Scientists at Nanyang Technological University, Singapore (NTU Singapore) have developed a 3D concrete printing method that captures carbon, demonstrating a new pathway to reduce the environmental impact of the construction industry. The innovative method aims to significantly reduce the carbon footprint of cement — a material responsible for 1.6 billion metric tonnes of carbon dioxide (CO2) or about eight per cent of global CO2 emissions — through lower material usage, reduced construction time, and labour requirements. The newly developed 3D concrete printing process involves injecting steam and CO2, captured as the by-products of industrial processes, into the mixing concrete, which then directly incorporates and stores the CO2 in the concrete structure. Results have showed that the CO2 and steam injection method improved the mechanical properties of the concrete, offering increased strength compared to conventional 3D printed concrete. Principal investigator of the study said, “The building and construction sector causes a significant portion of global greenhouse gas emissions. Our newly developed 3D concrete printing system offers a carbon reducing alternative by not only improving the mechanical properties of concrete but also contributing to reducing the sector’s environmental impact. It demonstrates the possibility of using CO2 produced by power plants or other industries for 3D concrete printing. Since traditional cement emits a lot of carbon, our method offers a way to plough back CO2 through 3D concrete printing.”The research team believes their innovation represents a promising contribution towards achieving global sustainable development goals and reducing the industry’s reliance on conventional energy-intensive processes like reinforced concrete construction. To develop their 3D concrete printing system, the research team connected the 3D printer to CO2 pumps and a jet that sprays steam. When activated, the system pumps CO2 and steam into the concrete mix as the structure is printed. CO2 reacts with the components in the concrete, turning into a solid form that stays locked inside the material (sequestered and stored). At the same time, steam improves the absorption of CO2 into the 3D printed structure, enhancing its properties. In lab tests, researchers found the printed concrete structure showed a 50 per cent improvement in printability — meaning it can be shaped and printed more efficiently. The structure also displayed better strength and durability. The printed concrete was up to 36.8 per cent stronger in compression (how much weight it can bear) and up to 45.3 per cent stronger in bending (how much it can flex before breaking) compared to regular 3D printed concrete. Notably, the method is also greener, absorbing and trapping 38 per cent more carbon dioxide compared to traditional 3D printing methods.

Source: https://www.sciencedaily.com/releases/2024/12/241216130026.htm

The melding of visual information (microscopic and X-ray images, CT and MRI scans, for example) with text (exam notes, communications between physicians of varying specialties) is a key component of cancer care. But while artificial intelligence helps doctors review images and home in on disease-associated anomalies like abnormally shaped cells, it’s been difficult to develop computerized models that can incorporate multiple types of data. Now researchers at Stanford Medicine have developed an AI model able to incorporate visual and language-based information. After training on 50 million medical images of standard pathology slides and more than 1 billion pathology-related texts, the model outperformed standard methods in its ability to predict the prognoses of thousands of people with diverse types of cancer, to identify which people with lung or gastroesophageal cancers are likely to benefit from immunotherapy, and to pinpoint people with melanoma who are most likely to experience a recurrence of their cancer. The researchers named the model MUSK, for multimodal transformer with unified mask modeling. MUSK represents a marked deviation from the way artificial intelligence is currently used in clinical care settings, and the researchers believe it stands to transform how artificial intelligence can guide patient care. Although artificial intelligence tools have been increasingly used in the clinic, they have been primarily for diagnostics (does this microscope image or scan show signs of cancer?) rather than for prognosis (what is this person’s likely clinical outcome, and which therapy is most effective for an individual?). Part of the challenge is the need to train the models on large amounts of labeled data (this is a microscope slide of a slice of lung tissue with a cancerous tumour, for example) and paired data (here are the clinical notes about the patient from whom the tumour was obtained). But carefully curated and annotated datasets are hard to come by. In artificial intelligence terms, MUSK is what’s called a foundation model. Foundation models pretrained on vast amounts of data can be customized with additional training to perform specific tasks. Because the researchers designed MUSK to use unpaired multimodal data that doesn’t meet the traditional requirements for training artificial intelligence, the pool of data that the computer can use to “learn” during its initial training is expanded by several orders of magnitude. With this head start, any subsequent training is accomplished with much smaller, more specialized sets of data. In effect, MUSK is an off-the-shelf tool that doctors can fine-tune to help answer specific clinical questions. The researchers collected microscopic slides of tissue sections, the associated pathology reports and follow-up data (including how the patients fared) from the national database The Cancer Genome Atlas for people with 16 major types of cancer, including breast, lung, colorectal, pancreas, kidney, bladder, head and neck. They used the information to train MUSK to predict disease-specific survival, or the percentage of people who have not died from a specific disease during a defined time period. For all cancer types, MUSK accurately predicted the disease-specific survival of a patient 75% of the time. In contrast, standard predictions based on a person’s cancer stage and other clinical risk factors were correct 64% of the time. In another example, the researchers trained MUSK to use thousands of bits of information to predict which patients with cancers of the lung or of the gastric and oesophageal tracts are most likely to benefit from immunotherapy. For non-small cell lung cancer, MUSK correctly identified patients who benefited from immunotherapy treatment about 77% of the time. In contrast, the standard method of predicting immunotherapy response based on PD-L1 expression was correct only about 61% of the time. Similar results were obtained when the researchers trained MUSK to identify which people with melanoma were most likely to relapse within five years after their initial treatment. In this case the model was correct about 83% of the time, which is about 12% more accurate than the predictions generated by other foundation models.

Source: https://www.sciencedaily.com/releases/2025/01/250108173150.htm

As part of an international project consortium, TU Graz has developed new measurement techniques and methods to measure emissions from Category-L vehicles in realistic operation and to determine corresponding limit values. As part of the “LENS” project (L-vehicles Emissions and Noise Mitigation Solutions) funded by the European Commission, Graz University of Technology (TU Graz), as part of an international consortium, has now developed corresponding test procedures and the necessary test equipment. “The measurement methods developed for passenger cars in recent years are not applicable to the much more dynamic Category-L vehicles,” says Stephan Schmidt from the Institute of Thermodynamics and Sustainable Propulsion Systems at TU Graz. “So, we had to develop our own measuring methods, which also included the development and further development of suitable measuring devices that are small and light enough to be used on motorbikes and mopeds. The measurement methodology and technology developed and the emissions data collected are unique worldwide.” A total of 15 partners are involved in the project consortium, including nine research institutions, four manufacturers of two-wheelers and producers of measurement technology. As part of “LENS,” the project consortium measured a total of 150 vehicles on the road and in the laboratory, 40 of them at TU Graz alone. The Institute of Thermodynamics and Sustainable Propulsion Systems and the Institute of Electrical Measurement and Sensor Systems were responsible for developing and creating the measurement methodology and some of the measurement technology for all project participants. In addition to the creation of route profiles suitable for tests with all Category-L vehicle types, the miniaturisation of the measurement technology was a particular challenge. While equipment weighing more than 60 kilograms does not play much of a role in a car, it makes a huge difference on a motorbike and especially on mopeds — both in terms of pollutant emissions and riding characteristics. For motorbikes, the necessary reduction in size and weight was achieved by involving an external partner. For the weaker vehicles, a consortium partner contributed small measuring devices which, although not as accurate, provide good reference values. Creating the route profiles was challenging because a scooter with just a few horsepower is completely different to ride compared with a motorbike with over 100 horsepower. In the end, the researchers found a good mix that included both sporty and hilly sections and took different vehicle classes and driving styles into account. However, the wide range of drive systems, drive outputs, installation space ratios and vehicle masses required a measurement methodology adapted to the subclasses. Precise measurement of the exhaust gas mass flow is crucial for calculating emissions. With small-volume single-cylinder engines, however, mass flow measurement using conventional methods is difficult. However, the model-based method for mass flow calculation developed at TU Graz and used in the LENS project provided a solution. As the vehicles in the lower performance classes can be fully extended on the test bench, the researchers were able to create a model based on the test bench data, from which the mass flows during the journey can be calculated. This enabled the team to obtain usable emission data from the reference values of the small measuring devices. “The many engine concepts and performance classes in the L-vehicle sector are a challenge when it comes to finding standardised test methods that realistically measure noise and exhaust emissions,” says Stephan Schmidt. “In the LENS project, however, we have succeeded in doing this and, together with our consortium, we have created the technical basis for manufacturers, legislators and law enforcement agencies to be able to assess vehicles on the basis of realistic values in future. This will contribute to a significant reduction in pollutant emissions from the Category-L vehicle fleet.”

Source: https://www.sciencedaily.com/releases/2025/01/250109130035.htm

A Cornell University-led research team has developed a method for extracting gold from electronics waste, then using the recovered precious metal as a catalyst for converting carbon dioxide (CO2), a greenhouse gas, to organic materials. The method could provide a sustainable use for some of the approximately 50 million tons of e-waste discarded each year, only 20% of which is recycled, according to Amin Zadehnazari, a postdoctoral researcher in the lab of Alireza Abbaspourrad, professor of food chemistry and ingredient technology. Zadehnazari synthesized a pair of vinyl-linked covalent organic frameworks (VCOFs) to remove gold ions and nanoparticles from circuit boards in discarded electronic devices. One of his VCOFs was shown to selectively capture 99.9% of the gold and very little of other metals, including nickel and copper, from the devices. “We can then use the gold-loaded COFs to convert CO2 into useful chemicals,” Zadehnazari said. “By transforming CO2 into value-added materials, we not only reduce waste disposal demands, we also provide both environmental and practical benefits. It’s kind of a win-win for the environment.” Electronics waste is a literal gold mine: It’s estimated that a ton of e-waste contains at least 10 times more gold than a ton of the ore from which gold is extracted. Traditional methods for recovering gold from e-waste involve harsh chemicals, including cyanide, which pose environmental risks. Zadehnazari’s method is achieved without hazardous chemicals, using chemical adsorption — the adhesion of particles to a surface.

Source: https://www.sciencedaily.com/releases/2025/01/250102162300.htm

The electronics industry is approaching a limit to the number of transistors that can be packed onto the surface of a computer chip. So, chip manufacturers are looking to build up rather than out. Instead of squeezing ever-smaller transistors onto a single surface, the industry is aiming to stack multiple surfaces of transistors and semiconducting elements. Such multi-layered chips could handle exponentially more data and carry out many more complex functions than today’s electronics. A significant hurdle, however, is the platform on which chips are built. Today, bulky silicon wafers serve as the main scaffold on which high-quality, single-crystalline semiconducting elements are grown. Any stackable chip would have to include thick silicon “flooring” as part of each layer, slowing down any communication between functional semiconducting layers. Now, MIT engineers have found a way around this hurdle, with a multi-layered chip design that doesn’t require any silicon wafer substrates and works at temperatures low enough to preserve the underlying layer’s circuitry. In a study the team reports using the new method to fabricate a multi-layered chip with alternating layers of high-quality semiconducting material grown directly on top of each other. The method enables engineers to build high-performance transistors and memory and logic elements on any random crystalline surface — not just on the bulky crystal scaffold of silicon wafers. Without these thick silicon substrates, multiple semiconducting layers can be in more direct contact, leading to better and faster communication and computation between layers, the researchers say. The researchers envision that the method could be used to build AI hardware, in the form of stacked chips for laptops or wearable devices, that would be as fast and powerful as today’s supercomputers and could store huge amounts of data on par with physical data centres.

Source: https://www.sciencedaily.com/releases/2024/12/241218131321.htm

While smart devices in homes have grown to include speakers, security systems, lights and thermostats, the ways to control them have remained relatively stable. Users can interact with a phone, or talk to the tech, but these are frequently less convenient than the simple switches they replace: “Turn on the lamp…. Not that one…. Turn up the speaker volume…. Not that loud!” University of Washington researchers have developed IRIS, a smart ring that allows users to control smart devices by aiming the ring’s small camera at the device and clicking a built-in button. The prototype Bluetooth ring sends an image of the selected device to the user’s phone, which controls the device. The user can adjust the device with the button and — for devices with gradient controls, such as a speaker’s volume — by rotating their hand. IRIS, or Interactive Ring for Interfacing with Smart home devices, operates off a charge for 16-24 hours. IRIS is not currently available to the public. The team decided to put the system in a ring because they believed users would realistically wear that throughout the day. The challenge, then, was integrating a camera into a wireless smart ring with its size and power constraints. The system also had to toggle devices in under a second; otherwise, users tend to think it is not working. To achieve this, researchers had the ring compress the images before sending them to a phone. Rather than streaming images all the time, the ring gets activated when the user clicks the button, then turns off after 3 seconds of inactivity. In a study with 23 participants, twice as many users preferred IRIS over a voice command system alone. On average, IRIS controlled home devices more than two seconds faster than voice commands.

Source: https://www.sciencedaily.com/releases/2025/01/250109130038.htm

A collaboration between NASA and the Indian Space Research Organisation (ISRO) has resulted in the NISAR (NASA-ISRO Synthetic Aperture Radar) satellite, which is set to launch in a few months. This mission, designed to track and monitor Earth’s dynamic surface, will use synthetic aperture radar technology to measure changes in land and ice formations. Capable of delivering precise data down to centimetre-level accuracy, NISAR will contribute significantly to understanding natural disasters, ice-sheet movements, and global vegetation shifts. According to an official press release by NASA, NISAR is equipped with two radar systems: the L-band with a wavelength of 25 centimetres and the S-band with a 10-centimetre wavelength. This dual-band configuration enables detailed observations of various features, from small surface elements to larger structures. These advanced radars will collect data frequently, covering nearly all land and ice surfaces to provide a comprehensive view of Earth’s transformations. As per reports, synthetic aperture radar technology, first utilised by NASA in the 1970s, has been refined for this mission. The data from NISAR will support ecosystem research, cryosphere studies, and disaster response initiatives. Stored and processed in the cloud, the data will be freely accessible to researchers, governments, and disaster management agencies. The partnership between NASA and ISRO, brought together teams to create this dual-band radar satellite. Hardware was developed across continents, with final assembly in India. ISRO’s Space Applications Centre developed the S-band radar, while NASA’s Jet Propulsion Laboratory provided the L-band radar and other key components. The satellite will launch from ISRO’s Satish Dhawan Space Centre and will be operated by ISRO’s Telemetry Tracking and Command Network. NISAR’s deployment highlights international collaboration in addressing global challenges, promising transformative insights into Earth’s changing landscapes.

Source: https://www.gadgets360.com/science/news/us-india-nisar-satellite-revolutionary-earth-observing-technology-launches-soon-7425892

Researchers from the National University of Singapore (NUS) have recently achieved a significant breakthrough in the development of next-generation carbon-based quantum materials, opening new horizons for advancements in quantum electronics. The innovation involves a novel type of graphene nanoribbon (GNR), named Janus GNR (JGNR). The material has a unique zigzag edge, with a special ferromagnetic edge state located on one of the edges. This unique design enables the realisation of one-dimensional ferromagnetic spin chain, which could have important applications in quantum electronics and quantum computing. Graphene nanoribbons, which are narrow strips of nanoscale honeycomb carbon structures, exhibit remarkable magnetic properties due to the behaviour of unpaired electrons in the atoms’ π-orbitals. Through atomically precise engineering of their edge structures into a zigzag arrangement, a one-dimensional spin-polarised channel can be constructed. This feature offers immense potential for applications in spintronic devices or serving as next-generation multi-qubit systems which are the fundamental building blocks of quantum computing. Janus, the ancient Roman god of beginnings and endings, is often depicted as having two faces pointing in opposite directions representing the past and the future. The term “Janus” has been applied in materials science to describe materials that have different properties on opposite sides. JGNR has a novel structure with only one edge of the ribbon having a zigzag form, making it the world’s first one-dimensional ferromagnetic carbon chain. This design is achieved by employing a Z-shaped precursor design which introduces a periodic array of hexagon carbon rings on one of the zigzag edges, breaking the structural and spin symmetry of the ribbon. The significant achievement is a result of close collaboration among synthetic chemists, materials scientists, and theoretical physicists. To produce the JGNR, the researchers initially designed and synthesised a series of special ‘Z-shape’ molecular precursors via conventional in-solution chemistry. These precursors were then used for subsequent on-surface synthesis, which is a new type of solid-phase chemical reaction performed in an ultra-clean environment. This approach allowed the researchers to precisely control the shape and structure of the graphene nanoribbons at the atomic level. The ‘Z-shape’ design allows for the asymmetric fabrication by independently modifying one of the two branches, thereby creating a desired ‘defective’ edge, while maintaining the other zigzag edge unchanged. Moreover, adjusting the length of the modified branch enables the modulation of the width of the JGNRs. Characterisation via state-of-art scanning probe microscopy/spectroscopy and first-principles density functional theory confirms the successful fabrication of JGNRs with ferromagnetic ground state exclusively localised along the single zigzag edge.

Source: https://www.sciencedaily.com/releases/2025/01/250109125912.htm

Researchers have developed a high-performance self-charging energy storage device capable of efficiently storing solar energy. The research team has dramatically improved the performance of existing supercapacitor devices by utilizing transition metal-based electrode materials and proposed a new energy storage technology that combines supercapacitors with solar cells. The research team designed the electrodes using a nickel-based carbonate and hydroxide composite material and maximized the conductivity and stability of the electrodes by adding transition metal ions such as Mn, Co, Cu, Fe, and Zn. This technology has greatly improved the performance of energy storage devices, demonstrating significant advancements in energy density, power density, and charge and discharge stability. Particularly, the energy density achieved in this study is 35.5 Wh kg⁻¹, which is significantly higher than the energy storage per unit weight in previous studies (5-20 Wh kg⁻¹). The power density is 2555.6 W kg⁻¹, significantly exceeding the values from previous studies (- 1000 W kg⁻¹), demonstrating the ability to release higher power rapidly, enabling immediate energy supply even for high-power devices. Additionally, the performance showed minimal degradation during repeated charge and discharge cycles, confirming the long-term usability of the device. Furthermore, the research team developed an energy storage device that combines silicon solar cells with supercapacitors, creating a system capable of storing solar energy and utilizing it in real time. This system achieved an energy storage efficiency of 63% and an overall efficiency of 5.17%, effectively validating the potential for commercializing the self-charging energy storage device. Jeongmin Kim, Senior Researcher at the Nanotechnology Division of DGIST, states, “This study is a significant achievement, as it marks the development of Korea’s first self-charging energy storage device combining supercapacitors with solar cells. By utilizing transition metal-based composite materials, we have overcome the limitations of energy storage devices and presented a sustainable energy solution.” Damin Lee, a researcher at the RLRC of Kyungpook National University, stated, “We will continue to conduct follow-up research to further improve the efficiency of the self-charging device and enhance its potential for commercialization.”

Source: https://www.sciencedaily.com/releases/2024/12/241230131926.htm

In the future, delivering therapeutic drugs exactly where they are needed within the body could be the task of miniature robots. Not little metal humanoid or even bio-mimicking robots; think instead of tiny bubble-like spheres. Such robots would have a long and challenging list of requirements. For example, they would need to survive in bodily fluids, such as stomach acids, and be controllable, so they could be directed precisely to targeted sites. They also must release their medical cargo only when they reach their target, and then be absorbable by the body without causing harm. Now, microrobots that tick all those boxes have been developed by a Caltech-led team. Using the bots, the team successfully delivered therapeutics that decreased the size of bladder tumors in mice. The robots also have to be biocompatible and bioresorbable, meaning that they leave nothing toxic behind in the body. The Caltech-developed microrobots are spherical microstructures made of a hydrogel called poly (ethylene glycol) diacrylate. Hydrogels are materials that start out in liquid or resin form and become solid when the network of polymers found within them becomes cross-linked, or hardens. This structure and composition enable hydrogels to retain large amounts of fluid, making many of them biocompatible. The additive manufacturing fabrication method also enables the outer sphere to carry the therapeutic cargo to a target site within the body. Expertise in two-photon polymerization (TPP) lithography, a technique that uses extremely fast pulses of infrared laser light to selectively cross-link photosensitive polymers according to a particular pattern in a very precise manner was deployed. The technique allows a structure to be built up layer by layer, in a way reminiscent of 3D printers, but in this case, with much greater precision and form complexity. The research group managed to “write,” or print out, microstructures that are roughly 30 microns in diameter — about the diameter of a human hair. In their final form, the microrobots incorporate magnetic nanoparticles and the therapeutic drug within the outer structure of the spheres. The magnetic nanoparticles allow the scientists to direct the robots to a desired location using an external magnetic field. When the robots reach their target, they remain in that spot, and the drug passively diffuses out. Researchers further designed the exterior of the microstructure to be hydrophilic — that is, attracted to water — which ensures that the individual robots do not clump together as they travel through the body. However, the inner surface of the microrobot cannot be hydrophilic because it needs to trap an air bubble, and bubbles are easy to collapse or dissolve. To construct hybrid microrobots that are both hydrophilic on their exterior and hydrophobic, or repellent to water, in their interior, the researchers devised a two-step chemical modification. First, they attached long-chain carbon molecules to the hydrogel, making the entire structure hydrophobic. Then the researchers used a technique called oxygen plasma etching to remove some of those long-chain carbon structures from the interior, leaving the outside hydrophobic and the interior hydrophilic. This was one of the key innovations of this project. This asymmetric surface modification, where the inside is hydrophobic and the outside is hydrophilic, really allows us to use many robots and still trap bubbles for a prolonged period of time in biofluids, such as urine or serum. Indeed, the team showed that the bubbles can last for as long as several days with this treatment versus the few minutes that would otherwise be possible. The presence of trapped bubbles is also crucial for moving the robots and for keeping track of them with real-time imaging. For example, to enable propulsion, the team designed the microrobot sphere to have two cylinder-like openings — one at the top and another to one side. When the robots are exposed to an ultrasound field, the bubbles vibrate, causing the surrounding fluid to stream away from the robots through the opening, propelling the robots through the fluid. The team found that the use of two openings gave the robots the ability to move not only in various viscous biofluids, but also at greater speeds than can be achieved with a single opening. Trapped within each microstructure is an egg-like bubble that serves as an excellent ultrasound imaging contrast agent, enabling real-time monitoring of the bots in vivo. The final stage of development involved testing the microrobots as a drug-delivery tool in mice with bladder tumors. The researchers found that four deliveries of therapeutics provided by the microrobots over the course of 21 days was more effective at shrinking tumors than a therapeutic not delivered by robots.

Source: https://www.sciencedaily.com/releases/2024/12/241211143603.htm