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AI Innovation Solves Supercomputer Math on Desktop Computers in a Matter of Seconds
Posted by Okachinepa on 01/07/2025 @ 
SynEVOL Source
Artificial Intelligence CPU Technology Concept Art
Courtesy of SynEvol
Credit: Johns Hopkins University


The ability to model complicated systems, such as how vehicles deform in collisions, how spacecraft handle harsh circumstances, or how bridges bear stress, at thousands of times faster than previously feasible is being made possible by a breakthrough in artificial intelligence. Massive mathematical problems that formerly required the power of supercomputers can now be solved by personal computers because to this invention.


The new AI framework provides a flexible and effective way to forecast answers to difficult mathematical problems. These formulas are essential for simulating phenomena that are frequently seen in engineering and design tests, such as fluid flow or the behavior of electrical current in different geometries.

The system, known as DIMON (Diffeomorphic Mapping Operator Learning), resolves partial differential equations, which are common mathematical problems found in almost all engineering and scientific study. Researchers can convert real-world systems or processes into mathematical depictions of how environments or items will change across time and space by using these equations.

"This is a solution that we think will generally have a massive impact on various fields of engineering because it's very generic and scalable," said Natalia Trayanova, a professor of biomedical engineering and medicine at Johns Hopkins University who co-led the study, although the idea to develop it came from our own work. "It can essentially solve partial differential equations on multiple geometries in any problem, in any field of science or engineering, such as in crash testing, orthopedics research, or other complex problems where shapes, forces, and materials change."

Trayanova's team evaluated the new AI on more than 1,000 cardiac "digital twins," which are extremely precise computer models of actual patients' hearts, in addition to showcasing DIMON's suitability for resolving other engineering issues. The platform achieved great prognosis accuracy by predicting the propagation of electrical signals through each distinct heart shape.

In order to investigate cardiac arrhythmia—an electrical impulse disturbance in the heart that results in irregular beating—Trayanova's team employs partial differential equations. Researchers can determine whether patients are at risk of developing the frequently fatal illness and provide treatment options using their cardiac digital twins.

Trayanova, who leads the Johns Hopkins Alliance for Cardiovascular Diagnostic and Treatment Innovation, stated, "We're bringing novel technology into the clinic, but a lot of our solutions are so slow that it takes us about a week from when we scan a patient's heart and solve the partial differential equations to predict if the patient is at high risk for sudden cardiac death and what is the best treatment plan." The speed at which we can find a solution with this new AI method is astounding. By using a desktop computer instead of a supercomputer, the time required to compute the prediction of a heart digital twin will drop from many hours to 30 seconds, enabling us to make it a component of the regular clinical process.

In order to solve partial differential equations, complicated objects, such as body organs or airplane wings, are typically divided into grids or meshes composed of tiny components. Each simple piece's difficulty is then resolved and reassembled. However, the grids must be updated and the solutions computed if their shapes change, as in crashes or deformations, which can be costly and computationally slow.

This issue is resolved by DIMON, which uses AI to comprehend the behavior of physical systems in a variety of shapes without requiring a complete recalculation for every new shape. The AI is far quicker and more effective at activities like designing or modeling shape-specific scenarios because it uses learned patterns to forecast how variables like heat, stress, or motion will react rather than breaking forms into grids and repeatedly calculating equations.

The group is adding cardiac pathology that causes arrhythmia to the DIMON framework. According to Minglang Yin, a Johns Hopkins Biomedical Engineering Postdoctoral Fellow who created the platform, the technology's adaptability allows it to be used for shape optimization and numerous other engineering activities where solving partial differential equations on novel shapes is frequently required.

"DIMON maps the solution to several new shapes after first solving the partial differential equations on a single shape for each problem. Its amazing adaptability is highlighted by its shape-shifting capacity, according to Yin. "We are eager to use it to solve a variety of issues and to make it available to the larger community so they can expedite their engineering design solutions."





Revolutionary Thermal Switches Increase Energy Efficiency
Posted by Okachinepa on 01/04/2025 @ 
SynEVOL Source
Thermal Switch Graphic Representation
Courtesy of SynEvol
Credit: Hokkaido University




Modern thermal management systems depend on thermal switches, which are electrically powered devices that regulate heat transport. However, due to their poor performance, conventional electrochemical thermal switches have not been widely used in industries including waste heat recovery, electronics, and energy generation.

A ground-breaking approach has been presented by a research team headed by Professor Hiromichi Ohta of Hokkaido University's Research Institute for Electronic Science. They created a very effective and environmentally friendly substitute by using cerium oxide (CeO2) thin films as the active component in thermal switches. Their ground-breaking research was just released in Science Advances.


CeO2-Based Thermal Switch
Courtesy of SynEvol
Credit: Hokkaido University

The study team demonstrated that CeO2-based thermal switches can outperform previous standards. "The innovative device sets a new standard for electrochemical thermal switches with an on/off thermal conductivity ratio of 5.8 and a thermal conductivity (κ)-switching width of 10.3 W/m·K," says Ohta.

In its minimum state (off-state), the thermal conductivity is 2.2 W/m·K; however, in its oxidized form (on-state), it dramatically increases to 12.5 W/m·K. These performance measurements show exceptional durability and dependability for prolonged use in real-world applications, remaining constant after 100 cycles of reduction and oxidation.


CeO2-Based Solid State Electrochemical Thermal Switch Schematic
Courtesy of SynEvol
Credit: Hokkaido University

Utilizing cerium oxide, a material that is abundant in the earth and known for its ecological sustainability and economic feasibility, is a noteworthy advantage of this technology. CeO2 provides a sustainable and easily accessible substitute for traditional thermal switches, which rely on expensive and limited resources. This lowers costs and the environmental impact of thermal management systems. As a result, the technique is more effective, scalable, and applicable to a wider range of industrial sectors.

An important advancement in thermal management technology has been made with the creation of CeO2-based thermal switches, which have a wide range of uses in sectors including electronics cooling and renewable energy systems. These switches effectively control infrared heat flow, improve waste heat recovery, and support energy-efficient systems. They are used in thermal shutters and sophisticated displays.

Princeton Researchers Create Amazing New Substance
Posted by Okachinepa on 01/01/2025 @ 
SynEVOL Source
Stretchable, Flexible, Recyclable 3D Printed Plastic
Courtesy of SynEvol
Credit: Princeton University


Engineers at Princeton have created a scalable 3D printing method that allows them to create soft polymers with tunable stretchiness and flexibility, as well as being economical and recyclable—a combination of properties that are rarely found in materials that are sold commercially.

A team lead by Emily Davidson described how they produced 3D-printed objects with adjustable stiffness using thermoplastic elastomers, a type of commonly accessible polymers, in a research published in Advanced Functional Materials. The developers were able to program the physical characteristics of the plastic by creating the print path for the 3D printer. This allowed the gadgets to flex and stretch in one direction while staying stiff in another.

The potential uses of this approach in areas like soft robotics, medical devices, prostheses, lightweight helmets, and customized high-performance shoe soles were emphasized by Davidson, an assistant professor of chemical and biological engineering.

The smallest level of the material's interior structure is crucial to its performance. The study team employed a block copolymer type that, within a stretchy polymer matrix, generates stiff cylindrical structures that are 5-7 nanometers thick (human hair is roughly 90,000 nanometers thick). These tiny cylinders were oriented by the researchers via 3D printing, resulting in a 3D printed material that is soft and elastic in almost every direction yet hard in one. These cylinders can be oriented in many orientations within a single object by designers, creating soft constructions that show stretchiness and rigidity in different areas.

"We are able to control the nanostructures that the elastomer we are using forms," Davidson stated. This gives designers a lot of influence over the final goods. "We are able to design materials with specific properties in various directions."

Selecting the appropriate polymer was the first stage in creating this procedure. The block copolymer that the researchers selected is a thermoplastic elastomer, which hardens into an elastic substance when cooled but can be heated and treated as a polymer melt. Polymers are extended chains of interconnected molecules at the molecular level. Block copolymers are composed of many homopolymers joined to one another, while traditional homopolymers are lengthy chains of a single repeating monomer. These distinct areas of a block copolymer chain resemble water and oil Rather than combining, they separate. This characteristic was employed by the researchers to create a material with stiff cylinders inside a flexible matrix.

The researchers created a 3D printing method that successfully induces the alignment of these stiff nanostructures by applying their understanding of how these block copolymer nanostructures originate and react to flow. The researchers examined how the physical characteristics of the printed material may be regulated by printing rate and controlled under-extrusion.

The lead author of the paper, Alice Fergerson, a Princeton graduate student, discussed the method and the crucial part thermal annealing—the regulated heating and cooling of a material—plays.

"I think one of the coolest things about this technique is the many functions that thermal annealing performs—it not only significantly enhances the properties after printing, but it also makes the items we print reusable and even capable of self-healing in the event that they break or get damaged."

One of the project's objectives, according to Davidson, was to develop soft materials with regionally adjustable mechanical qualities in a way that is both economical and scalable for industry. Materials like liquid crystal elastomers can be used to produce comparable structures with regionally controlled characteristics. However, according to Davidson, those materials are costly (up to $2.50 per gram) and necessitate a multi-step manufacturing procedure that includes meticulously regulated extrusion and UV light exposure. Davidson's lab uses thermoplastic elastomers that can be manufactured using a commercial 3D printer and cost around one cent per gram.

The researchers have demonstrated that their method can add useful additives to thermoplastic elastomers without compromising material property control. In one instance, they introduced an organic compound created by the group of Professor Lynn Loo that causes the plastic to glow red when exposed to UV radiation. They also showed off the printer's capacity to create intricate, multi-layered structures, such as a little plastic vase and printed lettering that spelled out PRINCETON using sharp turns.

By improving the internal nanostructures' order and perfection, annealing is essential to their process. According to Davidson, annealing also makes the material's self-healing qualities possible. The researchers can anneal a flexible piece of the printed plastic to reattach it after cutting it as part of the projectthe substance. The material that was restored showed the same traits as the original sample. The original and the restored material showed "no significant differences," according to the researchers.

In the future, the study team anticipates investigating novel 3D printable designs that will work with wearable electronics and biomedical devices, among other uses.

Small “Molecular Flashlight” Could Change Brain Disease Detection
Posted by Okachinepa on 01/01/2025 @ 
SynEVOL Source

Brain Cancer Laser Treatment
Courtesy of SynEvol
Credit: Centro Nacional De Investigaciones Oncologicas



In biomedical research, it has long been difficult to examine molecular alterations in the brain brought on by neurological illnesses and cancer without intrusive treatments. Now, researchers have created a novel method that allows for in-depth molecular analysis by shining light into mice's brains using an incredibly thin probe. International researchers, including teams from the Spanish National Cancer Research Centre (CNIO) and the Spanish National Research Council (CSIC), collaborated to produce the findings, which were published today (December 31) in the journal Nature Methods.

Because it illuminates nerve tissue and reveals its chemical makeup, the researchers refer to this invention as a "molecular flashlight." With this method, researchers can identify genetic alterations linked to primary and metastatic brain cancers as well as traumas like traumatic brain injury.

Invisible to the human sight, the molecular flashlight is a probe that is less than 1 mm thick and has a tip that is only one micron wide, or around one thousandth of a millimeter. Since a human hair is between 30 and 50 microns in diameter, it can be put deeply into the brain without harming it.

The flashlight-probe is mainly a "promising" research tool in animal models that enables "monitoring molecular changes caused by traumatic brain injury, as well as detecting diagnostic markers of brain metastasis with high accuracy," according to the paper's authors. It is not yet ready for patient testing.

The experiment was conducted by the European NanoBright consortium, which comprises two Spanish groups: the Neuronal Circuits Laboratory of the Cajal Institute at the CSIC, led by Liset Menéndez de la Prida, and the group headed by Manuel Valiente, who leads the CNIO's Brain Metastasis Group. The instrumentation was built by teams from French and Italian institutions, while both teams have been in charge of the biomedical research at NanoBright.


Vibrational Spectroscopy Instrument
Courtesy of SynEvol
Credit:CNIO



Although it is a fantastic accomplishment, the use of light to record or stimulate brain function is not a novel technology. For instance, individual neurons' activity can be controlled by light using so-called optogenetic techniques. To make the neurons light-sensitive, these techniques include introducing a gene into the neurons. A paradigm change in biomedical research has been brought about by NanoBright's revolutionary technology, which allows the brain to be investigated without any prior alterations.

The new molecular lamp is based on a technique known as vibrational spectroscopy. It operates by taking use of a characteristic of light called the Raman effect, which states that the way light interacts with molecules depends on their structure and chemical makeup. This makes it possible to identify a distinct spectrum, or signal, for every molecule. After then, the spectrum serves as a molecular signature that reveals details about the makeup of the tissue that is illuminated.

"This technology enables us to study the brain in its natural state without the need for prior alteration," says Manuel Valiente. Furthermore, unlike other technologies, it allows us to examine any kind of brain structure, not simply those that have been genetically marked or altered. When a pathology is present, vibrational spectroscopy allows us to observe any chemical changes in the brain.

Neurosurgery already makes use of Raman spectroscopy, albeit in a less accurate and invasive way. According to Valiente, "studies have been conducted on its use during brain tumor surgery in patients." After the majority of the tumor has been surgically removed, a Raman spectroscopy probe can be placed in the operating room to determine whether any cancer cells are still present. the region. But only when the cavity is sufficiently big and the brain is already open is this done. These comparatively big "molecular flashlights" cannot be used in live animal models in a minimally invasive manner.

The NanoBright consortium's probe is referred regarded as "minimally invasive" since it is so thin that any harm it might do when inserted into brain tissue is deemed insignificant.

In Nature Methods, the authors offer particular applications. In experimental models of brain metastases, Valiente's team at CNI has employed the molecular flashlight: "As happens with patients, we have observed tumor fronts releasing cells that would escape surgery," says Valiente. "The difference with current technology is that, regardless of the depth of the tumor, we can now perform this analysis in a minimally invasive manner."

Determining if the data from the probe can "differentiate various oncological entities, such as types of metastases, based on their mutational profiles, by their primary origin, or from different types of brain tumors" is one of the CNIO team's current objectives.

The Cajal Institute team has applied the method to investigate the epileptogenic regions around traumatic brain injury. Depending on whether they were linked to a tumor or a trauma, we were able to distinguish distinct vibrational signatures in the same brain areas that are susceptible to epileptic convulsions. This suggests that the molecular signatures of these areas are affected differently and could be used to distinguish between different pathological entities using automatic classification algorithms, including artificial intelligence,” explains Liset Menéndez de la Prida.

The CSIC researcher says, "We will be able to find new high-precision diagnostic markers by combining vibrational spectroscopy with other modalities for recording brain activity and advanced computational analysis using artificial intelligence." "This will make it easier to create cutting-edge neurotechnology for novel biomedical uses."

 


Korea Introduces Groundbreaking Supercapacitors That Charge on Their Own
Posted by Okachinepa on 12/31/2024 @ 
SynEVOL Source
Solar Supercapacitor Concept
Courtesy of SynEvol 
Credit: DGIST


Senior researcher Jeongmin Kim of DGIST and Damin Lee of Kyungpook National University's RLRC have created a novel self-charging energy storage device that effectively stores solar energy. Through the integration of transition metal-based electrode materials, this novel technology dramatically improves the performance of conventional supercapacitors. The group also unveiled a brand-new energy storage system that combines solar cells and supercapacitors.

The researchers used a carbonate and hydroxide composite material based on nickel to create electrodes in order to do this. They increased conductivity and stability by adding transition metal ions like manganese (Mn), cobalt (Co), copper (Cu), iron (Fe), and zinc (Zn). These developments have pushed the limits of energy storage technology by producing notable gains in energy density, power density, and the general stability of charge and discharge cycles.

In particular, this study's energy density of 35.5 Wh/kg is a significant increase over earlier research's energy storage per unit weight of 5–20 Wh/kg. With a power density of 2555.6 W/kg, it greatly outperforms the numbers from earlier research (-1000 W/kg), indicating the capacity to release more power quickly and providing an instant energy source even for high-power equipment. Furthermore, the device's long-term usability was confirmed by the low loss in performance during repeated cycles of charging and discharging.

Additionally, the study team created an energy storage device that combines supercapacitors and silicon solar cells to create a system that can store solar energy and use it instantly. This system successfully validated the possibility for commercializing the self-charging energy storage device with an overall efficiency of 5.17% and an energy storage efficiency of 63%.

"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," says Jeongmin Kim, Senior Researcher at DGIST's Nanotechnology Division. We have provided a sustainable energy solution by overcoming the drawbacks of energy storage devices through the use of transition metal-based composite materials. “We will continue to conduct follow-up research to further improve the efficiency of the self-charging device and enhance its potential for commercialization,” said Damin Lee, a researcher at Kyungpook National University’s RLRC.




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