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Stable single-site organonickel catalyst preferentially hydrogenolyses branched polyolefin C–C bonds

Current methods of processing accumulated polyolefin waste typically require harsh conditions, precious metals or high metal loadings to achieve appreciable activities. Here, in this work, we examined supported, single-site organonickel catalysts for polyolefin upcycling. Chemisorption of Ni(COD) 2 (COD, 1,5-cyclooctadiene) onto Brønsted acidic sulfated alumina (AlS) yields a highly electrophilic Ni(I) precatalyst, AlS/Ni(COD) 2 , which is converted under H 2 to the active AlS/Ni II H catalyst. This single-site system exhibits unique hydrogenolysis selectivity that favours cleaving branched polyolefin C–C linkages, enabling the hydrogenolytic separation of polyethylene and isotactic polypropylene (iPP) mixtures. Moreover, AlS/Ni II H remains highly selective and active for hydrogenolysis of iPP admixed with polyvinyl chloride, and the spent catalyst can be repeatedly regenerated by AlEt3 treatment. Experimental mechanistic analysis and density functional theory modelling reveal a turnover-limiting C–C scission pathway featuring β-alkyl transfer and strong olefin binding. These results highlight the potential of nickel-based systems for the selective upcycling of complex plastic waste streams.

green chemistry↗

Residual Stress Limits Gridline Bridging in Cracked Solar Cells

Cracks in solar cells can be generated in various ways, but this does not mean immediate power loss. Previous studies showed that gridlines bridge cracked silicon cells, and the bridging behavior decreases during the contact and separation of gridlines within bare cells. In this study, we investigate bridging behavior in laminated monocrystalline cells. We characterize the behavior with Weibull analysis of critical crack opening distance (COD), at which the gridline is completely separated. The Weibull analysis of the laminated cell shows a good agreement with bare cells at the first cycle. However, we observe different behavior during cyclic bending. Bare cells show gradual decay of critical COD, while laminated cells show instant decay and plateau. We hypothesize that the difference is due to residual stress, squeezing gridlines, and causing plastic deformation. This is justified by the correlation between critical COD and gridline morphology. In the presentation, we shall present a Weibull analysis of the cyclic bending of a laminated cell with a reduced residual stress effect.

bending↗

Utilization of lignocellulosic biofuel conversion residue by diverse microorganisms

Lignocellulosic conversion residue (LCR) is the material remaining after deconstructed lignocellulosic biomass is subjected to microbial fermentation and treated to remove the biofuel. Technoeconomic analyses of biofuel refineries have shown that further microbial processing of this LCR into other bioproducts may help offset the costs of biofuel generation. Identifying organisms able to metabolize LCR is an important first step for harnessing the full chemical and economic potential of this material. In this study, we investigated the aerobic LCR utilization capabilities of 71 Streptomyces and 163 yeast species that could be engineered to produce valuable bioproducts. The LCR utilization by these individual microbes was compared to that of an aerobic mixed microbial consortium derived from a wastewater treatment plant as representative of a consortium with the highest potential for degrading the LCR components and a source of genetic material for future engineering efforts. We analyzed several batches of a model LCR by chemical oxygen demand (COD) and chromatography-based assays and determined that the major components of LCR were oligomeric and monomeric sugars and other organic compounds. Many of the Streptomyces and yeast species tested were able to grow in LCR, with some individual microbes capable of utilizing over 40% of the soluble COD. For comparison, the maximum total soluble COD utilized by the mixed microbial consortium was about 70%. This represents an upper limit on how much of the LCR could be valorized by engineered Streptomyces or yeasts into bioproducts. To investigate the utilization of specific components in LCR and have a defined media for future experiments, we developed a synthetic conversion residue (SynCR) to mimic our model LCR and used it to show lignocellulose-derived inhibitors (LDIs) had little effect on the ability of the Streptomyces species to metabolize SynCR. We found that LCR is rich in carbon sources for microbial utilization and has vitamins, minerals, amino acids and other trace metabolites necessary to support growth. Testing diverse collections of Streptomyces and yeast species confirmed that these microorganisms were capable of growth on LCR and revealed a phylogenetic correlation between those able to best utilize LCR. Identification and quantification of the components of LCR enabled us to develop a synthetic LCR (SynCR) that will be a useful tool for examining how individual components of LCR contribute to microbial growth and as a substrate for future engineering efforts to use these microorganisms to generate valuable bioproducts.

09 BIOMASS FUELS↗

Availability and Performance Loss Factors for U.S. PV Fleet Systems

In the PV Fleet Performance Data Initiative, we partner with photovoltaic (PV) fleet owners to collect time-series PV production data and publish aggregated, anonymized results. This report is an update of our previous publications, specifically a FY 2021 performance index publication and a FY 2022 fleet degradation analysis. In this analysis, we have increased our data participants and system totals by around 10% to 8.5 GW and 24,000 separate inverter data channels. Four major analysis topics are considered in this report: Performance Index (PI) trends, PV system availability, soiling losses, and PV system degradation. Performance Index and inverter availability are assessed on a larger set of data from our FY 2021 report: 1,128 systems compared with 200 systems from before. The increased number of systems is due to an improved data quality methodology, as well as introducing new systems to the analysis. Overall results are similar to previously published values - overall inverter availability is low in the first six months of system performance before reaching steady-state by the end of the first year. Excluding this six-month startup period, system-level aggregated data shows a median (P50) system availability of 0.99 and a lower 10th percentile (P90) value of 0.95 (Figure ES-1). A dependence on system size is also demonstrated, with worse inverter availability results for larger PV systems. Causes of this effect are under investigation, but may be impacted by inverter size, which also show lower availability for larger inverter sizes. This report also investigates PI, correcting for degradation, soiling, snow, and availability. Following these corrections, the median system PI over its entire lifetime is 0.95. PI values reported here are approximately 3% lower than what we presented in our previous FY 2021 report. Soiling loss is assessed in a comprehensive way for the first time in this report. Results are presented using the COmbined Degradation and Soiling (CODS) method, as implemented in RdTools (v3.0.0a4). Soiling values are presented for 255 systems, which indicated irradiance-weighted soiling loss greater than 1%. The values have been published in an updated NREL soiling map at nrel.gov/pv/soiling.html. Finally, we investigated system degradation using three different data analysis techniques: conventional RdTools (year-on-year (YOY)), CODS, and Performance Loss Rate (PLR) analysis. Overall degradation results are consistent with our previous publications. Rerunning conventional RdTools on our updated fleet shows that some data partners have systematically fallen below the median system degradation rate (change over time) of -0.75 %/year. A comparison with PLR analysis, which looks at change in annual PI over time, shows that median system degradation is consistent with -0.5% to -0.75% per year change. However, at the P90 value, system degradation is substantially faster. These two results are consistent and indicate that resulting degradation statistics depend to a great degree on the population of PV systems making up the analysis cohort and whether soiling impacts the systems. The use of CODS for degradation analysis provides a different method for degradation assessment, which explicitly excludes the impact of recoverable soiling on degradation analysis. Excluding soiling effects yields an annual system degradation around -0.5% per year on average. This indicates that a portion of system performance loss may be attributed to periodic soiling that is not fully recovered. This report provides PV system owners/operators with background and methods to analyze PV system performance, give guidance for expected cohort performance, and performance loss values for use in pro-forma financial models, which guide new-build system design and bankability reports.

14 SOLAR ENERGY↗

Evaluation of liquid cloud albedo susceptibility in E3SM using coupled eastern North Atlantic surface and satellite retrievals

The impact of aerosol number concentration on cloud albedo is a persistent source of spread in global climate predictions due to multi-scale, interactive atmospheric processes that remain difficult to quantify. We use 5 years of geostationary satellite and surface retrievals at the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) eastern North Atlantic (ENA) site in the Azores to evaluate the representation of liquid cloud albedo susceptibility for overcast cloud scenes in the DOE Energy Exascale Earth System Model version 1 (E3SMv1) and provide possible reasons for model–observation discrepancies. The overall distribution of surface 0.2 % CCN concentration values is reasonably simulated, but simulated liquid water path (LWP) is lower than observed and layer mean droplet concentration (N d ) comparisons are highly variable depending on the N d retrieval technique. E3SMv1's cloud albedo is greater than observed for given LWP and N d values due to a lower cloud effective radius than observed. However, the simulated albedo response to N d is suppressed due to a correlation between the solar zenith angle (SZA) and N d created by the seasonal cycle that is not observed. Controlling for this effect by examining the cloud optical depth (COD) shows that E3SMv1's COD response to CCN concentration is greater than observed. For surface-based retrievals, this is only true after controlling for cloud adiabaticity because E3SMv1's adiabaticities are much lower than observed. Assuming a constant adiabaticity in surface retrievals as done in top-of-atmosphere (TOA) retrievals narrows the retrieved ln N d distribution, which increases the cloud albedo sensitivity to ln N d to match the TOA sensitivity. The greater sensitivity of COD to CCN is caused by a greater Twomey effect in which the sensitivity of N d to CCN is greater than observed for TOA-retrieved N d , and once model–observation cloud adiabaticity differences are removed, this is also true for surface-retrieved N d . The LWP response to N d in E3SMv1 is overall negative as observed. Despite reproducing the observed LWP–N d relationship, observed clouds become much more adiabatic as N d increases, while E3SMv1 clouds do not, associated with more heavily precipitating clouds that are partially but not completely caused by deeper clouds and weaker inversions in E3SMv1. These cloud property differences indicate that the negative LWP–N d relationship is likely not caused by the same mechanisms in E3SMv1 and observations. The negative simulated LWP response also fails to mute the excessively strong Twomey effect, highlighting potentially important confounding factor effects that likely render the LWP–N d relationship non-causal. N d retrieval scales and assumptions, particularly related to cloud adiabaticity, contribute to substantial spreads in the model–observation comparisons, though enough consistency exists to suggest that aerosol activation, drizzle, and entrainment processes are critical areas to focus E3SMv1 development for improving the fidelity of aerosol–cloud interactions in E3SM.

54 ENVIRONMENTAL SCIENCES↗

Coastal and submarine features on MSS imagery of Southeastern Massachusetts: Comparison with conventional maps

Three ERTS-1, MSS images of southeastern Massachusetts, including Cape Cod Bay, Cape Cod, and Nantucket Sound, show a variety of dynamic geologic and hydrologic phenomena. Coastal features imaged include the coastline at different time in the tidal cycle, harbors, lakes and ponds, marshes (wetlands), and beach and dune areas; submarine features include tidal flats, shoals, dredged and natural channels, and bars. Comparison with conventional maps at 1:1,000,000 and 1:250,000 scales show many inaccuracies between the ERTS imagery and the two map scales. The ERTS-1 imagery can be used to increase the accuracy of these maps, portray additional environmental information, and provide the capability for frequent updating of maps at such scales. ERTS-1 imagery provides a very cost effective method for provision of certain types of environmental data for Cape Cod and environs.

Williams, R. S., Jr.↗

Retrievals of Thick Cloud Optical Depth from the Geoscience Laser Altimeter System (GLAS) by Calibration of Solar Background Signal

Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other space-borne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds (< about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so we first calibrate the reflected solar radiation received by the photon-counting detectors of GLAS' 532 nm channel, which is the primary channel for atmospheric products. The solar background radiation is regarded as a noise to be subtracted in the retrieval process of the lidar products. However, once calibrated, it becomes a signal that can be used in studying the properties of optically thick clouds. In this paper, three calibration methods are presented: (I) calibration with coincident airborne and GLAS observations; (2) calibration with coincident Geostationary Operational Environmental Satellite (GOES) and GLAS observations of deep convective clouds; (3) calibration from the first principles using optical depth of thin water clouds over ocean retrieved by GLAS active remote sensing. Results from the three methods agree well with each other. Cloud optical depth (COD) is retrieved from the calibrated solar background signal using a one-channel retrieval. Comparison with COD retrieved from GOES during GLAS overpasses shows that the average difference between the two retrievals is 24%. As an example, the COD values retrieved from GLAS solar background are illustrated for a marine stratocumulus cloud field that is too thick to be penetrated by the GLAS laser. Based on this study, optical depths for thick clouds will be provided as a supplementary product to the existing operational GLAS cloud products in future GLAS data releases.

Yang, Yuekui↗

Analyzing the Effect of Intraseasonal Meteorological Variability and Land Cover on Aerosol-Cloud Interactions During the Amazonian Biomass Burning Season

High resolution aerosol, cloud, water vapor, and atmospheric profile data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are utilized to examine the impact of aerosols on clouds during the Amazonian biomass burning season in Rondnia, Brazil. It is found that increasing background column water vapor (CWV) throughout this transition season between the Amazon dry and wet seasons exerts a strong effect on cloud properties. As a result, aerosol-cloud correlations should be stratified by column water vapor to achieve a more accurate assessment of the effect of aerosols on clouds. Previous studies ignored the systematic changes to meteorological factors during the transition season, leading to possible misinterpretation of their results. Cloud fraction is shown generally to increase with aerosol optical depth (AOD) for both low and high values of column water vapor, whereas the relationship between cloud optical depth (COD) and AOD exhibits a different relationship. COD increases with AOD until AOD approx. 0.25 due to the first indirect (microphysical) effect. At higher values of AOD, COD is found to decrease with increasing AOD, which may be due to: (1) the inhibition of cloud development by absorbing aerosols (radiative effect) and/or (2) a retrieval artifact in which the measured reflectance in the visible is less than expected from a cloud top either from the darkening of clouds through the addition of carbonaceous biomass burning aerosols or subpixel dark surface contamination in the measured cloud reflectance. If (1) is a contributing mechanism, as we suspect, then a linear relationship between the indirect effect and increasing AOD, assumed in a majority of GCMs, is inaccurate since these models do not include treatment of aerosol absorption in and around clouds. The effect of aerosols on both column water vapor and clouds over varying land surface types is also analyzed. The study finds that the difference in column water vapor between forest and pasture is not correlated with aerosol loading, supporting the assumption that temporal variation of column water vapor is primarily a function of the larger-scale meteorology. However, a difference in the response of cloud fraction to increasing AOD is observed between forest and pasture. This suggests that dissimilarities between other meteorological factors, such as atmospheric stability, are likely to have an impact on aerosol-cloud correlations between different land-cover types.

TenHoeve, J. E.↗

Extending "Deep Blue" Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: Sensitivity Analysis and First Case Studies

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty approximately 25-50 percent (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty approximately10-20 percent, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

aerosols above clouds↗

The Two-Column Aerosol Project: Phase I - Overview and Impact of Elevated Aerosol Layers on Aerosol Optical Depth

The Two-Column Aerosol Project (TCAP), conducted from June 2012 through June 2013, was a unique study designed to provide a comprehensive data set that can be used to investigate a number of important climate science questions, including those related to aerosol mixing state and aerosol radiative forcing. The study was designed to sample the atmosphere be tween and within two atmospheric columns; one fixed near the coast of North America (over Cape Cod, MA) and a second moveable column over the Atlantic Ocean several hundred kilometers from the coast. The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) was deployed at the base of the Cape Cod column, and the ARM Aerial Facility was utilized for the summer and winter intensive observation periods. One important finding from TCAP is that four of six nearly cloud-free flight days had aerosol layers aloft in both the Cape Cod and maritime columns that were detected using the nadir pointing second-generation NASA high-spectral resolution lidar (HSRL-2).These layer s contributed up to 60 of the total observed aerosol optical depth (AOD). Many of these layers were also intercepted by the aircraft configured for in situ sampling, and the aerosol in the layers was found to have increased amounts of biomass burning material and nitrate compared to aerosol found near the surface. In addition, while there was a great deal of spatial and day-to-day variability in the aerosol chemical composition and optical properties, no systematic differences between the two columns were observed.

aerosols↗

Cloud Thermodynamic Phase Detection with Polarimetrically Sensitive Passive Sky Radiometers

The primary goal of this project has been to investigate if ground-based visible and near-infrared passive radiometers that have polarization sensitivity can determine the thermodynamic phase of overlying clouds, i.e. if they are comprised of liquid droplets or ice particles. While this knowledge is important by itself for our understanding of the global climate, it can also help improve cloud property retrieval algorithms that use total (unpolarized) radiance to determine Cloud Optical Depth (COD). This is a potentially unexploited capability of some instruments in the NASA Aerosol Robotic Network (AERONET), which, if practical, could expand the products of that global instrument network at minimal additional cost. We performed simulations that found, for zenith observations, cloud thermodynamic phase is often expressed in the sign of the Q component of the Stokes polarization vector. We chose our reference frame as the plane containing solar and observation vectors, so the sign of Q indicates the polarization direction, parallel (negative) or perpendicular (positive) to that plane. Since the quantity of polarization is inversely proportional to COD, optically thin clouds are most likely to create a signal greater than instrument noise. Besides COD and instrument accuracy, other important factors for the determination of cloud thermodynamic phase are the solar and observation geometry (scattering angles between 40 and 60 degrees are best), and the properties of ice particles (pristine particles may have halos or other features that make them difficult to distinguish from water droplets at specific scattering angles, while extreme ice crystal aspect ratios polarize more than compact particles). We tested the conclusions of our simulations using data from polarimetrically sensitive versions of the Cimel 318 sun photometerradiometer that comprise AERONET. Most algorithms that exploit Cimel polarized observations use the Degree of Linear Polarization (DoLP), not the individual Stokes vector elements (such as Q). For this reason, we had no information about the accuracy of Cimel observed Q and the potential for cloud phase determination. Indeed, comparisons to ceilometer observations with a single polarized spectral channel version of the Cimel at a site in the Netherlands showed little correlation. Comparisons to Lidar observations with a more recently developed, multi-wavelength polarized Cimel in Maryland, USA, show more promise. This divergence between simulations and observations has prompted us to begin the development of a small test instrument called the Sky Polarization Radiometric Instrument for Test and Evaluation (SPRITE). This instrument is specifically devoted to the accurate observation of Q, and the testing of calibration and uncertainty assessment techniques, with the ultimate goal of understanding the practical feasibility of these measurements.

Knobelspiesse, Kirk D.↗

Multimaterial 3D Printing in Activating Bath Enables In Situ Polymerization of Thermosets with Intricate Geometries and Diverse Elastic Behaviors

Polydicyclopentadiene, p(DCPD), is a high‐performance thermoset valued for its exceptional toughness, strength, and stiffness. When copolymerized with 1,5‐cyclooctadiene (COD), its mechanical properties can be tuned from glassy to rubbery at room temperature. While frontal polymerization enables a rapid and energy‐efficient route to 3D print DCPD‐based materials, challenges such as ink shelf life and gravitational distortion, especially in direct ink writing of soft COD‐rich formulations, must be considered. Here, a complementary chemical strategy is presented, embedded 3D printing, that enables localized in situ polymerization of printed DCPD/COD inks within a reactive support matrix. The matrix provides both physical support and a reservoir of chemical activator, which diffuses into the ink, activates a latent bis(N‐heterocyclic carbene) Ru precatalyst, and initiates ring‐opening metathesis polymerization. Curing begins at the ink–matrix interface and propagates inward via diffusion, stabilizing the interface and preventing capillary‐driven deformation regardless of the matrix yield stress. This approach eliminates the need for cold storage, external curing, or photoinitiation, significantly expanding the processing window. Using this method, diverse thermosetting and elastomeric architectures are fabricated with features as small as 5 µm and aspect ratios of 100, including interlinked chains, shallow spherical shells exhibiting snap‐through buckling, and hair‐like fin arrays inaccessible through traditional techniques.

chemical activation↗

Long term performance of pilot methanogenic digester filled with seashell wastes treating slaughterhouse wastes: Biogas production and environmental impact

High ammonia and organic acids contents of decomposed slaughterhouse waste (SHW) often result in the severe inhibition or even failure of the anaerobic digestion (AD). The two-stage AD system can alleviate the ammonia inhibition; however, addition of alkali is often needed to maintain the neutral condition. In this study, seashell wastes containing high percentage of calcium carbonate (CaCO 3 ) were for the first time added in a pilot scale methanogenic digester treating chicken blood waste to retain the microorganisms and provide pH buffers for the substrate. A long-duration performance of this digester was conducted for 400 days under different organic loading rates (OLRs). The results show that methane yields of the digester were 244.8 and 224.9 mL g –1 COD added at OLR of 0.4 and 0.6 g COD L –1 d –1 , respectively, higher than the results of previous studies treating the similar feedstock. An AD system treating blood wastes of a typical poultry slaughterhouse was also proposed for which energy balance and carbon footprint analyses were conducted. The energy production of 0.35 MJ kg –1 blood and carbon emissions reduction of 0.05 kg CO 2 -eq kg –1 blood can be achieved from treating blood waste of the broiler chicken. Finally, this study reveals that using seashell wastes in an AD treating SHW can facilitate the reuse of aquaculture wastes and improve the sustainability of meat industry.

09 BIOMASS FUELS↗

Scaling up carboxylic acid production from cheese whey and brewery wastewater via methane-arrested anaerobic digestion

In a circular economy, organic waste streams are valuable resources for sustainably producing chemicals and fuels. This study investigates a new methane-arrested anaerobic digestion (MAAD) process that converts high-strength cheese whey and brewery wastewater into carboxylic acids. The process was developed and optimized under various bench-scale semi-continuous (fed-batch) operating conditions (e.g., retention time, organic loading rate, pH, and feed/harvest frequency). The MAAD responses to various control-failure scenarios were also systematically investigated. The highest total acid productivity was 26g/(L liq ·d) with a substrate conversion of 0.79g COD digested /g COD fed at a hydraulic retention time (HRT) of approximately 2 d in a 14-L digester. The most stable conditions for digester operation (HRT 3 d at pH 6.0 and 40°C) were selected for process scale-up to 100gal (~380 L). Semi-continuous, pilot-scale MAAD successfully produced a total acid concentration of 40.6+/-1.1 g/L with 8.1% acetic acid, 45.1% butyric acid, and 44.5% lactic acid. The links between wastewater characteristics, operation mode, digester scale, and microbial community structure were statistically analyzed. The results show genera Sporolactobacillus and Clostridium positively correlate with butyric acid production (Pearson correlation coefficient>0.5). Moreover, four kinetic models were developed and fit to batch MAAD experimental datasets (R 2 >95%) and were successfully applied to predict the total acid production in both bench-and pilot-scale semi-continuous MAADs. In conclusion, this study shows MAAD has the potential for industrial-scale applications and is a robust platform to valorize low- or negative-value waste streams into high-value bioproducts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tackling the curse of dimensionality in fractional and tempered fractional PDEs with physics-informed neural networks

Fractional and tempered fractional partial differential equations (PDEs) are effective models of long-range interactions, anomalous diffusion, and non-local effects. Traditional numerical methods for these problems are mesh-based, thus struggling with the curse of dimensionality (CoD). Physics-informed neural networks (PINNs) offer a promising solution due to their universal approximation, generalization ability, and mesh-free training. In principle, Monte Carlo fractional PINN (MC-fPINN) estimates fractional derivatives using Monte Carlo methods and thus could lift CoD. However, this may cause significant variance and errors, hence affecting convergence; in addition, MC-fPINN is sensitive to hyperparameters. In general, numerical methods and specifically PINNs for tempered fractional PDEs are under-developed. Herein, we extend MC-fPINN to tempered fractional PDEs to address these issues, resulting in the Monte Carlo tempered fractional PINN (MC-tfPINN). To reduce possible high variance and errors from Monte Carlo sampling, we replace the one-dimensional (1D) Monte Carlo with 1D Gaussian quadrature, applicable to both MC-fPINN and MC-tfPINN. We validate our methods on various forward and inverse problems of fractional and tempered fractional PDEs, scaling up to 100,000 dimensions. Our improved MC-fPINN/MC-tfPINN using quadrature consistently outperforms the original versions in accuracy and convergence speed in very high dimensions.

42 ENGINEERING↗

Pilot microbial electrolysis cell closes the hydrogen loop for hydrothermal wet waste conversion to jet fuel

The global shift toward net-zero emissions necessitates resource recovery from wet waste. In this study, we demonstrate the first feasibility of combining pilot-scale microbial electrolytic cells (MECs) with hydrothermal liquefaction (HTL) for simultaneous post-hydrothermal liquefaction wastewater (PHW) treatment and efficient hydrogen (H₂) production to meet biocrude upgrading requirements. Long-term single reactor operation revealed that fixed anode potential enabled rapid startup, and low catholyte pH and high salinity were effective in suppression of cathodic methanogenesis and acetogenesis – resulting in high current density of 16.6 A m –2 and 9.3 A m –2 when feeding synthetic wastewater and PHW respectively. Additionally, the anode biofilm exhibited spatial variations in response to local environmental conditions. In conclusion, onsite parallel or serial operations of multiple MECs showed good performance using actual PHW with a record-high H 2 production rate of 0.5 L L R day –1 for MEC over 10 liters scale, and the optimal chemical oxygen demand (COD)-to-H 2 yield reached 0.127 kg-H 2 per kg-COD, supporting a self-sufficient, closed-loop upgrade to jet fuel.

08 HYDROGEN↗

Electrocatalytic oxidation of hydrothermal liquefaction-derived aqueous phase for on-site wastewater treatment and H 2 production

Electrocatalytic oxidation (ECO) is a promising method for generating molecular hydrogen (H 2 ) while simultaneously treating the aqueous phase (AP) from hydrothermal liquefaction (HTL) of biomass-derived feedstocks such as algae, food waste, sludge, and wood. This study highlights the impact of HTL-AP composition on ECO performance, mainly activity, stability, and efficiency in a batch and flow electrolyzer. We demonstrated current efficiency (CE) for chemical oxygen demand (COD) removal ranges from 14% to 85% in the flow electrolyzer with electrode stability increasing from 20 to ≥2,800 h. Decreasing the applied potential enhances the CE. High ammonium content can accelerate deactivation, yet chloride ions appear to aid oxidation of organic compounds and enhanced anode stability. A preliminary energy and H 2 balance for an HTL sewage sludge plant shows that the HTL-AP contains sufficient COD to produce all the H 2 needs for bio-oil hydrotreating, with a 26% surplus available for other uses.

Electrolysis↗

Prioritization of Early-Stage Research and Development of a Hydrogel-Encapsulated Anaerobic Technology for Distributed Treatment of High Strength Organic Wastewater

This study aims to support the prioritization of research and development (R&D) pathways of an anaerobic technology leveraging hydrogel-encapsulated biomass to treat high-strength organic industrial wastewaters, enabling decentralized energy recovery and treatment to reduce organic loading on centralized treatment facilities. To characterize the sustainability implications of early-stage design decisions and to delineate R&D targets, an encapsulated anaerobic process model was developed and coupled with design algorithms for integrated process simulation, techno-economic analysis, and life cycle assessment under uncertainty. Across the design space, a single-stage configuration with passive biogas collection was found to have the greatest potential for financial viability and the lowest life cycle carbon emission. Through robust uncertainty and sensitivity analyses, we found technology performance was driven by a handful of design and technological factors despite uncertainty surrounding many others. Hydraulic retention time and encapsulant volume were identified as the most impactful design decisions for the levelized cost and carbon intensity of chemical oxygen demand (COD) removal. Encapsulant longevity, a technological parameter, was the dominant driver of system sustainability and thus a clear R&D priority. Ultimately, we found encapsulated anaerobic systems with optimized fluidized bed design have significant potential to provide affordable, carbon-negative, and distributed COD removal from high strength organic wastewaters if encapsulant longevity can be maintained at 5 years or above.

Anaerobic Treatment↗