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Advanced Membrane Science and Technology for Water and Wastewater Treatment

The pressing need for clean and affordable drinking water is intensifying as global populations rise and pollutants increasingly compromise available water sources. Traditional methods of water purification, while effective, are often insufficient to address the complex array of contaminants now present in water, including microorganisms, organic compounds, and heavy metals. Over the past four decades, significant breakthroughs in water and wastewater treatment have been achieved through the application of nanotechnology, particularly in the development of nanomaterials and nanomembranes. These science and technology advancements have revolutionized membrane-based water and wastewater treatment, offering new levels of efficiency and precision in removing a wide range of pollutants.

This Collection aims to advance our understanding of membrane-based water and wastewater treatment, underlining the challenges and opportunities within this rapidly evolving field, e.g., the limitations of conventional ultrafiltration and microfiltration membrane systems, such as their reduced effectiveness in removing certain trace organic compounds (TrOCs) and the persistent issues of membrane fouling and salinity build-up. The Collection seeks to explore innovative solutions, e.g., high-retention membrane bioreactors (HR-MBRs) and advanced pre-treatment options like advanced oxidation processes (AOPs), which have the potential to significantly improve the effectiveness and sustainability of water and wastewater treatment processes.

Moreover, the Collection emphasizes the importance of developing sustainable materials, such as biopolymers, which can replace traditional synthetic polymers in membrane fabrication. While these materials offer eco-friendly alternatives with unique adsorption properties, their performance can vary based on source and processing methods, presenting challenges in terms of durability and scalability. The Collection also aims to showcase advancements in PVDF-based membranes, which are gaining popularity due to their superior mechanical and chemical properties, and to examine the integration of these materials in innovative membrane technologies, e.g., membrane distillation (MD) and hybrid systems.

Pinning down protons in water—a basic science success story

The movement of protons through electrically charged water is one of the most fundamental processes in chemistry. It is evident in everything from eyesight to energy storage to rocket fuel—and scientists have known about it for more than 200 years.

But no one has ever seen it happen. Or precisely measured it on a microscopic scale.

Now, the Mark Johnson lab at Yale has—for the first time—set benchmarks for how long it takes protons to move through six charged . The discovery, made possible with a highly customized mass spectrometer that has taken years to refine, could have far-reaching applications for researchers in years to come.

Misinformation and distrust in science — with Naomi Oreskes

Find out how organisations like tobacco and fossil fuel companies sell doubt about science, in order to undermine public trust.

You can watch Naomi’s recent talk about the origin of the plate tectonics theory here: • Rethinking the origin of plate tectonics -… and if you sign up as one of our Science Supporters, see the full Q&A here: • Q&A: Rethinking the origin of plate tecton…

Buy Naomi’s book ‘Merchants of Doubt: How a Handful of Scientists Obscured the Truth on Issues from Tobacco Smoke to Global Warming’ here: https://geni.us/orTZL9D

00:00 Introduction.
0:41 Why do bad actors work to create mistrust in science?
2:26 How do bad actors create mistrust in science?
3:24 How does the fossil fuel industry create mistrust?
5:04 How can we rebuild trust in science and government?
7:50 Does it matter who funds science?
11:52 What role does government regulation play in science?
14:01 How does the concept of freedom affect the climate debate?

Naomi Oreskes is Professor of the History of Science and Affiliated Professor of Earth and Planetary Sciences at Harvard University. She has worked on studies of geophysics, climate change and the history of science. She sits on the board of US based not-for-profit organisations the National Center for Science Education and Climate Science Legal Defense Fund. She is a distinguished speaker and has published 10 books, including Science on a Mission and The Big Myth.

The Ri is on Twitter: / ri_science.

Continue reading “Misinformation and distrust in science — with Naomi Oreskes” | >

College of Science | researcher proposes first-time model that replaces dark energy and dark matter in explaining nature of the universe | The University of Alabama in Huntsville

Dr. Richard Lieu, a physics professor at The University of Alabama in Huntsville (UAH), a part of The University of Alabama System, has published a paper in the journal Classical and Quantum Gravity that proposes a universe built on steps of multiple singularities rather than the Big Bang alone to account for the expansion of the cosmos. The new model forgoes the need for either dark matter or dark energy as explanations for the universe’s acceleration and how structures like galaxies are generated.

The researcher’s work builds on an earlier model hypothesizing gravity can exist without mass that has garnered 41,000 reads and numerous citations since its publication in 2024.

BEAST-GB model combines machine learning and behavioral science to predict people’s decisions

A key objective of behavioral science research is to better understand how people make decisions in situations where outcomes are unknown or uncertain, which entail a certain degree of risk.

The ability to predict people’s choices in these situations could be highly advantageous, as it could help to draft effective initiatives aimed at prompting people to make better decisions for themselves and others in their community.

Researchers at Technion (Israel Institute of Technology) and various institutes in the United States recently developed a new computational model called BEAST-GB, which was found to predict people’s decisions in situations that entail risk and uncertainty.

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