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At least 163 records · Page 9

Techno-Economic and life cycle assessment of standalone Single-Stream material recovery facilities in the United states

Material Recovery Facilities (MRFs) are crucial players in achieving a circular economy. MRFs receive complex waste streams and separate valuable recyclables from these mixtures. This study conducts techno-economic analysis (TEA) to estimate the net present value (NPV) and life cycle assessment (LCA) to estimate different environmental impacts of a commercial scale standalone, single-stream MRF to assess the economic feasibility and environmental impacts of recovering valuable recyclables from an MRF processing 120,000 tonnes per year (t/y). The TEA employs a discounted cash flow rate of return (DCFROR) analysis over a 20-year facility lifetime, along with a sensitivity analysis on the impact of different operating and economic parameters. Results show that the total fixed cost of building the MRF facility is $\$ $23 MM, and the operating cost is $\$ $45.48/tonne. Further the NPV of the MRF can vary from $\$ $3.57 MM to $\$ $60 MM, while 100-year global warming potential can range from 5.98 to 8.53 kg carbon dioxide equivalents (CO2-eq) per tonne of MSW. We have also found that MSW composition (arising from regional effects) significantly impacts costs, 100-year global warming potential, and other impact categories such as acidification potential, eutrophication potential, ecotoxicity, ozone depletion, photochemical oxidation, carcinogenic effects, and non-carcinogenic effects. Sensitivity and uncertainty analysis indicate that waste composition and market prices significantly impact the profitability of the MRF, and the waste composition mostly impacts global warming potential. Our analysis also indicates that facility capacity, fixed capital cost, and waste tipping fees are vital parameters that affect the economic viability of MRF operations.

36 MATERIALS SCIENCE↗

Analysis of Material Properties of Aged Rigid Polyurethane Foam

Foams are classified as either rigid or flexible and are commonly used in applications such as pipe insulation, carpet fibers, and chair foam cushions. Polyurethane foams are excellent thermal insulators, have excellent mechanical properties, and are chemically inert. With the addition of fire protective additives, polyurethane foams have the ability to intumescence when exposed to high temperatures. For the future storage of the 9977 nuclear shipping packages, the material properties of the General Plastics 3716 rigid polyurethane foam were evaluated for long term performance by comparing aged samples to unaged samples. General Plastics 3716 rigid polyurethane foam was aged from November 2014 to June 2019 at varying temperatures of: 160 deg. F, 160 deg. F + 50% relative humidity (RH), 185 deg. F, 215 deg. F, and 250 deg. F. The foam was then analyzed via Fourier Transform Infrared Spectroscopy (FTIR), 3D Optical Microscope, Thermal Gravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC). FTIR and Optical Microscope: No significant change to chemical or physical structure was evident by FTIR or optical microscope analysis. DSC: Decrease of heat capacity over time for all oven temperatures except a slight increase for the 185 deg. F conditioned foams. Largest decrease evident with foams conditioned at 250 deg. F. A slight increase in heat capacity for humid samples. Similar trends in heat capacities at 71 deg. C and 102 deg. C. TGA: As conditioning temperature increased, a decline was evident in the average percent weight loss, onset temperature, and first derivative peak temperature. No significant effect due to humidity except for a decrease in first derivative peak temperature. Unaged samples exhibited strong intumescence. Foams conditioned at 160 deg. F exhibited slight intumescence. Results suggest fire protective additives decomposed at higher temperatures, which contributed to a lower average percent mass loss in higher temperature conditioning. Further thermal degradation testing would be beneficial to evaluate the ability of the conditioned foams to intumesce. Evaluate irradiation dose rate effects on conditioned foam. Possible conditioning in an environment with a known humidity or analyzing a new aliquot of sample for each trial to achieve a more representative heat capacity calculation.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Tuscaloosa Marine Shale: Seal or Source? Petrophysical Comparative Study of Wells in SE Louisiana and SW Mississippi

The Tuscaloosa Marine Shale (TMS) is a versatile Late Cretaceous shale formation present in central and SE Louisiana and SW Mississippi, which drew attention because of the various roles played within the Tuscaloosa Group. In this paper, it is debated whether the Tuscaloosa Marine Shale can act as a source, reservoir, or seal all throughout the shale play or only in certain areas. Well log and core data from Adams County, Mississippi, are compared to data from East Feliciana Parish in Louisiana. Conclusions were drawn based on the results of well log analysis, X-ray Diffraction (XRD), porosity–permeability measurements, programmed pyrolysis, and fracture analysis. It was shown that the Tuscaloosa Marine Shale interval in SE Louisiana consists of important amounts of calcite, exhibits multiple natural fractures, has porosity values as high as 9.3%, and shows a TOC content of up to 2.8 wt%. On the other hand, samples from a well at the Cranfield field, MS, are characterized by considerably lower TOC values of around 0.88 wt%, porosities between 0.33% and 4%, and no serious fracturing. The formation demonstrates better reservoir and source potential in SE Louisiana and reliable CO2 sealing capacity in SW Mississippi. The analysis presented in this paper represents a holistic approach to the characterization of shale formations, is applicable to other plays around the world, and can be used as an integral part of CO2 sequestration or hydraulic fracturing programs.

04 OIL SHALES AND TAR SANDS↗

Emerging concepts in intermediate carbon dioxide emplacement to support carbon dioxide removal

Substantial upscaling of carbon dioxide capture is possible in the coming decades but existing solutions for storage are projected to be limited in annual capacity by as much as 2–10 GtCO 2 per year until mid-century. Temporary storage of CO 2 in a solid or liquid state could prove useful for filling this gap in capacity, until more permanent and ideally lucrative CO 2 sequestration options come online. There are several concepts for reversible solid-state and chemical CO 2 storage, but their advantages and limitations have yet to be reviewed in this context. This article focuses on the physical and chemical aspects of CO 2 storage via liquid and solid chemical carriers and sorbents, and gives an overview of the energetics around their use, as well as prospects for their future development. Exciting opportunities for coupling capture and medium to high maturity multi-year storage technologies could support carbon removal in the coming decades. Highlights of the analysis are the remarkable storage capacity of oxalic acid and formic acid (CO 2 -density of 1857 kg m –3 and 1152 kg m –3 , compared with condensed liquid CO 2 at 993–1096 kg m –3 , respectively), the relative scalability and compatibility of carbonate salts for stationary storage with direct air capture, and the potential promise of multiple carriers for CO 2 transportation. Solid sorbents do not achieve such ultra-high storage capacities, but could improve storage over compressed gas tanks on a capacity and energetics basis.

54 ENVIRONMENTAL SCIENCES↗

Effect of Storage Conditions on Efficacy of Poly(ethylenimine)-Alumina CO 2 Sorbents

Solid amine sorbents are one of the primary components of DAC technologies that allow for the removal of ultradilute CO 2 from the atmosphere. A main drawback in the implementation of solid amine sorbents in industrial-scale DAC applications is their instability under certain operational or storage conditions over an extended period. In this work, the effect of storage temperature and gas composition in the storage headspace on the long-term stability of a poly(ethylenimine)-alumina (PEI/γ-Al 2 O 3 ) sorbent is explored. PEI/γ-Al 2 O 3 sorbents with 70 and 100% pore filling are aged under varying gases (N 2 , O 2 , Ar, 0.04% CO 2 −N 2 , CO 2 , and ambient air) in an oven (40 °C), at common ambient indoor temperature conditions (23 °C), or in a freezer (−4 °C). The CO 2 sorption capacity, as measured by thermogravimetric analysis (TGA), along with FTIR spectra of the fresh and aged sorbents, reveal that at 23 and −4 °C, storage under ambient air or inert gas (Ar) provides reasonable long-term stability, with <13% degradation over 12 and 5 months of storage. Interestingly, with storage at 40 °C, similar levels of deactivation were observed under pure O 2 and N 2 after 4 months of storage, which suggests that nonoxidative thermal reactions can occur under prolonged storage conditions under N 2 . In contrast, with storage under CO 2 , sorbent degradation is substantially suppressed compared to storage under N 2 , ambient air, O 2 , or Ar, yielding sorbents with no observable loss in capacity after 2 months, compared to a 66, 63, and 62% loss under N 2 , ambient air, and N 2 in the same period at 40 °C, respectively. Overall, these findings provide guidance for practical amine sorbent storage in academic or industrial settings where amine sorbents are used for carbon capture.

Atmospheric chemistry↗

Nuclear Materials Process Modeling at the Y-12 National Security Complex

The Y-12 National Security Complex (Y-12) has implemented process modeling for various accountable nuclear materials operations that are performed throughout the plant. Using a discrete, event-based dynamic simulation program, key nuclear material streams are modeled, allowing Y-12 to effectively manage numerous points of interest within the plant’s production operations. Integration of the various material processes into a single, interdependent supply and demand model is one of the ongoing focuses within Y-12’s process modeling effort. The primary purpose of using dynamic simulation modeling is to allow for analysis of the nuclear materials inventories and forecasted supplies based on future demands. Analysis of these inventories includes capacity evaluation, bottleneck mitigation, and assessments of individual pieces of equipment to inform future facility investment decisions and associated project schedules. Modeling of the nuclear materials processes throughout the complex also allows for incorporation of changes relevant to production capabilities such as the upcoming transition of specific operations to the new Uranium Processing Facility. Prior to implementation of process modeling, Y-12 forecasted supply and demand of accountable nuclear materials streams using Microsoft Excel. With deterministic models such as Microsoft Excel, the annual forecasts, generated within data input condition parameters, can only provide a fixed point of data. Fixed data cannot simulate integrated material streams and account for the possibility of occurrences and other changes that dynamic simulations take into consideration. Y-12’s dynamic process modeling allows integrated simulations of multiple accountable nuclear materials processes, including supply and demand forecasting and analysis, and is a coordinated effort involving many steps of verification and validation (V&V), site briefings, testing, reporting, data mining, planning, and documentation that spans various programs throughout the Y-12 complex.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Development of Control System Functional Capabilities within the IES Plug-and-Play Simulation Environment

The concept of an Integrated Energy System (IES) is meant to combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. The RAVEN-based HYBRID framework is used to find the optimal installed capacity and the optimal economical dispatch of each component of the IES. A new RAVEN (Risk Analysis Virtual ENvironment) plugin for grid and capacity optimization (HERON) has been developed for optimizing the production variables of the IES given the demand profile. Currently, only the limits that affect the production variables and their corresponding time rates of change are considered (explicit constraints). However, other variables are additionally subject to constraints, but the associated limits are not accounted for (implicit constraints). In particular, for the power dispatch problem, the optimization algorithm takes into account the limits on the electrical power output and the corresponding hourly power variations but does not consider other constraints on process variables whose response effects the service life of the IES. This report describes a scheme that allows accounting for implicit constraints without increasing the size of the optimization problem. The Reference Governor (RG) algorithm is traditionally used for enforcing state and control constraints by modifying the set-point trajectories supplied to the feedback regulators. In our application, the RG is coupled within an iterative loop with the HERON-power dispatcher to generate optimal trajectories that ensure the operational constraints are met. A data-driven procedure to derive a representation of the dynamics of the controlled system was developed. First, the variables that represented the state of the system are selected (PCA-based approach), and then state-space representation matrices are derived from the collected measurements (DMDc algorithm). A preliminary version of the developed workflow based on Linear Time Invariant matrices was assessed by adopting a two-unit test case. More sophisticated versions of this workflow foreseeing the on-line derivation of system matrices will be deployed in FY 2021. Finally, a “plug-and-play” library of controllers and state observers was developed in Dymola. Some aspects of the current configuration of the IES unit components, e.g., the encapsulation of the control schemes into dedicated blocks, are consistent with the “plug-and-play” philosophy. Other features, e.g., the system buses collecting the input and the output variables, are not. For this reason, once listed and described the limits of the current configuration, necessary modifications to the plant model interface are presented. As a test-case, the interfaces of the SES model in the RAVEN-based HYBRID framework were reworked accordingly, and two different control schemes were applied to the same plant model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Providencia Island High-Level Power System Capacity Expansion Analyses [Slides]

Results of a high level cost-benefit analysis using HOMER Pro software are presented for Providencia Island, Colombia. The analysis focuses on integrating solar photovoltaics (PV) and a battery energy storage system (BESS) into an existing diesel-only remote power system. The analysis uses fuel costs and discount rates provided by the stakeholders and NREL-derived capital cost estimates.

14 SOLAR ENERGY↗

A Technical and Economic Assessment of LWR Flexible Operation for Generation and Demand Balancing to Optimize Plant Revenue

With increased penetration of subsidized variable renewable energy (VRE) resources and competition from low natural gas prices, existing light water reactor (LWR) nuclear power plants (NPPs) are struggling to remain economically competitive. This work examines the potential economic competitiveness of various thermal energy storage (TES) technologies when coupled directly or indirectly with a NPP. To highlight their relative economic competitiveness, we contrast several energy storage solutions in stochastic dispatch optimization. We leverage data from recent work analyzing a range of TES technologies with varying capital costs, performance, and technology readiness level (TRL) to establish our case. We explore inserting these technologies into an electricity market with existing nuclear generation and large projected variable renewable energy (VRE) penetration. Although these technologies' projected capital costs may make them unlikely candidates in their current state, this analysis demonstrates a high-fidelity techno-economic analysis of energy storage. Furthermore, as the projected cost of energy storage technologies evolves, this analysis sets a precedent for similar future investigations. One region with projected trends that may be unfavorable for existing nuclear capacity is the New York Independent System Operator (NYISO) market. New York state’s baseload generation has been historically provided by fossil-fired and nuclear assets. However, amid economic pressures from subsidized VREs and low natural gas prices, the state has recently deactivated Indian Point nuclear power plant units 2 and 3. Furthermore, the state plans to meet its zero-emission generation target by 2040 by replacing fossil-fired capacity with significant investments in VRE resources like wind and solar photovoltaic (PV) and battery storage. Increased intermittent resource penetration lowers the baseload power requirement, adding further economic pressure to the state’s three remaining NPPs still in operation. With three NPPs still in operation in New York, this work analyzes potential economic benefits to NPPs on the New York grid when directly or indirectly coupled with various TES technologies. This work requires two modeling steps to analyze the potential economic benefits of various system configurations of the TES directly or indirectly coupled with nuclear. First, this analysis leverages capacity expansion modeling by experts at the Electric Power Research Institute (EPRI). Using their deterministic capacity expansion model, U.S. Regional Economy, Greenhouse Gas, and Energy (US-REGEN), EPRI analysts evaluated the capacity and generation evolution of the New York state energy market under four projection scenarios. These four projection scenarios were developed to represent the potential evolution of the capacity and generation in NYISO from 2015 to 2050 under various economic, technology, and policy constraints. The results from these capacity expansion models are then used as boundary conditions in the second modeling step. The second modeling step uses the Holistic Energy Resource Optimization Network (HERON) for a set of stochastic techno-economic analyses (STEAs) to investigate the potential increase in the economic viability of various configurations of the TES. With no current capacity expansion capabilities, HERON takes the data generated from US-REGEN for 2050 to generate synthetic load, solar, and wind data. Then HERON economically optimizes the capacity and dispatch of the various TES configurations. The potential economic benefit is the differential net present value (NPV) of the TES configurations from the no-TES baseline. As a stochastic techno-economic analysis package, HERON introduces uncertainty into the economic metrics, while US-REGEN trades resolution for reduced computational complexity. Using HERON also allows the modeling of direct thermal coupling, a feature not common in capacity and dispatch models. As expected, with high capital costs, the costs of introducing energy storage for all the technologies considered outweighed the potential economic benefit of this strategy for flexible plant operation. The benefit of this analysis is primarily in demonstrating a workflow that examines innovative solutions to increase NPP revenue via TES coupling. HERON’s stochastic capacity and dispatch optimization process used in this work has proven an effective tool in observing and evaluating the impact of introducing storage technologies in a grid energy system.

25 ENERGY STORAGE↗

Electroprecipitation Mechanism Enabling Silica and Hardness Removal through Aluminum-Based Electrocoagulation

We evaluate the effectiveness of an aluminum-based electrocoagulation pretreatment system to remove dissolved silica and hardness. Silica and hardness limit water recovery during membrane-based desalination applications when silica and hardness exceed the solubility limit and generate scale on the membrane surface. We show that simultaneous removal of nearly all silica (95 ± 4%) and a significant amount of hardness (40–60%) occurs with a hydraulic residence time of 2 h and a charge loading between 0 and 1200 C/L. Increasing the residence time maximized the hardness removal (58 ± 8%) via the formation of larger flocs, which allowed for more constituent removal by gravity settling. We highlight the trade-offs between improved energy efficiency at lower charge loadings and an improved removal rate at a higher charge loading. We further compare the percentage of silica and hardness removed in multicomponent solutions and compare this to single component feed solution. We discuss the implications that operational considerations have in terms of cost and treatment capacity. Finally, a cost–benefit analysis comparing chemical coagulation with electrocoagulation indicates that electrocoagulation could be half the cost of chemical coagulation and could produce more stable effluent pH and conductivity.

36 MATERIALS SCIENCE↗

Water-stable direct air capture of CO 2 with microcapsules of task-specific ionic liquid and their electrothermal regeneration

Microcapsules of the task specific ionic liquid (TSIL) 1-ethyl-3-methylimidazolium 2-cyanopyrrolide [EMIM][2CNpyr] with composite polydimethylsiloxane (PDMS) shells were fabricated for use in CO 2 direct air capture (DAC) conditions. The TSIL was encapsulated using an oil-in-oil emulsion as a templating procedure through two different approaches. In the first approach, a PDMS-polyurea (PU) shell was constructed by interfacial polymerization, while in the second approach, a graphene oxide (GO)-PDMS shell was constructed by cross-linking GO sheets. The composition and structure of both capsule types were fully characterized, and their CO 2 DAC performance was evaluated by gravimetric and breakthrough analysis. Both capsules exhibited competitive capacities, with the PDMS-PU capsules and the GO-PDMS capsules reaching 0.75 mol kg −1 and 0.66 mol kg −1 , respectively. We further demonstrate that both capsule systems can be regenerated with complementary electrothermal methods. Microwave (MW) regeneration was used for the PDMS-PU capsules, effectively releasing absorbed CO 2 in less than an hour. Owing to the electrical conductivity of GO, GO-PDMS capsules were regenerated via radio frequency heating (RF). This work highlights the importance and opportunity of tuning solid–liquid composite performance for advanced applications, including direct air capture of carbon dioxide.

Al-Mahbobi, Luma [Texas A&M University, College St↗

A Critical Review of the Circular Economy for Lithium-Ion Batteries and Photovoltaic Modules: Status, Challenges, and Opportunities

To meet net-zero emissions and cost targets for power production, recent analysis indicates that photovoltaic (PV) capacity in the United States could exceed 1 TW by 2050 alongside comparable levels of energy storage capacity, mostly from batteries. For comparison, the total U.S. utility-scale power capacity from all energy sources in 2020 was 1.2 TW (EIA 2022), of which solar satisfied approximately 3% (DOE 2021). With such massive scales of deployment, questions have arisen regarding issues of material supply for manufacturing, end-of-life management of technologies, environmental impacts across the life cycle, and economic costs to both individual consumers and society at large. A set of solutions to address these issues center on the development of a circular economy - shifting from a take-make-waste linear economic model to one that retains the value of materials and products as long as possible, recovering materials at end of life to recirculate back into the economy. With limited global experience, scholars and practitioners have begun to investigate circular economy pathways, focusing on applying novel technologies and analytical methods to fast-growing sectors like renewable energy. This critical review aims to synthesize the growing literature to identify key insights, gaps, and opportunities for research and implementation of a circular economy for two of the leading technologies that enable the transition to a renewable energy economy: solar PV and lithium-ion batteries (LIBs). We apply state-of-the-science systematic literature review procedures to critically analyze over 3,000 publications on the circular economy of solar PV and LIBs, categorizing those that pass a series of objective screens in ways that can illuminate the current state of the art, highlight existing impediments to a circular economy, and recommend future technological and analytical research. We conclude that while neither PV nor LIB industries have reached a circular economy, they are both on a path towards increased circularity. Based on our assessment of the state of current literature and scientific understanding, we recommend research move beyond its prior emphasis on recycling technology development to more comprehensively investigate other CE strategies, more holistically consider economic, environmental and policy aspects of CE strategies, increase leveraging of digital information systems that can support acceleration towards a CE, and to continue to study CE-related aspects of LIB and PV markets.

circular economy↗

Vanishing RKKY interactions in Ce-based cage compounds

Abstract We report the results of thermodynamic measurements in external magnetic field of the cubic Ce-based cage compounds Ce T 2 Cd 20 ( T = Ni,Pd). Our analysis of the heat-capacity data shows that the Γ 7 doublet is the ground state multiplet of the Ce 3+ ions. Consequently, for the Γ 7 doublet it can be theoretically shown that the Ruderman–Kittel–Kasuya–Yosida interaction between the localized Ce moments mediated by the conduction electrons, must vanish at temperatures much lower than the energy separating the ground state doublet from the first excited Γ 8 quartet. Our findings provide an insight as to why no long range order has been observed in these compounds down to temperatures in the milliKelvin range.

Physics↗

Computing with a Chemical Reservoir

Contemporary computation is expensive, with large language models and artificial intelligence becoming more common in daily life. However, high-performance computing is reaching the limits in speed and energy expenditure, and domain science requires ever-increasing computational capacity, with simulations and data analysis pipelines ever-growing in complexity. As we progress towards post-exascale computation, with the associated high energy costs, new methods of energy-conscious computation are required. Novel analog and hybrid digital-analog systems can overcome these challenges, and chemical reactions offer a promising avenue. Computers based on chemistry can provide compact desktop devices with immense computational power. These devices are readily scalable by considering greater reaction systems or vessels, meeting the high-performance requirements for scientific workflows. In this article, we present ChemComp, a compilation pipeline for the conversion of ordinary differential equations into implementable chemical reactions. We then demonstrate the solving capabilities of ChemComp by emulating a potential chemical reservoir device. We leverage the multi-layer intermediate representation (MLIR) compiler framework to implement an expressive chemical reaction abstraction and propose a path for chemical reaction networks (CRNs) to represent mathematical problems effectively. Combined, we demonstrate a potential workflow that can harness chemistry’s computing power to create energy-efficient, high-performance computation systems for contemporary computing needs.

artificial intelligence↗

Developing a Framework for Valuation of Grid Services

The electric system is rapidly evolving and growing, raising new questions about how to define and value grid services delivered by a diverse set of resources, including customer-owned assets. This report advances a service–parameter–value framework that links what a grid service does to why it matters, and how its benefits are evidenced. We build upon prior efforts (Bender et al. 2021) and extend them to include value categories (reliability, resilience, cost & access, and security) with primary and secondary tiers, service-specific value streams that explain how benefits materialize, and metrics that make valuation traceable and comparable. We apply the framework to the six core grid services defined in (Kolln et al. 2023): Frequency Response, Regulation, Reserves, Energy, Voltage Management, and Blackstart and demonstrate it on three use cases to highlight the adaptability of these value streams. Further, we outline how the framework integrates with existing tools such as asset optimization, hosting capacity and cost-benefit analysis, and propose a path to portable qualifications and consistent stacking rules for use in tariffs and filings. Finally, we identify future pathways for research and application research needs to support standardization and decision-ready comparisons across services, assets, and architectures.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Chemical looping conversion of CH4/CO2 to syngas on 5wt.%Ni@Ce0.6Zr0.4O2 catalyst: Impact of dynamic accumulation of surface carbon and oxygen vacancies

Syngas, a combination of carbon monoxide (CO) and hydrogen (H2), is a precursor to many chemicals and fuels, contributing to the billion-dollar global hydrocarbon industry. Chemical looping reforming (CLR) of the greenhouse gases methane (CH4) and carbon dioxide (CO2) allows for energy-efficient production of syngas. 5wt.% nickel (Ni) on ceria-zirconia (5wt%Ni@Ce0.6Zr0.4O2) mixed metal oxide catalyst was investigated here to explore pathways for enhanced syngas production on sustainable earth-abundant transition metal supported catalysts. The role of reduction-oxidation (redox) state of the catalyst, and carbon formation on the catalyst surface during chemical looping is explored to drive superior reaction kinetics, conversions, selectivity, and syngas ratios (H2/CO). The bulk and surface structure of the catalyst, along with carbon deposition features were characterized by electron microscopy, X-Ray diffraction, and ex situ Raman spectroscopy. The dynamic evolution of catalysts under CLR reaction conditions and the intrinsic reaction mechanisms were probed with in situ Raman spectroscopy, in situ Fourier transform spectroscopy, dynamic oxygen storage capacity (DOSC), and the Temporal Analysis of Products (TAP) reactor studies. Intrinsic kinetics of syngas production via CLR was correlated to the redox state of catalyst and the participation of nickel-catalyzed multiwalled carbon nanotube (CNT) growth, allowing enhanced CLR reaction performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Uncertainty quantification and reliability assessment for intermodal freight transportation

Intermodal freight optimization models support cost-effective, low-emission, and timely goods movement by coordinating trucks, rail, and barges. These models determine optimal flows, routing, and modal switches while respecting infrastructure and operational constraints. However, their real-world utility is often undermined by pervasive uncertainties-such as fluctuating transportation costs and emissions, variable terminal capacities, and uncertain freight demand-that distort key performance outcomes, including total system cost, carbon footprint, and transit time reliability. This study presents a structured framework for quantifying uncertainty in intermodal freight transportation (IFT) optimization. The framework evaluates how input uncertainty affects system performance and reliability, a critical need for ensuring that model-based decisions remain robust under real-world variability, especially amid volatile fuel prices, shifting demand, and growing disruptions. It integrates three complementary methods: (1) Sobol-based global sensitivity analysis to identify influential parameters affecting cost, emissions, and transit time, (2) Monte Carlo-based capacity perturbation analysis to assess robustness under probabilistic facility disruptions, and (3) Monte Carlo filtering with Bayesian inference to detect threshold-based performance vulnerabilities. The results highlight diesel truck unit cost as the dominant driver of variability. To improve system resilience, planners should prioritize uncertainty in fuel-related parameters when designing intermodal strategies.

Intermodal freight transportation↗

Robust measurement of microbial reduction of graphene oxide nanoparticles using image analysis

ABSTRACT Shewanella oneidensis ( S. oneidensis ) has the capacity to reduce electron acceptors within a medium and is thus used frequently in microbial fuel generation, pollutant breakdown, and nanoparticle fabrication. Microbial fuel setups, however, often require costly or labor-intensive components, thus making optimization of their performance onerous. For rapid optimization of setup conditions, a model reduction assay can be employed to allow simultaneous, large-scale experiments at lower cost and effort. Since S. oneidensis uses different extracellular electron transfer pathways depending on the electron acceptor, it is essential to use a reduction assay that mirrors the pathways employed in the microbial fuel system. For microbial fuel setups that use nanoparticles to stimulate electron transfer, reduction of graphene oxide provides a more accurate model than other commonly used assays as it is a bulk material that forms flocculates in solutions with a large ionic component. However, graphene oxide flocculates can interfere with traditional absorbance-based measurement techniques. This study introduces a novel image analysis method for quantifying graphene oxide reduction, showing improved performance and statistical accuracy over traditional methods. A comparative analysis shows that the image analysis method produces smaller errors between replicates and reveals more statistically significant differences between samples than traditional plate reader measurements under conditions causing graphene oxide flocculation. Image analysis can also detect reduction activity at earlier time points due to its use of larger solution volumes, enhancing color detection. These improvements in accuracy make image analysis a promising method for optimizing microbial fuel cells that use nanoparticles or bulk substrates. IMPORTANCE Shewanella oneidensis ( S. oneidensis ) is widely used in reduction processes such as microbial fuel generation due to its capacity to reduce electron acceptors. Often, these setups are labor-intensive to operate and require days to produce results, so use of a model assay would reduce the time and expenses needed for optimization. Our research developed a novel digital analysis method for analysis of graphene oxide flocculates that may be utilized as a model assay for reduction platforms featuring nanoparticles. Use of this model reduction assay will enable rapid optimization and drive improvements in the microbial fuel generation sector.

Bennett, Danielle T. (ORCID:0009000188748827)↗