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At least 487 records · Page 27

Carbon dioxide pipeline network transportation cost model: evaluating economic and geographic factors for efficient carbon capture, storage, and utilization

This study presents a comprehensive pipeline network modeling framework to estimate the CO 2 delivery cost for CO 2 utilization and geologic CO 2 storage across the United States. We developed a Python-based CO 2 pipeline transportation cost model leveraging Argonne National Laboratory’s pipeline engineering expertise and detailed natural gas transmission pipeline cost data across U.S. regions. Using existing road corridors as practical routing guides, the model designs pipeline networks that aggregate CO 2 from one or multiple sources and deliver it to selected destinations. It then minimizes the total transportation cost by optimizing pipeline diameters and incorporating booster pumps. A key contribution is the incorporation of up-to-date, region-specific cost factors with itemized components for materials, labor, miscellaneous construction expenses, and right-of-way acquisition. Results emphasize that regional variation and economies of scale associated with CO 2 pipeline costs are significant and should be explicitly accounted for in screening and planning studies. By combining realistic routing constraints with regionalized cost inputs, the model provides transparent design methodology and location-specific insights into source–destination delivery costs, including the effects of routing complexity along existing road networks. We demonstrate the model with two illustrative case studies – one for CO 2 storage and one for CO 2 utilization – in which the model designs pipeline networks spanning hundreds of miles across the states, collecting CO 2 from multiple sources and delivering it to designated endpoints while minimizing levelized cost of delivery via diameter and compression optimization. The model offers a practical, scalable approach for alternative design option screening and early-stage CO 2 transportation planning.

CCS↗

Application of Modified Meshgraphnets for Subsurface Prediction during CO2 Sequestration

In the face of the increasingly dire consequences of anthropogenic climate change, capturing and storing carbon dioxide is paramount. However, several impediments exist to the safe and effective subsurface storage of CO2, such as cost of transport, identification of suitable sites for subsurface storage, and assessment of long-term risk from storage in subsurface aquifers. Accurate subsurface modeling is necessary to ensure that CO2 storage is both safe and effective. Still, such modeling has traditionally required either substantial time and computational power (numerical simulation) or a substantial amount of pre-existing data for training (machine learning models). Additionally, these models lack flexibility in dealing with both changes in discretization of the input data and generalizability beyond the data on which they are trained. In order to address these issues, this research applies graph neural networks (GNNs) to predict subsurface saturation and pressure during CO₂ injection in a model of the Illinois Basin-Decatur Project (IBDP). GNNs provide a flexible, intuitive method for representing and manipulating complex unstructured data, which is often found in many practical domain problems such as fluid flow and subsurface characterization. These unstructured grids are easily represented in GNNs by representing spatially-localized features such as permeability, porosity, saturation, and pressure as nodes in a graph and relationships between these properties as edges connecting these nodes. This research applies a specific GNN model called MeshGraphNets (MGN) to model the change in CO2 saturation and pressure over a 50-month time period (36 months of injection, 14 months post-injection). The MGN model leverages a message passing process that allows the network to learn both the spatial and temporal dynamics of this system simultaneously. Additionally, training on a limited dataset (64 realizations, 20 time points each) resulted in a high degree of accuracy in saturation prediction both within the same timeframe as the training (20 months, 0.039 average RMSE) and when projecting out to the end of injection (36 months, 0.053 average RMSE). Temporal predictions such as those generated by MGNs and other similar models are prone to accumulated error over time; in order to address this, a multi-step rollout (MSR) training process was applied to calculate training loss. This method mimics the forward prediction during inference by “rolling out” multiple time points in a single training step using the previous prediction as input to the MGN model. By calculating the loss several time steps forward from the current prediction, the model is forced to find a more stable state over time. Application of MSR to the MGN model resulted in an average 15% reduction in inference error over time during forward prediction. This study showcases the immense potential of GNNs as a game-changing methodology for predicting pressure and saturation evolution in CCS projects, ultimately paving the way for more sustainable and effective carbon storage solutions. Presentation prepared for the 2024 AiChE Annual Meeting, October 27 to November 1 2024, San Diego, CA.

Holcomb, Paul↗

Optimal Linear Water Density for Proton Transport in Tunnel Oxides

Proton intercalation and transport is key to pseudocapacitive energy storage of oxide electrodes in acidic electrolytes. Although proton transport in water confined in layered or 2D materials is attracting great interest, much less is known about how the proton is transported in the 1D channels of tunnel oxides such as hexagonal WO 3 (h-WO 3 ). Here, we use first-principles molecular dynamics to reveal an optimal linear density of four water molecules per nanometer that yields the highest proton diffusivity. The volcano shape of proton diffusivity versus linear water density is a result of balancing the linear hydrogen-bond chain and the rotation of the water molecules to enable the Grotthuss mechanism. Furthermore, this insight provides a unifying view of proton transport along a single file of water molecules confined in hydrophilic 1D channels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Concerted Electron-Ion Transport by Polyacrylonitrile Elucidated with Reactive Deep Learning Potentials

Charge transport in polymers, such as polyacrylonitrile (PAN), is crucial for electronics and energy storage. For instance, PAN can transport cations e.g., Li + , by facilitating dynamic cation-nitrile coordination in batteries. However, little is known regarding the underlying role of complex reactive polymer configurations. Herein, we develop a deep-learning potential, trained on ab initio energies and forces of nonequilibrium reactive PAN configurations, to unravel the kinetics of PAN cyclization initiated by a nucleophile (OH – dissociated from LiOH) attacking the terminal nitrile carbon. We find, based on the reaction free-energetics, rates, and charge analysis, that the nucleophile attack producing the first ring is the rate-limiting step, which subsequently triggers Li + -coupled electron transfer along the PAN backbone, causing ∼10 4 times faster sequential ring-formation of the remaining nitriles. PAN’s extended configurations, where dipolar and H-bonding interactions are minimal, enable such rapid kinetics. By validating our computational findings with IR and NMR experiments, we establish a pathway for designing reactive polymers with enhanced charge transport for energy applications.

Chahal-Crockett, Rajni [Oak Ridge National Laborat↗

Emergent Nanostructure and Ion Transport in Polyzwitterion/Polyanion Blends

Solid polymer electrolytes (SPEs) hold great promise for the advancement of next-generation energy storage devices. However, the ion transport mechanism in SPEs remains poorly understood. In this study, we investigate blends of poly(1-(3-sulfonatopropyl)-2-vinylpyridinium) (P2VPPS) and poly(lithium (trifluoromethane)sulfonimide methacrylate) (P(MTFSI)Li) of varying molar ratios to develop a mechanistic understanding of ionic conductivity in a miscible polyzwitterion/polyanion system. Polyanions can act as single-ion conductors, but conductivity is often prohibitively low due to the decreased segmental mobility and ion aggregation. Here, it is hypothesized that the introduction of a polyzwitterion would competitively interact with the polyanion charge groups to realize improvements in the conductivity. Attractive interactions between the polyanions and polyzwitterions are confirmed by the blend’s increased glass transition temperature using the Gordon–Taylor equation. Notably, an ordered local nanostructure (∼24 Å) emerged in the P2VPPS/P(MTFSI)Li system at certain compositions, as characterized by small-angle X-ray and neutron scattering (SAXS/SANS). Concurrent with the emergence of this structure, broadband dielectric spectroscopy confirmed improvements in ionic conductivity. The highest conductivity is observed at a specific blend ratio P2VPPS:P(MTFSI)Li = 0.2:1 in the glassy state and 0.3:1 in the rubbery state, corresponding to the lowest effective activation energy (E*). Coarse-grained molecular dynamics simulations further emphasize the role of complexation between polyzwitterion and polyanion chains, correlating with the emergence of a new peak in SAXS and SANS for the blends. This work provides a fresh perspective on the role of local structural design in developing SPEs and offers insights into the morphological effects on ionic conductivity.

chemical structure↗

A Versatile Remediation Module for Remote Repair of Spent Nuclear Fuel and High-Level Waste Storage Containers

Oak Ridge National Laboratory (ORNL) successfully demonstrated the Versatile Remediation Module (VRM), a prototype module designed and built by ORNL for on-site remote repair of welded stainless steel storage containers for spent nuclear fuel and high-level radioactive waste. This paper describes the VRM prototype and its design features and components to support continued long-term storage or off-site transportation of spent nuclear fuel and high-level radioactive waste currently stored in storage containers. A remote (100 ft away from the simulated radiative environment) demonstration of the VRM was successfully performed on a full-scale mock-up welded stainless steel canister. The VRM is designed with features to accommodate remediation techniques beyond those currently selected and described in this paper. Therefore, many of the VRM’s features may benefit other remote nuclear or nonnuclear applications. The VRM is envisioned to serve as a development center to facilitate and enhance further development of new remediation technologies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Versatile Remediation Module Final Operational Testing Results

Oak Ridge National Laboratory (ORNL) successfully demonstrated the Versatile Remediation Module (VRM), a prototype module designed and built by ORNL for performing the on-site remote repair of welded stainless-steel storage containers for spent nuclear fuel and high-level radioactive waste. This report describes the VRM prototype and its design features, components, qualification tests, operational procedures, and demonstration results to support continued long-term storage or off-site transportation of spent nuclear fuel and high-level radioactive waste currently stored in storage containers. A remote (i.e., 100 ft away from the simulated radiative environment) demonstration of the VRM was successfully performed on a full-scale mock-up welded stainless-steel canister. The VRM is designed with features to accommodate remediation techniques beyond those currently selected and described in this report. Therefore, many of the VRM’s features could benefit other remote nuclear or nonnuclear applications. The VRM is envisioned to serve as a development center to facilitate and enhance the further development of new remediation technologies.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Establishing the Stability of Cross-Linked Poly(ethylene oxide) Blended with Poly(pentyl malonate) against Lithium Metal Anodes

This work focuses on an electrolyte obtained by infusing linear poly(pentyl malonate) (PPM) chains into cross-linked poly(ethylene oxide) (PEO). A lithium salt is added to enable ion transport. Obtaining this electrolyte is only possible because PPM is miscible with PEO irrespective of salt concentration. The properties of this electrolyte are compared against two benchmarks: an electrolyte obtained by infusing linear PEO into cross-linked PEO and cross-linked PEO with no added linear polymer. Measurements of storage moduli and ion transport efficacies are found to be similar across the three electrolytes, suggesting similar stability behavior against lithium metal anodes, based on current theoretical models. Instead, the PPM infused electrolyte outperforms the other two electrolytes. In the cycling tests, the current supported by the PPM infused electrolyte was a factor of 20 higher than that of the PEO infused electrolyte and a factor of 4 higher than that of the cross-linked PEO electrolyte. In the unidirectional plating experiments, the other two electrolytes fail after about 4 h or less, while the PPM containing electrolyte did not fail during the 140 h testing period. Insight into the nature of failure modes was obtained using synchrotron hard X-ray microtomography.

Gido, Lily [University of California, Berkeley]↗

SISGR: Chemomechanics of Far-From-Equilibrium Interfaces (COFFEI)

Portable, reliable, and deployable devices for energy storage and conversion require fundamental changes in design of solid-state composites comprising ceramics and metals. These materials comprise the electrodes and electrolytes of next-generation solid-oxide fuel cells and all solid-state batteries, forming solid-state functional composites. The advent of solid-state batteries – which replace liquid electrolytes with solid electrolytes capable of lithium ion transport for reliable energy storage in portable batteries – and the increased demand space for all solid-state fuel cells capable of oxygen reduction at intermediate temperatures remain important challenges for improved material stability and decreased system cost. However, little is understood about three fundamental facets of materials that enable such solid-state energy applications. First, how do such materials deform, fracture, or delaminate under operando conditions? Second, how does such mechanical deformation limit or facilitate electronic and ionic transport within and across such material interfaces? Third, how we can predictably design interface-rich composites to engineer both structural and electrochemical stability? This COFFEI Group comprised expertise from Materials Science & Engineering and Nuclear Science & Engineering to integrate unique in situ experiments, simulations, and fabricated interfaces that address these fundamental questions in solid-state interfaces of nanoscale composites that will guide solid-state electrochemistry, transport kinetics, and mechanical deformation for nonstoichiometric materials that enable such applications. In particular, we built on COFFEI’s understanding of chemomechanical coupling among defect concentrations, ionic transport, electron transport, and stored elastic energy that is particularly acute in the far-from-equilibrium conditions typical of energy device applications. By tailoring our focus to solid-state interfaces, we addressed these important issues by (a) developing and applying advanced in situ and ex situ characterization tools to characterize model materials and interfaces synthesized with molecular-level control, under both laboratory-controlled and extreme environments representative of energy device operation; and (b) employing computational modeling and simulation frameworks to predict transport mechanisms, reactivity and stability of these model materials and interfaces under significant chemical strains typical of energy device operation. Recent progress provided insights to additional materials systems and electrochemomechanical fatigue and fracture that were not fully envisioned when the program was initiated. Specifically, in the final three years of COFFEI we pursued two integrated thrusts, with complementary focus. Thrust I focused on failure-resistant electrochemomechanical composites, while Thrust II focused on strain-modulated conductivity and reactivity across interfaces. In contrast to our initial COFFEI focus, these thrusts concentrated wholly on solid-state material interfacial interactions and included greater integration of multiscale visualization including in situ electron microscopy of strained structures/interactions and mesoscale simulations. Successful development of functionally superior and long-lived battery and fuel cell systems and stress adaptable oxides requires a deeper, fundamental understanding of the coupling among the historically important subfields of solid-state electrochemistry, transport kinetics, and mechanical deformation for nonstoichiometric metal oxide electrodes. In this program, the understanding and the application of chemomechanical coupling of defect concentrations, ionic transport, electro-catalytic activity and stored elastic energy, particularly acute in the far-from-equilibrium conditions typical of energy device applications, are being refined and implications for device operation clarified, including for miniaturized solid-state batteries and fuel cells.

36 MATERIALS SCIENCE↗

Design Basis Document / Owner’s Technical Specification for Nitrate Salt Systems in CSP Projects: Hypothesis of Hot Tank Failure

Work has begun on a Design Basis Document / Owner’s Technical Specification for parabolic trough and central receiver power plants using nitrate salt as the heat transport fluid and the thermal storage medium. A principal topic of recent interest is the failures of the hot salt tanks in central receiver projects. The paper outlines a hypothesis for the source of the failures, and discusses a range of possible solutions.

14 SOLAR ENERGY↗

Mechanistic insight into the effects of A-site doping in perovskite nanorods on interfacial Li-ion and Na-ion transport in polymer–perovskite composite electrolytes

Composite polymer electrolytes (CPEs) offer a promising pathway to safer and higher energy density electrochemical energy storage yet optimizing interfacial ion transport remains a critical challenge due to high resistances and a lack of understanding of the complex interfacial electrostatic interactions. This work investigates the mechanistic origins of the interfacial ion transport enhancement in single-ion conducting (SIC) polymer electrolytes filled with A-site disordered perovskite LaxMyTiOz (LMTO) (M = Li, Na, K) nanorods. By integrating Density Functional Theory (DFT) with broadband dielectric spectroscopy (BDS) and pulsed-field-gradient NMR (PFG-NMR), we analyze the ion transport behavior in Li-based and Na-based SIC systems containing compositionally distinct LMTO fillers (LMTO800 and LMTO900). Specifically, we introduce the site-to-site energy difference (ΔE) descriptor, which extends beyond single-site descriptors such as adsorption energy and ion binding energies. We demonstrate that ΔE together with ion binding energies provide a more comprehensive picture of the energy landscape at the polymer–ceramic interface. The combined DFT and experimental results show that A-site doping in the ceramic filler can effectively modulate ΔE and ion binding energies, creating a favorable potential energy landscape that promotes enhanced ion transport along the interface. This comprehensive study illustrates the impact of ceramic compositional tuning on interfacial ion transport and provides materials design rules towards real-world applications.

B shepard, Lauren [Pennsylvania State University]↗

Microbial carbon use efficiency promotes global soil carbon storage

Soils store more carbon than other terrestrial ecosystems. How soil organic carbon (SOC) forms and persists remains uncertain, which makes it challenging to understand how it will respond to climatic change. It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss. Although microorganisms affect the accumulation and loss of soil organic matter through many pathways, microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes. Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved. Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Polysulfide entrapment and retardation in gel electrolyte Li–S batteries: experiments and modeling

Gelling the electrolyte in lithium–sulfur (Li–S) batteries provides advantages in terms of safety and mitigating polysulfide shuttling leading to reduced side reactions and dendrite growth on the anode side. In the current study, organic and ceramic crosslinkers have been used to improve the entrapment of polysulfides and prevent them from shuttling to the anode side. However, the performance of gel electrolytes is still far from being on par with liquid electrolytes in terms of raw capacity. The discharge curves exhibit an extended first plateau for gel electrolyte batteries compared to liquid electrolytes, showing that polysulfides are better trapped in the gel system. Yet, in the conversion of soluble polysulfides into insoluble polysulfides, the second plateau was delayed. Qualitative and quantitative analysis of the polysulfide diffusion in the liquid electrolyte and gel electrolyte systems were also conducted to predict the relative diffusivity ratio between the liquid electrolyte and gel electrolyte for simulation. To probe what happens at the end of the discharge, where the mass transport in the gel electrolyte appears to be slow, a modified discharge procedure was used where the cell is first paused after discharge and then discharged a second time before recharging normally. Coin cell tests for two gel electrolytes in addition to liquid electrolyte show up to 7% capacity recovery after the pause, which indicates that the diffusion of species during the pause is responsible for the failure recovery. Additionally, the recovery is higher for gel electrolytes compared to liquid, for higher C-rates, and for longer pause times. To better understand this behavior, a Li–S numerical model with mass transport limited reactions was used to examine the polysulfide diffusion coefficients expected in different electrolyte systems. The model is able to reproduce the trends seen in experiments and yields a higher recovery for smaller Li 2 S 4 diffusion coefficients, suggesting that insufficient Li 2 S 4 mass transport is responsible for failure at the end of discharge. By identifying the effect that gel electrolytes have on the state of the battery during discharge using both experimental and simulation methods, this work is a step towards leveraging the advantages of gel electrolytes and mitigating their weaknesses.

25 ENERGY STORAGE↗

Towards fast-charging high-energy lithium-ion batteries: From nano- to micro-structuring perspectives

Electric vehicles (EVs) have been playing an indispensable role in reducing greenhouse gas emissions for our modern society. However, current EVs are difficult to meet people’s diverse travel needs, especially in long endurance and fast-charging capacities. At the heart of this issue is the physicochemical limit of current lithium-ion batteries (LIBs), which are the core parts for powering the vehicles. Hence, LIBs with simultaneous high energy and power are critically required to further promote the development of EVs. Here, in this review, we first summarize the key electrochemical processes in electrochemical reactions which lead to the corresponding overpotentials in or between multiple battery components. Furthermore, numerical simulations are employed to quantitatively analyze the effects of versatile electrode parameters on electrochemical properties in high-energy NMC811//graphite systems. On the basis of the in-depth understandings from simulation, recent experimental efforts on designing electroactive materials and electrode architectures across multiple length scales are discussed. Among them, nano-structuring can promote local mass transport and stabilize the interfaces at the particle level, while micro-structuring can establish efficient pathways for charge carriers at the electrode level. Finally, we conclude that a tight feedback loop among structure engineering, characterization and simulation should be followed to speed up the understanding of the deficiencies existing in current electrode designs as well as point out the possible electrode optimization routes for next-generation fast-charging LIBs.

25 ENERGY STORAGE↗

Unraveling the Effects of Hierarchical Bimodal Microscale Porosity on Thick Electrodes

The thick electrode design is preferential in high-energy lithium-ion batteries (LIBs) systems. However, the sluggish ionic transport in homogeneous porous thick electrodes severely limits the areal capacity at high charging/discharging rates. The hierarchical porous design is a promising approach to mitigate kinetic limitations because it can distribute mass effectively in natural systems. In this study, the effects of bimodal microscale pores are fully investigated in thick electrodes from both architectural and electrochemical perspectives. Notably, by introduction of the bimodal microscale porous structure, the rate capability improves remarkably in thick electrodes with a low porosity (39%). Herein, by combining experimental results with simulations, this work presents a rational design guideline for preparing thick electrodes with a porosity at the commercial level, as well as simultaneous high energy and power densities, which brings new insights into the advanced electrode architecture design in scalable high-energy and high-power energy storage systems for practical applications.

25 ENERGY STORAGE↗

Deciphering the Conflict Between Ion and Electron Percolating Networks in Solid-State Battery Cathodes

High-energy- and power-density solid state batteries require an optimal cathode composition and microstructural arrangement of cathode active material, solid-state electrolyte, conductive carbon, and binder to simultaneously support lithium-ion transport, electron conduction, and storage capacity. The ion and electron conducting phases in solid-state cathodes counteract each other's percolating networks as their mass ratios increase or decrease relative to each other. Here, we investigate targeted mass ratio variations of argyrodite solid electrolyte and two different types of conductive carbon (particles and fibers) in composite LiNi0.8Mn0.1Co0.1O2 (NMC811) solid-state cathodes to ascertain the ionic-electronic tradeoffs in cathode performance. Through ionic and electronic conductivity measurements on composite cathodes, as well as rate-testing and cycling performance in full cells, it is shown that the conductive carbon fibers form a percolative electronic network within the composite at a lower mass ratio (3-5 wt%) than particulate carbon (>5 wt%). The threshold to achieve electronic percolation coincides with higher accessible capacity in the cathode as the active material particles become electronically connected. However, carbon loadings beyond this percolation threshold lead to increased ion transport resistance, arising from disruptions to ionic conduction pathways and degraded contact at the interface between the electrolyte and active materials. Imaging, spectroscopy, and physics-based models quantitatively describe the relationship between carbon and electrolyte compositions and the cell's capacity and rate performance through percolation theory. This work demonstrates the importance of quantitatively understanding percolating networks in solid-state cells and that strategic engineering of conductive carbon morphologies can further increase the energy- and power-density of solid-state cells.

25 ENERGY STORAGE↗