Good vibrations turbo charge green hydrogen production

PhD researcher Yemima Ehrnst holding the acoustic device the research team used to boost hydrogen production, through electrolysis to split water.
Photo Credit: RMIT University

They say their invention offers a promising way to tap into a plentiful supply of cheap hydrogen fuel for transportation and other sectors, which could radically reduce carbon emissions and help fight climate change.

By using high-frequency vibrations to “divide and conquer” individual water molecules during electrolysis, the team managed to split the water molecules to release 14 times more hydrogen compared with standard electrolysis techniques.

Electrolysis involves electricity running through water with two electrodes to split water molecules into oxygen and hydrogen gases, which appear as bubbles. This process produces green hydrogen, which represents just a small fraction of hydrogen production globally due to the high energy required.

Most hydrogen is produced from splitting natural gas, known as blue hydrogen, which emits greenhouse gases into the atmosphere.

Researcher takes aim at turning yellow into green by recycling urine

Urine recycling is the goal of WVU researcher Kevin Orner’s study of a wastewater treatment system that can attach directly to a toilet, extracting valuable nutrients used as fertilizers.
Illustration Credit: Sheree Wentz / West Virginia University

The waste flushed down toilets could be a valuable source of resources and profits — and easier on the environment, according to a West Virginia University engineer’s research.

Kevin Orner, a Benjamin M. Statler College of Engineering and Mineral Resources assistant professor is developing a technology that can treat urine on site rather than at a remote, centralized wastewater treatment facility. The technology could reside underneath a toilet, enabling urine treatment to happen quickly and promoting the recovery of nitrogen, a nutrient that can be sold as a fertilizer.

Orner’s findings, published in the journal Environmental Technology, make urine recycling more feasible in terms of integration into existing infrastructure and could reduce the amount of nutrients that enter lakes and rivers. Excessive nutrient discharge can put aquatic ecosystems at risk by promoting the growth of algae that consume dissolved oxygen in the water.

The goal is to transform waste collection and treatment from an environmentally harmful service that costs money to an environmentally beneficial service that makes money.

Hummingbird flight could provide insights for biomimicry in aerial vehicles

Hummingbirds have extreme aerial agility and flight forms, which is why many drones and other aerial vehicles are designed to mimic hummingbird movement. Using a novel modeling method, researchers gained new insights into how hummingbirds produce wing movement, which could lead to design improvements in flying robots.
Photo Credit: Zdeněk Macháček

Hummingbirds occupy a unique place in nature: They fly like insects but have the musculoskeletal system of birds. According to Bo Cheng, the Kenneth K. and Olivia J. Kuo Early Career Associate Professor in Mechanical Engineering at Penn State, hummingbirds have extreme aerial agility and flight forms, which is why many drones and other aerial vehicles are designed to mimic hummingbird movement. Using a novel modeling method, Cheng and his team of researchers gained new insights into how hummingbirds produce wing movement, which could lead to design improvements in flying robots.

Their results were published this week in the Proceedings of Royal Society B.

“We essentially reverse-engineered the inner working of the wing musculoskeletal system — how the muscles and skeleton work in hummingbirds to flap the wings,” said first author and Penn State mechanical engineering graduate student Suyash Agrawal. “The traditional methods have mostly focused on measuring activity of a bird or insect when they are in natural flight or in an artificial environment where flight-like conditions are simulated. But most insects and, among birds specifically, hummingbirds are very small. The data that we can get from those measurements are limited.”

Intricate ‘snowflakes’ created in liquid metal

A snowflake-like zinc crystal synthesized in liquid gallium by researchers at UNSW Sydney.
Image Credit: Dr Jianbo Tang

Researchers, including those from UNSW Sydney, have synthesized complex symmetrical zinc crystals in liquid gallium which can potentially be used in a range of catalysis applications.

It’s beginning to look a lot like Christmas at UNSW Sydney’s School of Chemical Engineering where researchers have grown crystals made of zinc that look like snowflakes - inside a liquid metal.

The team predominantly used zinc metal dissolved in liquid gallium as the solvent, creating distinctive structures that often resembled those of six-branched snowflake crystals.

Apart from their structural beauty, these liquid metal-grown crystals can enable future processes for making catalytic materials for producing hydrogen from organic fuels. The metallic crystals can also be specially formulated, during their synthesis and extraction, to make semiconductors for electronic and optical devices of computers, mobile phones and solar cells of the future.

Cities on asteroids? It could work—in theory

In what they deem a “wildly theoretical” paper, Rochester researchers imagine covering an asteroid in a flexible, mesh bag made of ultralight and high-strength carbon nanofibers as the key to creating human cities in space.
Illustration Credit: University of Rochester | Michael Osadciw

Rochester scientists use physics and engineering principles to show how asteroids could be future viable space habitats.

This past year, Jeff Bezos launched himself into space, while Elon Musk funded a space flight for a non-astronaut crew. Space collaborations between government and private entities, including Musk’s SpaceX and Bezos’s Blue Origin have become increasingly common. But with the recent emergence of the so-called “New Space” movement, aerospace companies are working to develop low-cost access to space for everyone, not only billionaires.

For a future beyond Earth, however, humans need places to accommodate homes, buildings, and other structures for millions of people to live and work.

Right now, space cities exist only in science fiction. But are space cities feasible in reality? And, if so, how?

According to new research from University of Rochester scientists, our future may lie in asteroids.

In what they deem a “wildly theoretical” paper published in the journal Frontiers in Astronomy and Space Sciences, the researchers, including Adam Frank, the Helen F. and Fred H. Gowen Professor of Physics and Astronomy, and Peter Miklavčič, a PhD candidate in mechanical engineering and the paper’s first author, outline a plan for creating large cities on asteroids.

Wearable sensor could guide precision drug dosing

 The sensor uses microneedles that are made by cutting down clinical-grade acupuncture needles.
Image Credit: Emaminejad Lab/UCLA

For some of the powerful drugs used to fight infection and cancer, there’s only a small difference between a healing dose and a dose that’s large enough to cause dangerous side effects. But predicting that margin is a persistent challenge because different people react differently to medications — even to the same dose.

Currently, doctors can calibrate the amount of medication they administer in part by drawing blood to test the amount of medicine in a patient’s body. But results from those tests often take a day to process and only measure dosage at one or two moments in time, so they don’t help much when determining how to adjust dosage amounts in real time.

Now, a UCLA-led research team has developed a wearable patch that uses inexpensive microneedles to analyze the fluid between cells less than a millimeter underneath the skin and continuously record concentrations of medicine in the body. The technology could be a step toward improving doctors’ ability to administer precise medication doses.

In a study published in Science Advances, the investigators tested the system in rats that had been treated with antibiotics. Using data taken by the device within about 15 minutes after the medication was administered, the researchers reliably forecast how much of that drug would be effectively delivered to the animal’s system in total.

It’s colossal: Creating the world’s largest dilution refrigerator

Colossus will offer 5 cubic meters of space and cool components to around 0.01K.
Photo Credit: Ryan Postel, Fermilab

While the refrigerator in your kitchen gets cold enough to prevent your leftovers from spoiling, dilution refrigerators used for quantum computing research cool devices near the coldest physical temperature possible. Now at the U.S. Department of Energy’s Fermi National Accelerator Laboratory, researchers are building Colossus: It will be the largest, most powerful refrigerator at millikelvin temperatures ever created.

Fermilab is known for its massive experiments, and Colossus will fit right in. Researchers from the Fermilab-hosted Superconducting Quantum Materials and Systems Center need lots of room at cold temperatures to achieve their goal of building a state-of-the-art quantum computer.

Unlike a kitchen refrigerator, which compresses gases called refrigerants to cool food, a dilution refrigerator uses a mixture of helium isotopes to create temperatures close to absolute zero, or zero kelvin: the coldest temperature imaginable in physics, which is physically impossible to reach.

“With the cooling power and volume that Colossus will provide, SQMS researchers will have unprecedented space for our future quantum computer and many other quantum computing and physics experiments,” said Matt Hollister, the lead technical expert on this project. “Colossus is named after the first electronic programmable computer, which was constructed in the 1940s for codebreaking. It was a historic milestone in the history of computing and seemed like an appropriate name for the size of our new refrigerator.”

Researchers propose new structures to harvest untapped source of freshwater

“Eventually, we will need to find a way to increase the supply of fresh water as conservation and recycled water from existing sources, albeit essential, will not be sufficient to meet human needs. We think our newly proposed method can do that at large scales,” said Illinois professor Praveen Kumar. The illustration shows Kumar and his co-authors’ proposed approach for capturing moisture above ocean surfaces and transporting it to land for condensation. 
Illustration Credit: Courtesy Praveen Kumar and Nature Scientific Reports

Researchers said that an almost limitless supply of fresh water exists in the form of water vapor above Earth’s oceans, yet remains untapped. A new study from the University of Illinois Urbana-Champaign is the first to suggest an investment in new infrastructure capable of harvesting oceanic water vapor as a solution to limited supplies of fresh water in various locations around the world.

The study, led by civil and environmental engineering professor and Prairie Research Institute executive director Praveen Kumar, evaluated 14 water-stressed locations across the globe for the feasibility of a hypothetical structure capable of capturing water vapor from above the ocean and condensing it into fresh water – and do so in a manner that will remain feasible in the face of continued climate change.

Kumar, graduate student Afeefa Rahman and atmospheric sciences professor Francina Dominguez published their findings in the journal Nature Scientific Reports.

Consortium develops sustainable aircraft engines

Flying without pollutant emissions should be possible in the future.
Photo Credit: RUB, Marquard

A new drive technology should make air travel possible with a clear conscience.

In the face of climate change, many people get on the plane with a guilty conscience: the emission of climate-damaging carbon dioxide from the combustion of fossil fuels is high. An international consortium wants to change this: The aim of the "MYTHOS" project is to develop aircraft engines that can flexibly use various sustainably produced fuels up to pure hydrogen. The project called "Medium-range hybrid low-pollution flexi-fuel / hydrogen sustainable engine" will start from 1. January 2023 funded by the European Union for four years. The coordination is carried out by Prof. Dr. Francesca di Mare, holder of the professorship for thermal turbo machines and aircraft engines of the RUB.

The overarching goal to which the project team is committed is nothing less than the decarbonization of aviation. "We will be developing and demonstrating a groundbreaking design methodology for future short and medium-range civil engines that can use a wide range of liquid and gaseous fuels and ultimately pure hydrogen," said Francesca di Mare. The fuels for which the engines are to be designed include so-called Sustainable Aviation Fuels, or SAF for short: sustainably produced fuels that are not based on fossil fuels. In order to achieve these goals, the MYTHOS consortium develops a multidisciplinary modeling approach for the characterization of the relevant engine components and uses methods of machine learning.

Researchers developed a new cancer testing method that makes regular monitoring affordable

Asst Prof Cheow Lih Feng (right), his former PhD student Dr Elsie Cheruba (left) and their team have developed the Heatrich-BS assay, an affordable and highly sensitive blood test for cancer. This new testing method has strong potential to be used in regular cancer monitoring.
Photo Credit: National University of Singapore

The S$50 blood test has high sensitivity, comparable to the gold standard CT scan

Scientists from the National University of (NUS) have discovered a novel low-cost method of testing for cancers. Called the Heatrich-BS assay, this new test sequences clinical samples that have been heated in order to isolate cancer-specific signatures found in a patient’s blood.

The new method provides a promising non-invasive alternative to tissue biopsies. It costs around S$50 from start to finish, compared to other sequencing methods that can cost up to S$1,000 to conduct. Led by Assistant Professor Cheow Lih Feng, the team comprising researchers from the NUS Department of Biomedical Engineering under the College of Design and Engineering as well as the NUS Institute for Health Innovation & Technology, is now exploring industry partnerships to bring their technology to market.

“When you have a S$50 test, it opens up a lot of avenues because it is affordable, so you can do the test quite regularly,” said Asst Prof Cheow, pointing to the potential for their assay to be used in regular cancer monitoring.

Researchers Develop Strategy to Thermally Stabilize Microneedle Vaccine Technology

Visual of the researcher's microneedle vaccine technology concept.
Illustration Credit: Thahn Nguyen

Researchers use sugar molecules to help eliminate the need for cold-chain storage, a common logistical hurdle for vaccine distribution

Researchers in the Department of Biomedical Engineering —a shared department between the UConn Schools of Dental Medicine, Medicine, and Engineering—unlocked a new strategy using sugar molecules to thermally stabilize their existing microneedle vaccine technology, eliminating the need for cold-chain storage.

Associate Professor Thanh Duc Nguyen from the Departments of Mechanical Engineering and Biomedical Engineering in the School of Engineering, reported this new development in a recent issue of Advanced Materials Technology. The work was led by Dr. Khanh Tran, Nguyen’s former UConn Ph.D. student currently at the Massachusetts Institute of Technology, and Dr. Tyler Gavitt, former UConn Ph.D. student currently at Duke University. Gavitt was a student of Associate Professor Steven Szczepanek in the Department of Pathobiology and Veterinary Science in the College of Agriculture, Health, and Natural Resources at UConn.

Typically, vaccinations against infectious diseases like COVID-19 require multiple painful, expensive and inconvenient injections, including a prime and several booster shots. The UConn researcher’s technology creates a self-administered microneedle patch which could be self-administered and only requires a single-time administration into skin—similar to a nicotine patch—to perform a release profile of vaccines, simulating the effect of multiple injections.

Better Than a Hole in the Head

Just as blood pressure informs heart health, intracranial pressure (ICP) helps indicate brain health. ICP sensing is the burgeoning focus of Jana Kainerstorfer's biomedical optics lab at Carnegie Mellon University. Her team is working to modernize ICP sensing approaches, which historically have been invasive and risky. Their noninvasive alternatives will ease the risk of infection, pain and medical expenses, as well as present new monitoring capabilities for patients with an array of brain injuries and conditions, from stroke to hydrocephalus.

Investigating pressure levels in the brain is a laborious task for health professionals and hasn't progressed much since the 1960s. Current practice involves drilling a hole into a patient's skull and placing a probe inside for continuous monitoring of ICP levels. It comes with the risk of infection and damaging the brain itself, and while valuable data is to have, ICP measurement is reserved only for the most critical of situations.

"At the core of it, what we've done is build a sensor alternative that doesn't require drilling a hole into the patient's head," said Kainerstorfer, an associate professor of biomedical engineering. "We recently published two papers that explore the use of optical sensors on the forehead for noninvasive ICP monitoring, using near-infrared spectroscopy and diffuse correlation spectroscopy. Both approaches represent huge strides in improving the patient experience and providing better tools to monitor pressure levels in the brain, which can be a key variable in both diagnosis and treatment decisions."

To track disease-carrying mosquitoes, researchers tag them with DNA barcodes

 The researchers at a field site in Fort Collins, Colorado collecting mosquitoes for analysis.
Photo Credit: Rebekah Kading/Colorado State University

West Nile, Zika, dengue and malaria are all diseases spread by bites from infected mosquitoes. To track the threat of such diseases over large populations, scientists need to know where the mosquitoes are, where they’ve been, and where they might go.

But take it from Rebekah Kading, a Colorado State University researcher who studies mosquito-borne arboviruses: tracking mosquitoes is no easy task. The capture, tagging and release of single mosquitoes – as is commonly done with bats and other disease carriers – would be ridiculous, if not impossible. A common mosquito-tracking technique involves dousing the insects in fluorescent powder and letting them fly away, but the practice is error-prone and unreliable.

Thanks to a collaboration with CSU engineers, Kading and colleagues are introducing a better way to perform mosquito-tracking for disease applications. Their new method, which involves getting larval mosquitoes to eat harmless particles made entirely of DNA and proteins, has the potential to revolutionize how people study mosquito-borne diseases.

The edible mosquito marker particles are the work of Chris Snow, associate professor in the Department of Chemical and Biological Engineering. For the last several years, Snow’s team has been developing microscopic, porous protein crystals that self-assemble from a protein originally found in Camplyobacter jejuni bacteria. Since inventing these very small, non-toxic protein crystals that feature highly precise arrays of pores, Snow’s team has been exploring diverse applications for them, like capturing virus particles to facilitate wastewater testing.

Machine learning model builds on imaging methods to better detect ovarian lesions

(From left) The top row shows an ultrasound image of a malignant lesion, the blood oxygen saturation, and hemoglobin concentration. The bottom row is an ultrasound image of a benign lesion, the blood oxygen saturation, and hemoglobin concentration.
Image Credit: Zhu lab

Although ovarian cancer is the deadliest type of cancer for women, only about 20% of cases are found at an early stage, as there are no real screening tests for them and few symptoms to prompt them. Additionally, ovarian lesions are difficult to diagnose accurately — so difficult, in fact that there is no sign of cancer in more than 80% of women who undergo surgery to have lesions removed and tested.

Quing Zhu, the Edwin H. Murty Professor of Biomedical Engineering at Washington University in St. Louis’ McKelvey School of Engineering, and members of her lab have applied a variety of imaging methods to diagnose ovarian cancer more accurately. Now, they have developed a new machine learning fusion model that takes advantage of existing ultrasound features of ovarian lesions to train the model to recognize whether a lesion is benign or cancerous from reconstructed images taken with photoacoustic tomography. Machine learning traditionally has been focused on single modality data. Recent findings have shown that multi-modality machine learning is more robust in its performance over unimodality methods. In a pilot study of 35 patients with more than 600 regions of interest, the model’s accuracy was 90%.

New device can control light at unprecedented speeds

Scientists have developed a programmable, wireless spatial light modulator that can manipulate light at the wavelength scale with orders-of-magnitude faster response than existing devices.
Illustration Credit: Sampson Wilcox

In a scene from “Star Wars: Episode IV — A New Hope,” R2D2 projects a three-dimensional hologram of Princess Leia making a desperate plea for help. That scene, filmed more than 45 years ago, involved a bit of movie magic — even today, we don’t have the technology to create such realistic and dynamic holograms.

Generating a freestanding 3D hologram would require extremely precise and fast control of light beyond the capabilities of existing technologies, which are based on liquid crystals or micromirrors.

An international group of researchers, led by a team at MIT, spent more than four years tackling this problem of high-speed optical beam forming. They have now demonstrated a programmable, wireless device that can control light, such as by focusing a beam in a specific direction or manipulating the light’s intensity, and do it orders of magnitude more quickly than commercial devices.

They also pioneered a fabrication process that ensures the device quality remains near-perfect when it is manufactured at scale. This would make their device more feasible to implement in real-world settings.

Rice lab’s catalyst could be key for hydrogen economy

Rice University researchers have engineered a key light-activated nanomaterial for the hydrogen economy. Using only inexpensive raw materials, a team from Rice’s Laboratory for Nanophotonics, Syzygy Plasmonics Inc. and Princeton University’s Andlinger Center for Energy and the Environment created a scalable catalyst that needs only the power of light to convert ammonia into clean-burning hydrogen fuel.

The research is published in the journal Science.

The research follows government and industry investment to create infrastructure and markets for carbon-free liquid ammonia fuel that will not contribute to greenhouse warming. Liquid ammonia is easy to transport and packs a lot of energy, with one nitrogen and three hydrogen atoms per molecule. The new catalyst breaks those molecules into hydrogen gas, a clean-burning fuel, and nitrogen gas, the largest component of Earth’s atmosphere. And unlike traditional catalysts, it doesn’t require heat. Instead, it harvests energy from light, either sunlight or energy-stingy LEDs.

The pace of chemical reactions typically increases with temperature, and chemical producers have capitalized on this for more than a century by applying heat on an industrial scale. The burning of fossil fuels to raise the temperature of large reaction vessels by hundreds or thousands of degrees results in an enormous carbon footprint. Chemical producers also spend billions of dollars each year on thermocatalysts — materials that don’t react but further speed reactions under intense heating.

Improving AI training for edge sensor time series

Engineers at the Tokyo Institute of Technology (Tokyo Tech) have demonstrated a simple computational approach for improving the way artificial intelligence classifiers, such as neural networks, can be trained based on limited amounts of sensor data. The emerging applications of the internet of things often require edge devices that can reliably classify behaviors and situations based on time series. However, training data is difficult and expensive to acquire. The proposed approach promises to substantially increase the quality of classifier training, at almost no extra cost.

In recent times, the prospect of having huge numbers of Internet of Things (IoT) sensors quietly and diligently monitoring countless aspects of human, natural, and machine activities has gained ground. As our society becomes more and more hungry for data, scientists, engineers, and strategists increasingly hope that the additional insight which we can derive from this pervasive monitoring will improve the quality and efficiency of many production processes, also resulting in improved sustainability.

The world in which we live is incredibly complex, and this complexity is reflected in a huge multitude of variables that IoT sensors may be designed to monitor. Some are natural, such as the amount of sunlight, moisture, or the movement of an animal, while others are artificial, for example, the number of cars crossing an intersection or the strain applied to a suspended structure like a bridge. What these variables all have in common is that they evolve over time, creating what is known as time series, and that meaningful information is expected to be contained in their relentless changes. In many cases, researchers are interested in classifying a set of predetermined conditions or situations based on these temporal changes, as a way of reducing the amount of data and making it easier to understand. For instance, measuring how frequently a particular condition or situation arises is often taken as the basis for detecting and understanding the origin of malfunctions, pollution increases, and so on.

New CRISPR-based tool inserts large DNA sequences at desired sites in cells

Building on the CRISPR gene-editing system, MIT researchers designed a new tool that can snip out faulty genes and replace them with new ones.
Image Credit: Sangharsh Lohakare

Building on the CRISPR gene-editing system, MIT researchers have designed a new tool that can snip out faulty genes and replace them with new ones, in a safer and more efficient way.

Using this system, the researchers showed that they could deliver genes as long as 36,000 DNA base pairs to several types of human cells, as well as to liver cells in mice. The new technique, known as PASTE, could hold promise for treating diseases that are caused by defective genes with a large number of mutations, such as cystic fibrosis.

“It’s a new genetic way of potentially targeting these really hard to treat diseases,” says Omar Abudayyeh, a McGovern Fellow at MIT’s McGovern Institute for Brain Research. “We wanted to work toward what gene therapy was supposed to do at its original inception, which is to replace genes, not just correct individual mutations.”

The new tool combines the precise targeting of CRISPR-Cas9, a set of molecules originally derived from bacterial defense systems, with enzymes called integrases, which viruses use to insert their own genetic material into a bacterial genome.

The whole in a part: Synchronizing chaos through a narrow slice of spectrum

Conceptual overview of the coupling scheme between a master and a slave chaotic oscillator via a band-pass filter, and the resulting complex interdependence between their activities.
Credit: Tokyo Institute of Technology

Engineers at the Tokyo Institute of Technology (Tokyo Tech) have uncovered some intricate effects arising when chaotic systems, which typically generate broad spectra, are coupled by conveying only a narrow range of frequencies from one to another. The synchronization of chaotic oscillators, such as electronic circuits, continues to attract considerable fascination due to the richness of the complex behaviors that can emerge. Recently, hypothetical applications in distributed sensing have been envisaged, however, wireless couplings are only practical over narrow frequency intervals. The proposed research shows that, even under such constraints, chaos synchronization can occur and give rise to phenomena that could one day be leveraged to realize useful operations over ensembles of distant nodes.

The abstract notion that the whole can be found in each part of something has for long fascinated thinkers engaged in all walks of philosophy and experimental science: from Immanuel Kant on the essence of time to David Bohm on the notion of order, and from the self-similarity of fractal structures to the defining properties of holograms. It has, however, remained understandably extraneous to electronic engineering, which strives to develop ever more specialized and efficient circuits exchanging signals that possess highly controlled characteristics. By contrast, across the most diverse complex systems in nature, such as the brain, the generation of activity having features that present themselves similarly over different temporal scales, or frequencies, is nearly a ubiquitous observation.

Engineers improve electrochemical sensing by incorporating machine learning

Aida Ebrahimi, Thomas and Sheila Roell Early Career Assistant Professor of Electrical Engineering and assistant professor of biomedical engineering, and Vinay Kammarchedu, 2022-23 Milton and Albertha Langdon Memorial Graduate Fellowship in Electrical Engineering, developed a new approach to improve the performance of electrochemical biosensors by combining machine learning with multimodal measurement.
Photo Credit: Kate Myers | Pennsylvania State University

Combining machine learning with multimodal electrochemical sensing can significantly improve the analytical performance of biosensors, according to new findings from a Penn State research team. These improvements may benefit noninvasive health monitoring, such as testing that involves saliva or sweat. The findings were published this month in Analytica Chimica Acta.

The researchers developed a novel analytical platform that enabled them to selectively measure multiple biomolecules using a single sensor, saving space and reducing complexity as compared to the usual route of using multi-sensor systems. In particular, they showed that their sensor can simultaneously detect small quantities of uric acid and tyrosine — two important biomarkers associated with kidney and cardiovascular diseases, diabetes, metabolic disorders, and neuropsychiatric and eating disorders — in sweat and saliva, making the developed method suitable for personalized health monitoring and intervention.

Many biomarkers have similar molecular structures or overlapping electrochemical signatures, making it difficult to detect them simultaneously. Leveraging machine learning for measuring multiple biomarkers can improve the accuracy and reliability of diagnostics and as a result improve patient outcomes, according to the researchers. Further, sensing using the same device saves resources and biological sample volumes needed for tests, which is critical with clinical samples with scarce amounts.