Tiny plastic particles are found everywhere

The researchers were out in the southern Arctic Ocean on the research vessel Polarstern and took water samples, which they analyzed for the smallest microplastic particles.
Photo Credit: Clara Leistenschneider, University of Basel

Microplastic particles can be found in the most remote ocean regions on earth. In Antarctica, pollution levels are even higher than previously assumed. This is one finding of a recent study involving researchers from the University of Basel.

It’s not the first study on microplastics in Antarctica that researchers from the University of Basel and the Alfred-Wegener Institute (AWI) have conducted. But analysis of the data from an expedition in spring 2021 shows that environmental pollution from these tiny plastic particles is a bigger problem in the remote Weddell Sea than was previously known.

The total of 17 seawater samples all indicated higher concentrations of microplastics than in previous studies. “The reason for this is the type of sampling we conducted,” says Clara Leistenschneider, doctoral candidate in the Department of Environmental Sciences at the University of Basel and lead author of the study.

The current study focused on particles measuring between 11 and 500 micrometers in size. The researchers collected them by pumping water into tanks, filtering it, and then analyzing it using infrared spectroscopy. Previous studies in the region had mostly collected microplastic particles out of the ocean using fine nets with a mesh size of around 300 micrometers. Smaller particles would simply pass through these plankton nets.

The results of the new study indicate that 98.3 percent of the plastic particles present in the water were smaller than 300 micrometers, meaning that they were not collected in previous samples. “Pollution in the Antarctic Ocean goes far beyond what was reported in past studies,” Leistenschneider notes. The study appears in the journal Science of the Total Environment.

Deep parts of Great Barrier Reef ‘insulated’ from global warming – for now

Mesophotic corals on the Great Barrier Reef.
Photo Credit Prof Peter Mumby

Some deeper areas of the Great Barrier Reef are insulated from harmful heatwaves – but that protection will be lost if global warming continues, according to new research.

High surface temperatures have caused mass “bleaching” of the Great Barrier Reef in five of the last eight years, with the latest happening now.

Climate change projections for coral reefs are usually based on sea surface temperatures, but this overlooks the fact that deeper water does not necessarily experience the same warming as that at the surface.

The new study – led by the universities of Exeter and Queensland – examined how changing temperatures will affect mesophotic corals (depth 30-50 meters).

It found that separation between warm buoyant surface water and cooler deeper water can insulate reefs from surface heatwaves, but this protection will be lost if global warming exceeds 3°C above pre-industrial levels.

The researchers say similar patterns could occur on other reefs worldwide, but local conditions affecting how the water moves and mixes will mean the degree to which deeper water coral refuges exist and remain insulated from surface heatwaves will vary.

“Coral reefs are the canary in the coalmine, warning us of the many species and ecosystems affected by climate change,” said Dr Jennifer McWhorter, who led the research during a QUEX PhD studentship at the universities of Exeter and Queensland.

Finding New Chemistry to Capture Double the Carbon

An established carbon capture solvent can form clusters that could significantly increase the amount of carbon dioxide stored. 
Credits: Photo by Andrea Starr; Composite Graphic by Cortland Johnson
Pacific Northwest National Laboratory

Finding ways to capture, store, and use carbon dioxide (CO2) remains an urgent global problem. As temperatures continue to rise, keeping CO2 from entering the atmosphere can help limit warming where carbon-based fuels are still needed.

Significant progress has been made in creating affordable, practical carbon capture technologies. Carbon-capturing liquids, referred to as solvents when they are present in abundance, can efficiently grab CO2 molecules from coal-fired power plants, paper mills, and other emission sources. However, these all work through the same fundamental chemistry. Or so researchers assumed.

In a new work published in Nature Chemistry, scientists were surprised to find that a familiar solvent is even more promising than originally anticipated. New details about the solvent’s underlying structure suggest that the liquid could hold twice as much CO2 as previously thought. The newly revealed structure could also hold the key to creating a suite of carbon-based materials that could help keep even more CO2 out of the atmosphere.

The Pacific Northwest National Laboratory (PNNL) team developed the solvent several years ago and has studied it in a variety of scenarios. The team has worked to dial down the costs of using the solvent and turn up its efficiency. Last year, they revealed the least costly carbon capture system to date. It was during this research that the team noticed something odd.

MIT engineers design flexible “skeletons” for soft, muscle-powered robots

MIT engineers have developed a new spring (shown in Petri dish) that maximizes the work of natural muscles. When living muscle tissue is attached to posts at the corners of the device, the muscle’s contractions pull on the spring, forming an effective, natural actuator. The spring can serve as a “skeleton” for future muscle-powered robots.
Photo Credit: Felice Frankel
(CC BY-NC-ND 4.0 DEED)

Our muscles are nature’s perfect actuators — devices that turn energy into motion. For their size, muscle fibers are more powerful and precise than most synthetic actuators. They can even heal from damage and grow stronger with exercise.

For these reasons, engineers are exploring ways to power robots with natural muscles. They’ve demonstrated a handful of “biohybrid” robots that use muscle-based actuators to power artificial skeletons that walk, swim, pump, and grip. But for every bot, there’s a very different build, and no general blueprint for how to get the most out of muscles for any given robot design.

Now, MIT engineers have developed a spring-like device that could be used as a basic skeleton-like module for almost any muscle-bound bot. The new spring, or “flexure,” is designed to get the most work out of any attached muscle tissues. Like a leg press that’s fit with just the right amount of weight, the device maximizes the amount of movement that a muscle can naturally produce.

The researchers found that when they fit a ring of muscle tissue onto the device, much like a rubber band stretched around two posts, the muscle pulled on the spring, reliably and repeatedly, and stretched it five times more, compared with other previous device designs.

The team sees the flexure design as a new building block that can be combined with other flexures to build any configuration of artificial skeletons. Engineers can then fit the skeletons with muscle tissues to power their movements.

Boreal forest and tundra regions worst hit over next 500 years of climate change, study shows

The boreal forest is the Earth's most significant provider of carbon storage and clean water
Photo Credit: Landon Parenteau

The boreal forest, covering much of Canada and Alaska, and the treeless shrublands to the north of the forest region, may be among the worst impacted by climate change over the next 500 years, according to a new study.

The study, led by researchers at the White Rose universities of York and Leeds, as well as Oxford and Montreal, and ETH, Switzerland, ran a widely-used climate model with different atmospheric concentrations of carbon dioxide to assess the impact climate change could have on the distribution of ecosystems across the planet up to the year 2500.

Most climate prediction models run to the year 2100, but researchers are keen to explore longer-term projections that give a global picture of how much humans, animals and plant-life may need to adapt to climate change beyond the next century, which is important as long-lived trees adapt at scales of centuries rather than decades.

First-of-its-kind integrated dataset enables genes-to-ecosystems research

DOE national laboratory scientists led by Oak Ridge National Laboratory have developed the first tree dataset of its kind, bridging molecular information about the poplar tree microbiome to ecosystem-level processes.
Illustration Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

The first-ever dataset bridging molecular information about the poplar tree microbiome to ecosystem-level processes has been released by a team of Department of Energy scientists led by Oak Ridge National Laboratory. The project aims to inform research regarding how natural systems function, their vulnerability to a changing climate, and ultimately how plants might be engineered for better performance as sources of bioenergy and natural carbon storage.

The data, described in Nature Publishing Group’s Scientific Data, provides in-depth information on 27 genetically distinct variants, or genotypes, of Populus trichocarpa, a poplar tree of interest as a bioenergy crop. The genotypes are among those that the ORNL-led Center for Bioenergy Innovation previously included in a genome-wide association study linking genetic variations to the trees’ physical traits. ORNL researchers collected leaf, soil and root samples from poplar fields in two regions of Oregon — one in a wetter area subject to flooding and the other drier and susceptible to drought. 

Details in the newly integrated dataset range from the trees’ genetic makeup and gene expression to the chemistry of the soil environment, analysis of the microbes that live on and around the trees and compounds the plants and microbes produce.

The dataset “is unprecedented in its size and scope,” said ORNL Corporate Fellow Mitchel Doktycz, section head for Bioimaging and Analytics and project co-lead. “It is of value in answering many different scientific questions.” By mining the data with machine learning and statistical approaches, scientists can better understand how the genetic makeup, physical traits and chemical diversity of Populus relate to processes such as cycling of soil nitrogen and carbon, he said. 

Researchers develop better way to make painkiller from trees

Steven Karlen, left, and Vitaliy Tymokhin, scientists with the Great Lakes Bioenergy Research Center, examine a reactor used to convert chemicals in poplar trees into paracetamol, the active ingredient in Tylenol.
Photo Credit: Chelsea Mamott

Scientists at the University of Wisconsin–Madison have developed a cost-effective and environmentally sustainable way to make a popular pain reliever and other valuable products from plants instead of petroleum.

Building on a previously patented method for producing paracetamol – the active ingredient in Tylenol – the discovery promises a greener path to one of the world’s most widely used medicines and other chemicals. More importantly, it could provide new revenue streams to make cellulosic biofuels — derived from non-food plant fibers — cost competitive with fossil fuels, the primary driver of climate change.

“We did the R&D to scale it and make it realizable,” says Steven Karlen, a staff scientist at the Great Lakes Bioenergy Research Center who led the research published recently in the journal ChemSusChem.

Paracetamol, also known as acetaminophen, is one of the most widely used pharmaceuticals, with a global market value of about $130 million a year. Since it was introduced in the early 1900s, the drug has traditionally been made from derivatives of coal tar or petroleum.

Fueling nerve cell function and plasticity

The picture shows neurons (magenta) born in the adult mouse hippocampus. Nuclei are stained cyan. The extending dendrites are important sites where mechanisms of plasticity and competition for survival take place.
Photo Credit: Courtesy of ©Bergami Lab / University of Cologne

New finding from scientists at the University of Cologne discloses how mitochondria control tissue rejuvenation and synaptic plasticity in the adult mouse brain

Nerve cells (neurons) are amongst the most complex cell types in our body. They achieve this complexity during development by extending ramified branches called dendrites and axons and establishing thousands of synapses to form intricate networks. The production of most neurons is confined to embryonic development, yet few brain regions are exceptionally endowed with neurogenesis throughout adulthood. It is unclear how neurons born in these regions successfully mature and remain competitive to exert their functions within a fully formed organ. However, understanding these processes holds great potential for brain repair approaches during disease.

A team of researchers led by Professor Dr Matteo Bergami at the University of Cologne’s CECAD Cluster of Excellence in Aging Research addressed this question in mouse models, using a combination of imaging, viral tracing and electrophysiological techniques. They found that, as new neurons mature, their mitochondria (the cells’ power houses) along dendrites undergo a boost in fusion dynamics to acquire more elongated shapes. This process is key in sustaining the plasticity of new synapses and refining pre-existing brain circuits in response to complex experiences. The study ‘Enhanced mitochondrial fusion during a critical period of synaptic plasticity in adult-born neurons’ has been published in the journal Neuron.

Kerr-Enhanced Optical Spring for Next-Generation Gravitational Wave Detectors

A novel technique for enhancing optical spring that utilizes the Kerr effect to improve the sensitivity of gravitational wave detectors (GWDs) has recently been developed by scientists at Tokyo Tech. This innovative design uses optical non-linear effects from the Kerr effect in the Fabry-Perot cavity to achieve high signal amplification ratios and optical spring constant, with potential applications in not only GWDs but also in a range of optomechanical systems.

The detection of gravitational waves stands as one of the most significant achievements in modern physics. In 2017, gravitational waves from the merger of a binary neutron star were detected for the first time which uncovered crucial information about our universe, from the origin of short gamma-ray bursts to the formation of heavy elements. However, detecting gravitational waves emerging from post-merger remnants has remained elusive due to their frequency range lying outside the range of modern gravitational wave detectors (GWDs). These elusive waves hold important insights into the internal structure of neutron stars, and since these waves can be observed once every few decades by modern GWDs, there is an urgent need for next-generation GWDs.

One way to enhance the sensitivity of GWDs is signal amplification using an optical spring. Optical springs, unlike their mechanical counterparts, leverage radiation pressure force from light to mimic spring-like behavior. The stiffness of optical springs, such as in GWDs, is determined by the light power within the optical cavity. Thus, enhancing the resonant frequency of optical springs requires increasing the intracavity light power which, however, can result in thermally harmful effects and prevent the detector from working properly.

This 3D printer can figure out how to print with an unknown material

Researchers developed a 3D printer that can automatically identify the parameters of an unknown material on its own.
Photo Credit: Courtesy of the researchers
(CC BY-NC-ND 4.0 DEED)

While 3D printing has exploded in popularity, many of the plastic materials these printers use to create objects cannot be easily recycled. While new sustainable materials are emerging for use in 3D printing, they remain difficult to adopt because 3D printer settings need to be adjusted for each material, a process generally done by hand.

To print a new material from scratch, one must typically set up to 100 parameters in software that controls how the printer will extrude the material as it fabricates an object. Commonly used materials, like mass-manufactured polymers, have established sets of parameters that were perfected through tedious, trial-and-error processes.

But the properties of renewable and recyclable materials can fluctuate widely based on their composition, so fixed parameter sets are nearly impossible to create. In this case, users must come up with all these parameters by hand.

Researchers tackled this problem by developing a 3D printer that can automatically identify the parameters of an unknown material on its own.