 556–72. https://doi.org/10.1111/tgis.12633. Arundel, Samantha T, and Gaurav Sinha. 2018. “Validating GEOBIA Based Terrain Segmentation and Classification for Automated Delineation of Cognitively Salient Landforms BT - Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017).” In Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017), Lecture Notes in Geoinformation and Cartography, edited by Paolo Fogliaroni, Andrea Ballatore, and Eliseo Clementini, 9–14. Cham: Springer International Publishing. Arundel, Samantha T., Gaurav Sinha, Wenwen Li, David P. Martin, Kevin G. McKeehan, and Philip T. Thiem. 2023. “Historical Maps Inform Landform Cognition in Machine Learning.” Abstracts of the ICA 6 (August): 1–2. https://doi.org/10.5194/ica-abs-6-10-2023. Evans, Ian S. 2012. “Geomorphometry and Landform Mapping: What Is a Landform?” Geomorphology 137 (1): 94–106. https://doi.org/10.1016/j.geomorph.2010.09.029.

machine learning↗

GeoAI Advances in Specific Landform Mapping

Landform mapping (also referred to as geomorphology or geomorphometry) can be divided into two domains: general and specific (Evans 2012). Whereas general landform mapping categorizes all elements of the study area into landform classes, such as ridges, valleys, peaks, and depressions, the mapping of specific landforms requires the delineation (even if fuzzy) of individual landforms. The former is mainly driven by physical properties such as elevation, slope, and curvature. The latter, however, must consider the cognitive (human) reasoning that discriminates individual landforms in addition to these physical properties (Arundel and Sinha 2018). Both mapping forms are important. General geomorphometry is needed to understand geological and ecological processes and as boundary layer input to climate and environmental models. Specific geomorphometry supports such activities as disaster management and recovery, emergency response, transportation, and navigation. In the United States, individual landforms of interest are named in the U.S. Geological Survey (USGS) Geographic Names Information System, a point dataset captured specifically to digitize geographic names from the USGS Historical Topographic Map Collection (HTMC). Named landform extent is represented only by the name placement in the HTMC. Recent work has investigated CNN-based deep learning methods to capture these extents in machine-readable form. These studies first relied on physical properties (Arundel et al. 2020) and then included the HTMC as a band in RGB images in limited testing (Arundel et al. 2023). Results from the HTMC dataset surpassed those using just physical properties and using the HTMC alone performed best due to the hillshading and elevation (contour) data incorporated into the topographic maps. However, results fell short of an operational capacity to map all named landforms in the United States. Thus, our current work expands upon past research by focusing on the HTMC and physical information as inputs and the named landform label extents. Specifically, we propose to leverage pre-trained foundation models for segmentation and optical character recognition (OCR) models to jointly map landforms in the United States. Our approach aims to bridge the disparities among the independent information sources to facilitate informed decision-making. The modeling pipeline performs (1) segmentation using the physical information and (2) information extraction using OCR, in parallel. Then a computer vision approach merges the two branches into a labeled segmentation.

machine learning↗

Electrolyte and Cutoff Potential Effects on Cycle Life of Li4Ti5O12/LiNi0.9Mn0.1O2 Batteries for Behind-the-Meter Storage Applications

Behind-the-Meter Storage (BTMS) is a stationary battery energy storage system that is connected to the electrical distribution system on the customer's side of the utility's service meter. BTMS systems are used to store electrical energy from the grid as well as inconstant, renewable energy, such as local solar and wind generation. A successful BTMS system will allow the customer to pair their energy generation and storage to optimize electrical consumption from the grid, improving reliability and minimizing cost. For BTMS applications, batteries must be designed and optimized with different set of criteria from other leading segments of the Li-ion battery market, like transportation, due the system being stationary and proximal to the residential or commercial building it's benefitting. BTMS applications prioritize safety, cost (low/no-critical materials), reliability (20-year calendar life), and durability (10,000 cycle life), while having the ability to (minimally) compromise energy density and rate capability. Lithium titanate (Li4Ti5O12-, LTO) is a promising anode candidate for BTMS applications due to its high safety and capacity retention, while maintaining a reasonable 160 mAhg-1 reversable capacity and composition of relatively abundant materials. (1) Specifically, LTO has a high working voltage which helps to prevent Li dendrite formation, improving safety. Furthermore, LTO also has negligible lithiation-based volume change, leading to less mechanical pulverization, or loss of active material, upon cycling. For the cathode, materials with little or no Co are of high interest due to the high cost and low abundance of Co. LiMn2O4 (LMO) has been paired with LTO for BTMS applications in the past due to its safety, low cost (abundancy), and reasonably high operating voltage. (2-4) However, the low capacity of LMO limits energy density and specific energy. While not the highest priority for BTMS applications, increasing energy density will enable deployment in space constrained BTMS applications and decrease total cost. LiNi0.9Mn0.1O2 (LN-MO) is a recently developed material with promise due to its high operating voltage and relatively low price. (5) However, Ni-rich layered oxides, including LNMO, tend to struggle with capacity retention during high-voltage cycling due to mechanical pulverization, irreversible phase transitions, and unstable solid-electrolyte interphase. The study presented here focuses on building an understanding of how electrolyte solvent and varied cutoff potentials will impact the cycle life of LTO/LN-MO cells. Specifically, a comparison is provided between ethylene carbonate (EC), ethyl methyl carbonate (EMC), fluoroethylene carbonate (FEC), and Gen2 electrolyte solvents with 1M Lithium hexafluorophosphate (LiPF6) salt, cycling to two upper termination potentials, 2.6V and 2.7V. Electrochemical testing and diagnostics (e.g., differential capacity analysis, area specific impedance, constant voltage hold, and rate capability) and post-mortem characterization will be used to understand the aging behavior and failure mechanisms of the 8 cell combinations (four electrolytes and two voltage cutoffs). Cells with FEC electrolyte showed a lower initial capacity compared to cells with Gen2, EMC, and EC cycling at both voltages; however, the cells with FEC showed consistent trends in capacity retention with 2.6V and 2.7V termination potentials, while the cells with the other electrolytes showed much higher rates of capacity loss when cycling to the higher voltage. These results indicate that FEC may play a role in improving durability of high-voltage, Ni-rich electrode systems for use in high-cycle applications, such as BTMS.

electrolyte↗

Quantifying Acute Fuel and Respiration Dependent pH Homeostasis in Live Cells Using the mCherryTYG Mutant as a Fluorescence Lifetime Sensor

Intracellular pH plays a key role in physiology, and its measurement in living specimens remains a crucial task in biology. Fluorescent protein-based pH sensors have gained widespread use, but there is limited spectral diversity for multicolor detection, and it remains a challenge to measure absolute pH values. In this work we demonstrate that mCherryTYG is an excellent fluorescence lifetime pH sensor that significantly expands the modalities available for pH quantification in live cells. We first report the 1.09 Å X-ray crystal structure of mCherryTYG, exhibiting a fully matured chromophore. We next determine that it has an extraordinarily large dynamic range with a 2 ns lifetime change from pH 5.5 to 9.0. Critically, we find that the sensor maintains a pK a of 6.8 independent of environment, whether as the purified protein in solution or expressed in live cells. Furthermore, the lifetime measurements are robustly independent of total fluorescence intensity and scatter. We demonstrate that mCherryTYG is a highly effective sensor using time-resolved fluorescence spectroscopy on live-cell suspensions, which has been previously overlooked as an easily accessible approach for quantifying intracellular pH. As a red fluorescent sensor, we also demonstrate that mCherryTYG is spectrally compatible with the ATeam sensor and EGFP for simultaneous dual-color measurements of intracellular pH, ATP, and extracellular pH. In a proof-of-concept, we quantify acute respiration-dependent pH homeostasis that exhibits a stoichiometric relationship with the ATP-generating capacity of the carbon fuel choice in E. coli . Broadly speaking, our work presents a previously unemployed methodology that will greatly facilitate continuous pH quantification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Triarylmethyl cation redox mediators enhance Li–O 2 battery discharge capacities

A major impediment to Li–O 2 battery commercialization is the low discharge capacities resulting from electronically insulating Li 2 O 2 film growth on carbon electrodes. Redox mediation offers an effective strategy to drive oxygen chemistry into solution, avoiding surface-mediated Li 2 O 2 film growth and extending discharge lifetimes. As such, the exploration of diverse redox mediator classes can aid the development of molecular design criteria. Here, in this work, we report a class of triarylmethyl cations that are effective at enhancing discharge capacities up to 35-fold. Surprisingly, we observe that redox mediators with more positive reduction potentials lead to larger discharge capacities because of their improved ability to suppress the surface-mediated reduction pathway. This result provides important structure–property relationships for future improvements in redox-mediated O 2 /Li 2 O 2 discharge capacities. Furthermore, we applied a chronopotentiometry model to investigate the zones of redox mediator standard reduction potentials and the concentrations needed to achieve efficient redox mediation at a given current density. We expect this analysis to guide future redox mediator exploration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CHARACTERIZATION ON ANISOTROPIC THERMAL CONDUCTIVITY FOR BIG AREA ADDITIVE MANUFACTURING WITH POLYMERS

Additive manufacturing with polymers has been used mainly for prototyping. A recent development of Big Area Additive Manufacturing (BAAM) at Oak Ridge National Laboratory has opened its applications in the mold and die industry. A numerical simulation and prediction for a mold heating performance requires accurate anisotropic thermal properties of the printed material, which are challenging to obtain, and often requires the use of multiple techniques. The transient plane source (TPS) technique has been widely used due to its ability to measure the thermal properties of an extensive range of materials (solids, liquids, powder). Despite the capability to characterize thermal conductivity k of isotropic and anisotropic materials, the measurements of latter materials are limited to the cases, where the samples have the same thermal conductivity k along x- and y-axis that form the radial plane. In this work, the method for a characterization of k in all three dimensions is developed, and the application of TPS is extended to the determination of thermal properties along the x-, y-, and z-axis individually. The materials are represented by additively manufactured polymers including polylactic acid (PLA) and styrene maleic anhydride (SMA). The developed method consists of (1) a determination of the heat capacity of the polymers by means of TPS in combination with the developed in this work data analysis procedure, (2) a machining three types of cylindrical samples from the same material, with the height corresponding either to x-, y-, or z-direction of printing, and (3) a determination of axial thermal conductivity employing anisotropic model and using previously determined heat capacity

Trofimov, Artem↗

High-Performance InZn Alloy Anodes toward Practical Aqueous Zinc Batteries

Aqueous Zn batteries have high safety, low-cost and potential of delivering comparable energy density to alkali-ion batteries. However, its practical application is largely hampered by the limited cycle life associated with Zn anodes under conditions of high depth of discharge and high plating current densities. In this work, we report on electrodeposited indium-zinc alloy anodes that have well-dispersed zinc-domains surrounding indium domains that form a porous structure after dealloying which greatly improves tolerance to Zn dendrite formation. The InZn anodes exhibit low polarization of ~5 to 25 mV and demonstrate 700 cycles at a current density of ~10 mA cm -2 with a capacity of 5 mAh cm-2 capacity (45% depth-of-discharge). Full cells with an InZn anode, dibenzo[b,i]thianthrene-5,7,12,14-tetraone (DTT) cathode, in 2M ZnSO 4 deliver a capacity of ~ 110 mAh g -1 and good stability over 40 cycles. Finally, the work reveals a rational design of Zn-based anodes towards practical battery applications and opens the curtain for future development of aqueous Zn batteries.

25 ENERGY STORAGE↗

Tailoring the Reaction Heterogeneity for Robust Li‐Rich Cathodes

The practical application of Li-rich Mn-based layered oxides (LLO) cathode is hindered by severe capacity and voltage degradation resulting from severe oxygen release and irreversible phase transition. In this work, the reaction heterogeneity, which describes the spatially resolved electrochemical divergence within individual cathode particles, is engineered through compositional gradient design to couple Li + transport kinetics and the anion redox activity between particle interiors and surfaces. It is revealed that Co/Mn concentration gradient within particles creates heterogeneous phase content distribution and structural ordering, inducing surface-bulk reaction heterogeneity that significantly impacts the overall electrochemical performance. Specifically, Li 2 MnO 3 -poor and Co-enriched surface effectively mitigates the oxygen loss and enhances electrochemical reaction kinetics, benefited from the reduced surface redox reactivity and induced highly ordered intra-layered cationic arrangement. Meanwhile, the Li 2 MnO 3 -enriched core with slight Li/Ni intermixing provides high reversible capacity and strong mechanical stability. Consequently, the greatly enhanced anion redox reversibility, Li + diffusion dynamics, and structure stability endow LLO with exceptional electrochemical properties, showing a capacity retention of 86.0% and a reduced voltage decay of 0.518 mV per cycle after 500 cycles at 1 C. This work provides a valuable strategy to tailor the redox chemistry and achieve robust LLO.

25 ENERGY STORAGE↗

NUCLEAR INCIDENT CAPABILITIES, KNOWLEDGE & ENABLER LEVERAGING

The detonation of a 10 Kiloton Improvised Nuclear Device (IND) is a serious scenario that the United States must be prepared to address. The likelihood of a single nuclear bomb exploding in a single city is greater today than at the height of the Cold War. Layered defenses against domestic nuclear terrorism indicate that our government continues to view the threat as credible. The risk of such an event is further evidenced by terrorists desire to acquire nuclear weapons. The act of nuclear terrorism, particularly an act directed against a large population center in the United States, will overwhelm the capabilities of many local and state governments to respond, and will seriously challenge existing federal response capabilities. A 10 Kiloton IND detonation would cause total infrastructure damage in a 3-mile radius and levels of radiation spanning out 3,000 square miles. In a densely populated urban area, the anticipated casualties would be in excess of several hundred thousand. Although there would be enormous loss of life, housing and infrastructure, an IND detonation is a recoverable event. We can reduce the risk of these high-consequence, nontraditional threats by enhancing our nuclear detection architecture and establishing well planned and rehearsed plans for coordinated response. It is also important for us to identify new and improved ways to foster collaboration regarding the response to the IND threat to ensure the demand and density of expertise required for such an event is postured and prepared to mobilize, integrate, and support a myriad of anticipated challenges. We must be prepared to manage the consequences of such an event in a deliberate manner and get beyond notions of total devastation by adopting planning assumptions around survivability and resiliency. Planning for such a scenario needs to be decisive in determining a response based on competencies and desired outcomes. It is time to synthesize known threats and plausible consequences into action. Much work needs to be accomplished to enhance nuclear preparedness and to substantially bolster and clarify the capacity to deploy competent resources. Until detailed plans are scripted, and personnel and other resources are postured, and exercised, IND specific planning remains an urgent need requiring attention and action. Although strategic guidance, policies, concepts of operations, roles, responsibilities, and plans governing the response and consequence management for the IND scenario exist, an ongoing integration challenge prevails regarding how best to get capable and competent surge capacity personnel (disaster reservists) and other resources engaged and readied in an up-front manner with pre-scripted assignments to augment the magnitude of anticipated demands of expertise. With the above in mind, Savannah River National Laboratory (SRNL) puts science to work to create and deploy practical, high-value, cost-effective nuclear solutions. As the Department of Energy's (DOE) applied research and development laboratory, SRNL supports Savannah River Site (SRS) operations, DOE, national initiatives, and other federal agencies, across the country and around the world. SRNL's parent at SRS also employs more than 8,000 personnel. The team is a great asset that seeks to continue their service in the interest of national security and stands ready to accomplish new missions. Overall, an integral part of the vision for SRNL's National and Homeland Security Directorate is the establishment of a National Security Center at SRNL, and development of state of the science capabilities (technologies and trained technical personnel) for responding to emergency events on local, regional, or national scales. This entails leveraging and posturing the skills, knowledge and experience base of SRS personnel to deliver an integrated capability to support local, state, and federal authorities through the development of pre-scripted requests for assistance, agreements, and plans. It also includes developing plans, training, exercises, recruitment strategies, and processes to establish a 1,000 plus person nuclear disaster workforce capable of providing surge capacity support that can be deployed in part or in all.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Nitrogen-Doped Graphene-Like Carbon Intercalated MXene Heterostructure Electrodes for Enhanced Sodium- and Lithium-Ion Storage

MXene is investigated as an electrode material for different energy storage systems due to layered structures and metal-like electrical conductivity. Experimental results show MXenes possess excellent cycling performance as anode materials, especially at large current densities. However, the reversible capacity is relatively low, which is a significant barrier to meeting the demands of industrial applications. This work synthesizes N-doped graphene-like carbon (NGC) intercalated Ti 3 C 2 T x (NGC-Ti 3 C 2 T x ) van der Waals heterostructure by an in situ method. The as-prepared NGC-Ti 3 C 2 T x van der Waals heterostructure is employed as sodium-ion and lithium-ion battery electrodes. For sodium-ion batteries, a reversible specific capacity of 305 mAh g -1 is achieved at a specific current of 20 mA g -1 , 2.3 times higher than that of Ti 3 C 2 T x . For lithium-ion batteries, a reversible capacity of 400 mAh g -1 at a specific current of 20 mA g -1 is 1.5 times higher than that of Ti 3 C 2 T x . Both sodium-ion and lithium-ion batteries made from NGC-Ti 3 C 2 T x shows high cycling stability. The theoretical calculations also verify the remarkable improvement in battery capacity within the NGC-Ti 3 C 2 O 2 system, attributed to the additional adsorption of working ions at the edge states of NGC. This work offers an innovative way to synthesize a new van der Waals heterostructure and provides a new route to improve the electrochemical performance significantly.

25 ENERGY STORAGE↗

Understanding the Origins of Higher Capacities at Faster Rates in Lithium-Excess Li x Ni 2–4 x /3 Sb x /3 O 2

Here, the lithium-excess Li x Ni 2-4x/3 Sb x/3 O 2 (LNSO) materials were previously shown to demonstrate higher capacities and improved cyclability with increasing lithium content. While the performance trend is promising, observed capacities are much lower than theoretical capacities, pointing to a need for further understanding of active redox processes in these materials. In this work, we study the electrochemical behavior of the LNSO materials as a function of lithium content and at slow and fast rates. Surprisingly, Li 1.15 Ni 0.47 Sb 0.38 O 2 (LNSO-15) exhibits higher discharge capacities at faster rates and traverses distinct voltage curves at slow and fast rates. To understand these two peculiarities, we characterize the redox activity of nickel, antimony, and oxygen at different rates. While experiments confirm some nickel redox activity and oxygen loss, these two mechanisms cannot account for all observed capacity. We propose that the balance of the observed capacity may be due reversible oxygen redox and that the rate-dependent voltage curve features may derive from irreversible nickel migration occurring on slow charge. As future high energy density cathodes are likely to contain both lithium excess and high nickel content, both of these findings have important implications for the development of novel high capacity cathode materials.

36 MATERIALS SCIENCE↗

Value of Nuclear Energy to the Reliability of the North American Power System: Results for Western and Eastern Interconnections

This report documents the fulfillment of a milestone for the United States (U.S.) Department of Energy Office of Nuclear Energy Light Water Reactor Sustainability Program: completing a baseline study of regional impact of nuclear power plants and hydrogen production in maintaining grid services and power quality. Models have been comprehensively demonstrated for the Western Interconnection, or Western Electric Coordinating Council area, and in the Eastern Interconnection for scenarios representative of past extreme events (e.g., drought and heat waves). Understanding the impact on the reliability of the bulk electric system of any reduction in generation capacity from nuclear power, for any reason, is the motivation of this work. Factors that might lead to the premature or unplanned closure of nuclear plants, extended outages, or repurposing of nuclear power include: • Aging infrastructure: Many nuclear power plants in the U.S. are nearing the end of their designed operating lives. Upgrading aging infrastructure can be expensive, and some utilities may choose to retire plants rather than invest in costly upgrades. • Low wholesale electricity prices: The deregulation of the electricity market in many states has led to increased competition and driven down wholesale electricity prices, causing nuclear power operators to seek other revenue sources for their heat and power such as clean hydrogen production. • Renewables growth: The rapid growth of renewable energy sources like solar and wind power is posing a challenge to traditional generation sources like nuclear. While many see renewables as a key part of the clean energy transition, their intermittent nature requires additional grid solutions for reliable power supply. • The potential for regulatory decisions to be in conflict: In its 2021 rulemaking, EPA rule (86 FR 880), the Environmental Protection Agency (EPA) set a compliance date for the ban on processing and distribution in commerce of Decabromodiphenyl Ether (DecaBDE). Since DecaBDE is in many components, particularly wiring, of nuclear power plants which are deemed safety-related or important to safety, three plants would not have been able to restart after their 2023 spring outages, and numerous others would have faced issues in the near future. Fortunately, in this case, the EPA provided relief to the nuclear energy industry. The report provides a summary of the significant role nuclear energy plays in the United States’ power generation mix, supplying around 20% of the nation’s electricity generation, spread across 28 U.S. states. Nuclear power is reliable, mostly unaffected by weather and seasonal changes, and provides a consistent source of baseload power. In terms of capacity, nuclear power plants account for as much as 26% of balancing area power generation capacity. Nuclear power also provides a substantial contribution (e.g., 10% of the inertia in the Eastern Interconnection) of the synchronous spinning mass/inertia that buffers the rate at which frequency changes when a load and generation imbalance occurs (e.g., a large plant trips or a load is suddenly shed due to a transmission outage). This contribution is critical for maintaining grid stability during sudden changes in load or generation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Investigating the Role of Energy Density in Thermal Runaway of Lithium-Ion Batteries with Accelerating Rate Calorimetry

This work uses accelerating rate calorimetry to evaluate the impact of cell chemistry, state of charge, cell capacity, and ultimately cell energy density on the total energy release and peak heating rates observed during thermal runaway of Li-ion batteries. While the traditional focus has been using calorimetry to compare different chemistries in cells of similar sizes, this work seeks to better understand how applicable small cell data is to understand the thermal runaway behavior of large cells as well as determine if thermal runaway behaviors can be more generally tied to aspects of lithium-ion cells such as total stored energy and specific energy. We have found a strong linear correlation between the total enthalpy of the thermal runaway process and the stored energy of the cell, apparently independent of cell size and state of charge. We have also shown that peak heating rates and peak temperatures reached during thermal runaway events are more closely tied to specific energy, increasing exponentially in the case of peak heating rates.

25 ENERGY STORAGE↗

Two-Dimensional Siloxene Nanosheets: Impact of Morphology and Purity on Electrochemistry

Two-dimensional (2D) siloxene (Si 6 O 3 H 6 ) has shown promise as a negative electrode material for Li-ion batteries due to its high gravimetric capacity and superior mechanical properties under (de)lithiation compared to bulk Si. Here, in this work, we prepare purified siloxene nanosheets through the removal of bulk Si contaminants, use ultrasonication to control the lateral size and thickness of the nanosheets, and probe the effects of the resulting morphology and purity on the electrochemistry. The thin siloxene nanosheets formed after 4 h of ultrasonication deliver an average capacity of 810 mA h/g under a 1000 mA/g rate over 200 cycles with a capacity retention of 76%. Interestingly, the purified siloxene shows lower initial capacity but superior capacity retention over extended cycling. The 2D morphology benefit is illustrated where the parent siloxene nanosheet morphology and structure were largely maintained based on operando optoelectrochemistry, in situ Raman, ex situ scanning electron microscopy, and ex situ transmission electron microscopy. Furthermore, the purified siloxene-based electrode free from crystalline Si impurity experiences the least expansion upon (de)lithiation as visualized by cross-section electron microscopy of samples recovered post-cycling.

25 ENERGY STORAGE↗

Effects of friction stir processing and minor Sc addition on the microstructure, mechanical properties, and damping capacity of 7055 Al alloy

Highlights: • Good mechanical and damping properties were obtained in the 7055 after FSP and Sc addition. • The strengthening and damping mechanisms of FSP 7055(-Sc) were analyzed. • FSP and Sc addition were found to be strategy of preparing 7xxx alloys with well damping and mechanical properties. - Abstract: This study investigated the effects of friction stir processing (FSP) and addition of 0.25% (mass ratio) Sc on the microstructure, mechanical properties, and damping capacity of AA 7055 alloy. Microstructure analyses revealed that a low tool rotation rate of 300 rpm effectively inhibited the grain coarsening in the recrystallization of the alloy during FSP. Sc addition prevented the coarsening of grains and precipitated η phase and the annihilation of dislocations in the FSP AA 7055 alloy. After being subjected to FSP at 300 rpm, the AA 7055 alloy containing Sc exhibited good mechanical and damping properties, which were mainly attributed to the fine recrystallized grain structure, fine precipitated η phase, and large number of nano-sized Al{sub 3}(Sc, Zr) particles located at the grain boundaries and dislocations. This work provides an effective strategy for preparing commercial Al alloys with excellent damping capacity and mechanical properties.

36 MATERIALS SCIENCE↗

Wettability variation and its impact on CO 2 storage capacity at the Wyoming CarbonSAFE storage hub: An experimental approach

Meeting global and national net zero carbon emission targets will require geologic carbon disposal. The U.S. Department of Energy (DOE) has accordingly funded significant research in this area, including the Wyoming CarbonSAFE project at Dry Fork Station (DFS) in Campbell County, Wyoming. This work studied wettability on micro- and macro-scales, CO 2 storage potential, and the correlation between the two to support the Wyoming CarbonSAFE project’s subsurface assessment. During the study, a target formation’s wettability was found to affect how much CO 2 can be stored in a given formation. Here, in this study, representative rock samples were selected from the target storage formations— Lakota, Hulett, and Minnelusa—based on the heterogeneity of the lithology, permeability, and porosity of the respective formations. The rock samples are all fine-grained sandstone with variable cementation and bedding structure, including different scales of laminated bedding. The porosity and permeability vary within the range of 9.0–14.3% and 0.1–28.9 mD, respectively. These rock samples were prepared for the micro-scale wettability (contact angle measurement), macro-scale wettability (wettability index derived from unsteady-state flow characterization for the core plugs), and CO 2 storage evaluation. The macro-scale experiments suggested that wettability appeared to dominate the CO 2 storage potential performance during the drainage process, where less water-wet behavior promoted higher CO 2 storage potential. The micro-scale wettability tests showed that the rock samples at the studied reservoir conditions behaved water-wet and became more water-wet as pressure increased. This kind of wettability change discourages further CO 2 storage potential yet benefits the CO 2 residual trapping as the CO 2 injection proceeds for the studied area. The results allow the recommendation of the best reservoir candidate for storage based on wettability that affects CO 2 storage. The work presented in this study provides valuable insights into wettability’s effect on the CO 2 storage capacity and wettability’s importance when identifying the optimal CO 2 storage formation to meet the project’s goals.

58 GEOSCIENCES↗

Ultrastable Zirconium-Based Cationic Metal–Organic Frameworks for Perrhenate Removal from Wastewater

The effective removal of radioactive 99 TcO 4 – anion from nuclear wastewater remains a very difficult unsolved problem. Functional adsorbent materials with high stability, anion-exchange capacity, excellent selectivity, and recyclability are much needed to solve this problem. In this work, we designed two stable cationic metal–organic frameworks (MOFs)—Zr-tcbp-Me and Zr-tcpp-Me—for possible use as adsorbent materials to remove 99 TcO 4 – . Both compounds were synthesized by solvothermal reactions of the tetracarboxylate ligand with zirconium salt, followed by postsynthetic modification (N-methylation). Here, the crystallinity of both zirconium-based MOFs can be well retained under harsh conditions, and they exhibit high adsorption capacity and selectivity toward ReO 4 – anion, a nonradioactive analogue of 99 TcO 4 – . Zr-tcbp-Me and Zr-tcpp-Me demonstrate the highest framework stability toward acidity among all previously reported cationic MOFs that have been tested for perrhenate removal from wastewater.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Elucidating the Limit of Li Insertion into the Spinel Li 4 Ti 5 O 12

Here in this work, we show that the well-known lithium-ion anode material, Li 4 Ti 5 O 12 , exhibits exceptionally high initial capacity of 310 mAh g –1 when it is discharged to 0.01 V. It maintains a reversible capacity of 230 mAh g –1 , far exceeding the “theoretical” capacity of 175 mAh g –1 when this anode is lithiated to the composition Li 7 Ti 5 O 12 . Neutron diffraction analyses identify that additional Li reversibly enters into the Li 7 Ti 5 O 12 to form Li 8 Ti 5 O 12 . density functional theory (DFT) calculations reveal the average potentials of the Li 4 Ti 5 O 12 to Li 7 Ti 5 O 12 step and the Li 7 Ti 5 O 12 to Li 8 Ti 5 O 12 step are 1.57 and 0.19 V, respectively, which are in excellent agreement with experimental results. Transmission electron microscopy (TEM) studies confirm that the irreversible capacity of Li 4 Ti 5 O 12 during its first cycle originates from the formation of a solid electrolyte interface (SEI) layer. This work clarifies the fundamental lithiation mechanism of the Li 4 Ti 5 O 12 , when lithiated to 0.01 V vs L

25 ENERGY STORAGE↗