Machine Learning for Polymer Design to Enhance Pervaporation-Based Organic Recovery.

Pervaporation (PV) is an effective membrane separation process for organic dehydration, recovery, and upgrading. However, it is crucial to improve membrane materials beyond the current permeability-selectivity trade-off. In this research, we introduce machine learning (ML) models to identify high-potential polymers, greatly improving the efficiency and reducing cost compared to conventional trial-and-error approach. We utilized the largest PV data set to date and incorporated polymer fingerprints and features, including membrane structure, operating conditions, and solute properties. Dimensionality reduction, missing data treatment, seed randomness, and data leakage management were employed to ensure model robustness. The optimized LightGBM models achieved RMSE of 0.447 and 0.360 for separation factor and total flux, respectively (logarithmic scale). Screening approximately 1 million hypothetical polymers with ML models resulted in identifying polymers with a predicted permeation separation index >30 and synthetic accessibility score <3.7 for acetic acid extraction. This study demonstrates the promise of ML to accelerate tailored membrane designs.

Electrochemically coupled CH4 and CO2 consumption driven by microbial processes.

The chemical transformations of methane (CH4) and carbon dioxide (CO2) greenhouse gases typically have high energy barriers. Here we present an approach of strategic coupling of CH4 oxidation and CO2 reduction in a switched microbial process governed by redox cycling of iron minerals under temperate conditions. The presence of iron minerals leads to an obvious enhancement of carbon fixation, with the minerals acting as the electron acceptor for CH4 oxidation and the electron donor for CO2 reduction, facilitated by changes in the mineral structure. The electron flow between the two functionally active microbial consortia is tracked through electrochemistry, and the energy metabolism in these consortia is predicted at the genetic level. This study offers a promising strategy for the removal of CH4 and CO2 in the natural environment and proposes an engineering technique for the utilization of major greenhouse gases.

Coupling Curvature and Hydrophobicity: A Counterintuitive Strategy for Efficient Electroreduction of Nitrate into Ammonia.

The electrochemical upcycling of nitrate (NO3-) to ammonia (NH3) holds promise for synergizing both wastewater treatment and NH3 synthesis. Efficient stripping of gaseous products (NH3, H2, and N2) from electrocatalysts is crucial for continuous and stable electrochemical reactions. This study evaluated a layered electrocatalyst structure using copper (Cu) dendrites to enable a high curvature and hydrophobicity and achieve a stratified liquid contact at the gas-liquid interface of the electrocatalyst layer. As such, gaseous product desorption or displacement from electrocatalysts was enhanced due to the separation of a wetted reaction zone and a nonwetted zone for gas transfer. Consequently, this electrocatalyst structure yielded a 2.9-fold boost in per-active-site activity compared with that with a low curvature and high hydrophilic counterpart. Moreover, a NH3 Faradaic efficiency of 90.9 ± 2.3% was achieved with nearly 100% NO3- conversion. This high-curvature hydrophobic Cu dendrite was further integrated with a gas-extraction membrane, which demonstrated a comparable NH3 yield from the real reverse osmosis retentate brine.

Ca-Based Layered Double Hydroxides for Environmentally Sustainable Carbon Capture.

The process of carbon dioxide capture typically requires a large amount of energy for the separation of carbon dioxide from other gases, which has been a major barrier to the widespread deployment of carbon capture technologies. Innovation of carbon dioxide adsorbents is herein vital for the attainment of a sustainable carbon capture process. In this study, we investigated the electrified synthesis and rejuvenation of calcium-based layered double hydroxides (Ca-based LDHs) as solid adsorbents for CO2. We discovered that the particle morphology and phase purity of the LDHs, along with the presence of secondary phases, can be controlled by tuning the current density during electrodeposition on a porous carbon substrate. The change in phase composition during carbonation and calcination was investigated to unveil the effect of different intercalated anions on the surface basicity and thermal stability of Ca-based LDHs. By decoupling the adsorption of water and CO2, we showed that the adsorbed water largely promoted CO2 adsorption, most likely through a sequential dissolution and reaction pathway. A carbon capture capacity of 4.3 ± 0.5 mmol/g was measured at 30 °C and relative humidity of 40% using 10 vol % CO2 in nitrogen as the feed stream. After CO2 capture occurred, the thermal regeneration step was carried out by directly passing an electric current through the conductive carbon substrate, known as the Joule-heating effect. CO2 was found to start desorbing from the Ca-based LDHs at a temperature as low as 220 °C as opposed to the temperature above 700 °C required for calcium carbonate that forms as part of the Ca-looping capture process. Finally, we evaluated the cumulative energy demand and environmental impact of the LDH-based capture process using a life cycle assessment. We identified the most environmentally concerning step in the process and concluded that the postcombustion CO2 capture using LDH could be advantageous compared with existing technologies.

Membrane Distillation-Crystallization for Sustainable Carbon Utilization and Storage.

Anthropogenic greenhouse gas emissions from power plants can be limited using postcombustion carbon dioxide capture by amine-based solvents. However, sustainable strategies for the simultaneous utilization and storage of carbon dioxide are limited. In this study, membrane distillation-crystallization is used to facilitate the controllable production of carbonate minerals directly from carbon dioxide-loaded amine solutions and waste materials such as fly ash residues and waste brines from desalination. To identify the most suitable conditions for carbon mineralization, we vary the membrane type, operating conditions, and system configuration. Feed solutions with 30 wt % monoethanolamine are loaded with 5-15% CO2 and heated to 40-50 °C before being dosed with 0.18 M Ca2+ and Mg2+. Membranes with lower surface energy and greater roughness are found to more rapidly promote mineralization due to up to 20% greater vapor flux. Lower operating temperature improves membrane wetting tolerance by 96.2% but simultaneously reduces crystal growth rate by 48.3%. Sweeping gas membrane distillation demonstrates a 71.6% reduction in the mineralization rate and a marginal improvement (37.5%) on membrane wetting tolerance. Mineral identity and growth characteristics are presented, and the analysis is extended to explore the potential improvements for carbon mineralization as well as the feasibility of future implementation.

Tough and Recyclable Phase-Separated Supramolecular Gels via a Dehydration-Hydration Cycle.

Hydrogels are compelling materials for emerging applications including soft robotics and autonomous sensing. Mechanical stability over an extensive range of environmental conditions and considerations of sustainability, both environmentally benign processing and end-of-life use, are enduring challenges. To make progress on these challenges, we designed a dehydration-hydration approach to transform soft and weak hydrogels into tough and recyclable supramolecular phase-separated gels (PSGs) using water as the only solvent. The dehydration-hydration approach led to phase separation and the formation of domains consisting of strong polymer-polymer interactions that are critical for forming PSGs. The phase-separated segments acted as robust, physical cross-links to strengthen PSGs, which exhibited enhanced toughness and stretchability in its fully swollen state. PSGs are not prone to overswelling or severe shrinkage in wet conditions and show environmental tolerance in harsh conditions, e.g., solutions with pH between 1 and 14. Finally, we demonstrate the use of PSGs as strain sensors in air and aqueous environments.

Scale-up and techno-economic analysis of microbial electrolysis cells for hydrogen production from wastewater.

Microbial electrolysis cells (MECs) have demonstrated high-rate H2 production while concurrently treating wastewater, but the transition in scale from laboratory research to systems that can be practically applied has encountered challenges. It has been more than a decade since the first pilot-scale MEC was reported, and in recent years, many attempts have been made to overcome the barriers and move the technology to the market. This study provided a detailed analysis of MEC scale-up efforts and summarized the key factors that should be considered to further develop the technology. We compared the major scale-up configurations and systematically evaluated their performance from both technical and economic perspectives. We characterized how system scale-up impacts the key performance metrics such as volumetric current density and H2 production rate, and we proposed methods to evaluate and optimize system design and fabrication. In addition, preliminary techno-economic analysis indicates that MECs can be profitable in many different market scenarios with or without subsidies. We also provide perspectives on future development needed to transition MEC technology to the marketplace.

Simple and Low-Cost Electroactive Membranes for Ammonia Recovery.

Ammonia is considered a contaminant to be removed from wastewater. However, ammonia is a valuable commodity chemical used as the primary feedstock for fertilizer manufacturing. Here we describe a simple and low-cost ammonia gas stripping membrane capable of recovering ammonia from wastewater. The material is composed of an electrically conducting porous carbon cloth coupled to a porous hydrophobic polypropylene support, that together form an electrically conductive membrane (ECM). When a cathodic potential is applied to the ECM surface, hydroxide ions are produced at the water-ECM interface, which transforms ammonium ions into higher-volatility ammonia that is stripped across the hydrophobic membrane material using an acid-stripping solution. The simple structure, low cost, and easy fabrication process make the ECM an attractive material for ammonia recovery from dilute aqueous streams, such as wastewater. When paired with an anode and immersed into a reactor containing synthetic wastewater (with an acid-stripping solution providing the driving force for ammonia transport), the ECM achieved an ammonia flux of 141.3 ± 14.0 g.cm-2.day-1 at a current density of 6.25 mA.cm-2 (69.2 ± 5.3 kg(NH3-N)/kWh). It was found that the ammonia flux was sensitive to the current density and acid circulation rate.

Machine Learning in Environmental Research: Common Pitfalls and Best Practices.

Machine learning (ML) is increasingly used in environmental research to process large data sets and decipher complex relationships between system variables. However, due to the lack of familiarity and methodological rigor, inadequate ML studies may lead to spurious conclusions. In this study, we synthesized literature analysis with our own experience and provided a tutorial-like compilation of common pitfalls along with best practice guidelines for environmental ML research. We identified more than 30 key items and provided evidence-based data analysis based on 148 highly cited research articles to exhibit the misconceptions of terminologies, proper sample size and feature size, data enrichment and feature selection, randomness assessment, data leakage management, data splitting, method selection and comparison, model optimization and evaluation, and model explainability and causality. By analyzing good examples on supervised learning and reference modeling paradigms, we hope to help researchers adopt more rigorous data preprocessing and model development standards for more accurate, robust, and practicable model uses in environmental research and applications.

High-Efficiency Recovery of Acetic Acid from Water Using Electroactive Gas-Stripping Membranes.

Recovery of carbon-based resources from waste is a critical need for achieving carbon neutrality and reducing fossil carbon extraction. We demonstrate a new approach for extracting volatile fatty acids (VFAs) using a multifunctional direct heated and pH swing membrane contactor. The membrane is a multilayer laminate composed of a carbon fiber (CF) bound to a hydrophobic membrane and sealed with a layer of polydimethylsiloxane (PDMS); this CF is used as a resistive heater to provide a thermal driving force for PDMS that, while a highly hydrophobic material, is known for its ability to rapidly pass gases, including water vapor. The transport mechanism for gas transport involves the diffusion of molecules through the free volume of the polymer matrix. CF coated with polyaniline (PANI) is used as an anode to induce an acidic pH swing at the interface between the membrane and water, which can protonate the VFA molecule. The innovative multilayer membrane used in this study has successfully demonstrated a highly efficient recovery of VFAs by simultaneously combining pH swing and joule heating. This novel technique has revealed a new concept in the field of VFA recovery, offering promising prospects for further advancements in this area. The energy consumption was 3.37 kWh/kg for acetic acid (AA), and an excellent separation factor of AA/water of 51.55 ± 2.11 was obtained with high AA fluxes of 51.00 ± 0.82 g.m-2hr-1. The interfacial electrochemical reactions enable the extraction of VFAs without the need for bulk temperature and pH modification.

Highly Selective Electrochemical Nitrate to Ammonia Conversion by Dispersed Ru in a Multielement Alloy Catalyst.

Electrochemical reduction of nitrate to ammonia (NH3) converts an environmental pollutant to a critical nutrient. However, current electrochemical nitrate reduction operations based on monometallic and bimetallic catalysts are limited in NH3 selectivity and catalyst stability, especially in acidic environments. Meanwhile, catalysts with dispersed active sites generally exhibit a higher atomic utilization and distinct activity. Herein, we report a multielement alloy nanoparticle catalyst with dispersed Ru (Ru-MEA) with other synergistic components (Cu, Pd, Pt). Density functional theory elucidated the synergy effect of Ru-MEA than Ru, where a better reactivity (NH3 partial current density of -50.8 mA cm-2) and high NH3 faradaic efficiency (93.5%) is achieved in industrially relevant acidic wastewater. In addition, the Ru-MEA catalyst showed good stability (e.g., 19.0% decay in FENH3 in three hours). This work provides a potential systematic and efficient catalyst discovery process that integrates a data-guided catalyst design and novel catalyst synthesis for a range of applications.

Evaluating UV254 absorbance reductions in landfill leachate for municipal sewage co-treatment through timed UV/electrooxidation.

Landfill leachate contains dissolved organic matter (DOM) exhibiting high ultraviolet absorbance at 254 nm (UVA254). The UVA254 limits leachate co-treatment with municipal sewage by hindering the downstream UV disinfection efficiency at wastewater treatment plants. Here, we alleviated the UVA254 by timing the radiation in a UV/electrooxidation (UV/EO) process to accelerate reactive species formation. At 200 A·m-2, the UV radiation was delayed by 10 min to accumulate 21 mg·L-1 as Cl2, which enhanced the initial radical formation rate by 5.25 times compared with a simultaneous UV/EO. The timed operation increased the steady-state concentrations of ClO• by 700 times to 4.11 × 10-14 M and reduced the leachate UVA254 by 78.2% after 60 min. We identified that aromatic formulas with low oxygen content were susceptible to UV/EO from Fourier-transform ion cyclotron resonance mass spectrometry analysis. The toxicity of the treated leachate and generated byproducts was assessed through specific oxygen uptake rates (SOUR) and developmental assays with Platynereis dumerilii. After quenching the residual chlorine, leachate co-treatment at 3.5% v/v presented minimal toxicological risk. Our findings provide operational insights for applying UV/EO in high UVA254 matrices such as landfill leachate.

Predicting Extraction Selectivity of Acetic Acid in Pervaporation by Machine Learning Models with Data Leakage Management.

The extraction of acetic acid and other carboxylic acids from water is an emerging separation need as they are increasingly produced from waste organics and CO2 during carbon valorization. However, the traditional experimental approach can be slow and expensive, and machine learning (ML) may provide new insights and guidance in membrane development for organic acid extraction. In this study, we collected extensive literature data and developed the first ML models for predicting separation factors between acetic acid and water in pervaporation with polymers' properties, membrane morphology, fabrication parameters, and operating conditions. Importantly, we assessed seed randomness and data leakage problems during model development, which have been overlooked in ML studies but will result in over-optimistic results and misinterpreted variable importance. With proper data leakage management, we established a robust model and achieved a root-mean-square error of 0.515 using the CatBoost regression model. In addition, the prediction model was interpreted to elucidate the variables' importance, where the mass ratio was the topmost significant variable in predicting separation factors. In addition, polymers' concentration and membranes' effective area contributed to information leakage. These results demonstrate ML models' advances in membrane design and fabrication and the importance of vigorous model validation.

DIET-like mutualism of Geobacter and methanogens at specific electrode potential boosts production of both methane and hydrogen from propionate.

Direct interspecies electron transfer (DIET) has been demonstrated to be an efficient type of mutualism in methanogenesis. However, few studies have reported its presence in mixed microbial communities and its trigger mechanism in the natural environment and engineered systems. Here, we reported DIET-like mutualism of Geobacter and methanogens in the planktonic microbiome for the first time in anaerobic electrochemical digestion (AED) fed with propionate, potentially triggered by excessive cathodic hydrogen (56 times higher than the lowest) under the electrochemical condition. In contrast with model prediction without DIET, the highest current density and hydrogen and methane production were concurrently observed at -0.2 V where an abundance of Geobacter (49%) and extracellular electron transfer genes were identified in the planktonic microbiome via metagenomic analysis. Metagenomic assembly genomes annotated to Geobacter anodireducens were identified alongside two methanogens, Methanothrix harundinacea and Methanosarcina mazei, which were previously identified to participate in DIET. This discovery revealed that DIET-like mutualism could be triggered without external conductive materials, highlighting its potentially ubiquitous presence. Such mutualism simultaneously boosted methane and hydrogen production, thereby demonstrating the potential of AED in engineering applications.

Quick-Release Antifouling Hydrogels for Solar-Driven Water Purification.

Hydrogels are promising soft materials for energy and environmental applications, including sustainable and off-grid water purification and harvesting. A current impediment to technology translation is the low water production rate well below daily human demand. To overcome this challenge, we designed a rapid-response, antifouling, loofah-inspired solar absorber gel (LSAG) capable of producing potable water from various contaminated sources at a rate of ∼26 kg m-2 h-1, which is sufficient to meet daily water demand. The LSAG-produced at room temperature via aqueous processing using an ethylene glycol (EG)-water mixture-uniquely integrates the attributes of poly(N-isopropylacrylamide) (PNIPAm), polydopamine (PDA), and poly(sulfobetaine methacrylate) (PSBMA) to enable off-grid water purification with enhanced photothermal response and the capacity to prevent oil fouling and biofouling. The use of the EG-water mixture was critical to forming the loofah-like structure with enhanced water transport. Remarkably, under sunlight irradiations of 1 and 0.5 sun, the LSAG required only 10 and 20 min to release ∼70% of its stored liquid water, respectively. Equally important, we demonstrate the ability of LSAG to purify water from various harmful sources, including those containing small molecules, oils, metals, and microplastics.

Underestimation of Sector-Wide Methane Emissions from United States Wastewater Treatment.

An increasing percentage of US waste methane (CH4) emissions come from wastewater treatment (10% in 1990 to 14% in 2019), although there are limited measurements across the sector, leading to large uncertainties in current inventories. We conducted the largest study of CH4 emissions from US wastewater treatment, measuring 63 plants with average daily flows ranging from 4.2 × 10-4 to 8.5 m3 s-1 (<0.1 to 193 MGD), totaling 2% of the 62.5 billion gallons treated, nationally. We employed Bayesian inference to quantify facility-integrated emission rates with a mobile laboratory approach (1165 cross-plume transects). The median plant-averaged emission rate was 1.1 g CH4 s-1 (0.1-21.6 g CH4 s-1; 10th/90th percentiles; mean 7.9 g CH4 s-1), and the median emission factor was 3.4 × 10-2 g CH4 (g influent 5 day biochemical oxygen demand; BOD5)-1 [0.6-9.9 × 10-2 g CH4 (g BOD5)-1; 10th/90th percentiles; mean 5.7 × 10-2 g CH4 (g BOD5)-1]. Using a Monte Carlo-based scaling of measured emission factors, emissions from US centrally treated domestic wastewater are 1.9 (95% CI: 1.5-2.4) times greater than the current US EPA inventory (bias of 5.4 MMT CO2-eq). With increasing urbanization and centralized treatment, efforts to identify and mitigate CH4 emissions are needed.

Methane Emissions from Municipal Wastewater Collection and Treatment Systems.

Municipal wastewater collection and treatment systems are critical infrastructures, and they are also identified as major sources of anthropogenic CH4 emissions that contribute to climate change. The actual CH4 emissions at the plant- or regional level vary greatly due to site-specific conditions as well as high seasonal and diurnal variations. Here, we conducted the first quantitative analysis of CH4 emissions from different types of sewers and water resource recovery facilities (WRRFs). We examined variations in CH4 emissions associated with methods applied in different monitoring campaigns, and identified main CH4 sources and sinks to facilitate carbon emission reduction efforts in the wastewater sector. We found plant-wide CH4 emissions vary by orders of magnitude, from 0.01 to 110 g CH4/m3 with high emissions associated with plants equipped with anaerobic digestion or stabilization ponds. Rising mains show higher dissolved CH4 concentrations than gravity sewers when transporting similar raw sewage under similar environmental conditions, but the latter dominates most collection systems around the world. Using the updated data sets, we estimated annual CH4 emission from the U.S. centralized, municipal wastewater treatment to be approximately 10.9 ± 7.0 MMT CO2-eq/year, which is about twice as the IPCC (2019) Tier 2 estimates (4.3-6.1 MMT CO2-eq/year). Given CH4 emission control will play a crucial role in achieving net zero carbon goals by the midcentury, more studies are needed to profile and mitigate CH4 emissions from the wastewater sector.

Pumping and sliding of droplets steered by a hydrogel pattern for atmospheric water harvesting.

Atmospheric water harvesting is an emerging strategy for decentralized and potable water supplies. However, water nucleation and microdroplet coalescence on condensing surfaces often result in surface flooding owing to the lack of a sufficient directional driving force for shedding. Herein, inspired by the fascinating properties of lizards and catfish, we present a condensing surface with engineered hydrogel patterns that enable rapid and sustainable water harvesting through the directional pumping and drag-reduced sliding of water droplets. The movement of microscale condensed droplets is synergistically driven by the surface energy gradient and difference in Laplace pressure induced by the arch hydrogel patterns. Meanwhile, the superhydrophilic hydrogel surface can strongly bond inner-layer water molecules to form a lubricant film that reduces drag and facilitates the sliding of droplets off the condensing surface. Thus, this strategy is promising for various water purification techniques based on liquid-vapor phase-change processes.