Improving the Hydrophobicity of Powder Activated Carbon to Enhance the Adsorption Kinetics of Per- and Polyfluoroalkyl Substances.

Per- and polyfluoroalkyl substances (PFAS) are difficult to treat by using conventional drinking water treatment technologies. Herein, we upgrade a commercially available powder activated carbon (PAC) via an acid wash and pyrolysis to amplify hydrophobicity and enhance PFAS adsorption. Minimal differences in overall surface area, micropore volume and area, and external surface area were observed between acid-washed and pyrolyzed PACs.

Screening Environmentally Benign Ionic Liquids for CO Absorption Using Representation Uncertainty-Based Machine Learning.

Screening ionic liquids (ILs) with low viscosity, low toxicity, and high CO absorption using machine learning (ML) models is crucial for mitigating global warming. However, when candidate ILs fall into the extrapolation zone of ML models, predictions may become unreliable, leading to poor decision-making. In this study, we introduce a "representation uncertainty" (RU) approach to quantify prediction uncertainty by employing four IL representations: molecular fingerprint, molecular descriptor, molecular image, and molecular graph.

Real-Time Sensor Data Profile-Based Deep Learning Method Applied to Open Raceway Pond Microalgal Productivity Prediction.

Microalgal biotechnology holds the potential for renewable biofuels, bioproducts, and carbon capture applications due to unparalleled photosynthetic efficiency and diversity. Outdoor open raceway pond (ORP) cultivation enables utilization of sunlight and atmospheric carbon dioxide to drive microalgal biomass synthesis for production of bioproducts including biofuels; however, environmental conditions are highly dynamic and fluctuate both diurnally and seasonally, making ORP productivity prediction challenging without time-intensive physical measurements and location-specific calibrations. Here, for the first time, we present an image-based deep learning method for the prediction of ORP productivity.

The Minus Approach Can Redefine the Standard of Practice of Drinking Water Treatment.

Chlorine-based disinfection for drinking water treatment (DWT) was one of the 20th century's great public health achievements, as it substantially reduced the risk of acute microbial waterborne disease. However, today's chlorinated drinking water is not unambiguously safe; trace levels of regulated and unregulated disinfection byproducts (DBPs), and other known, unknown, and emerging contaminants (KUECs), present chronic risks that make them essential removal targets. Because conventional chemical-based DWT processes do little to remove DBPs or KUECs, alternative approaches are needed to minimize risks by removing DBP precursors and KUECs that are ubiquitous in water supplies.

Revolutionizing Membrane Design Using Machine Learning-Bayesian Optimization.

Polymeric membrane design is a multidimensional process involving selection of membrane materials and optimization of fabrication conditions from an infinite candidate space. It is impossible to explore the entire space by trial-and-error experimentation. Here, we present a membrane design strategy utilizing machine learning-based Bayesian optimization to precisely identify the optimal combinations of unexplored monomers and their fabrication conditions from an infinite space.

Use of Copper to Selectively Inhibit Brachionus calyciflorus (Predator) Growth in Chlorella kessleri (Prey) Mass Cultures for Algae Biodiesel Production.

A single Brachionus rotifer can consume thousands of algae cells per hour causing an algae pond to crash within days of infection. Thus, there is a great need to reduce rotifers in order for algal biofuel production to become reality. Copper can selectively inhibit rotifers in algae ponds, thereby protecting the algae crop.

Effect of centrifugation on water recycling and algal growth to enable algae biodiesel production.

The latest research shows that algal biofuels, at the production levels mandated in the Energy Independence and Security Act of 2007, will place significant demands on water and compete with agriculture meant for food production. Thus, there is a great need to recycle water while producing algal biofuels. This study shows that when using a synthetic medium, soluble algal products, bacteria, and other inhibitors can be removed by centrifugation and enable water recycling.