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05/19/2016 : 157557
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Positive Nanoplastics Boost E. coli Virulence
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Posted by Okachinepa on 05/19/2025 @
Courtesy of SynEVOL
Credit: University of Illinois at Urbana Champaign
Nanoplastics can be found everywhere. These small particles are so minuscule that they can gather on bacteria and be absorbed by plant roots; they exist in our food, our water, and within our bodies. Researchers are uncertain about the complete impact of nanoplastics on our health, but recent studies from food scientists at the University of Illinois Urbana-Champaign indicate that some nanoplastics might enhance the virulence of foodborne pathogens.
"While other research has assessed the relationship between nanoplastics and bacteria, our study is the first to examine the effects of microplastics and nanoplastics on human pathogenic bacteria." "We concentrated on a primary pathogen associated with foodborne illness outbreaks—E. coli O157:H7," stated senior author Pratik Banerjee, an associate professor in the Department of Food Science and Human Nutrition and an Illinois Extension Specialist; both are divisions of the College of Agricultural, Consumer and Environmental Sciences at Illinois.
The researchers anticipated that positively charged nanoplastics would affect E. coli due to the negative charge on the bacteria's surface. To evaluate their opposites-attract theory, they produced nanoplastics from polystyrene—the substance found in those common white clamshell takeout containers—and assigned positive, neutral, or negative charges prior to exposing the particles to E. coli either suspended in solution or within biofilms.
Courtesy of SynEVOL
Credit: University of Illinois at Urbana Champaign
"We began with the surface charge." Plastics possess a significant capacity to adsorb chemicals. "Banerjee stated that every chemical influences surface charge differently, depending on the amount of chemical adsorbed and the type of plastic."
"In this paper, we didn't examine the effects of the chemicals themselves—that's the focus of our next study—but this serves as the initial step in comprehending how the surface charge of plastics influences the response of pathogenic E. coli."
The bacteria subjected to positively charged nanoplastics exhibited stress through various means, not solely by generating increased amounts of Shiga-like toxins. They also required more time to reproduce when free-floating and came together to form biofilms at a slower pace. Nevertheless, growth ultimately recovered.
Biofilms provide bacterial cells with a level of protection due to an extracellular layer they form. To evaluate if this coating safeguards against stress caused by nanoplastics, the team submerged relatively large microplastic particles into the bacterial mixture and allowed E. coli a week or two to establish itself. Next, they presented the identical charged nanoplastics.
The positively charged particles continued to induce stress—and increased Shiga-like toxin production—in E. coli that were attached to biofilms.
"Biofilms represent a highly resilient bacterial formation and are difficult to eliminate." "They pose a significant issue in the healthcare field, developing on devices such as catheters or implants, as well as in the food sector," Banerjee stated. "One of our objectives was to observe the effects when this human pathogen, frequently spread through food, interacts with these nanoplastics from the perspective of a biofilm."
Engagements with plastic particles could be doing more than elevating E. coli's toxicity; other research indicates that biofilms on microplastics might act as focal points for the transfer of antibiotic resistance genes, complicating bacterial management.
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Solar Power Surpasses Nuclear Energy Generation
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Posted by Okachinepa on 05/19/2025 @
Courtesy of SynEVOL
Credit: Boston University
The International Energy Agency estimates that over $100 trillion will be invested in developing net-zero energy infrastructure worldwide by 2050. However, each of these projects carries the possibility of exceeding anticipated construction costs or experiencing delays. Recent technologies like hydrogen or geothermal energy, introduced in the last ten years, are harder to assess as government bodies, energy developers, utilities, investors, and other parties determine which sustainable energy systems are ideal for upcoming projects.
Researchers at the Institute for Global Sustainability (IGS) at Boston University have discovered that escalating construction expenses and missed deadlines hinder numerous energy initiatives. The study revealed that, on average, project expenses exceed expectations by 40% for construction and that they typically require nearly two additional years to complete compared to initial plans.
Nuclear power facilities are the most significant culprits, often experiencing construction cost overruns that are usually double or even greater than anticipated, along with the longest delays in completion. Specifically, the typical nuclear power facility experiences a construction cost overrun of 102.5%, resulting in an overall expense of $1.56 billion above what was anticipated.
Examining newer net-zero alternatives also shows greater risk. Hydrogen infrastructure and carbon capture and storage both show considerable average delays and cost overruns during construction, similar to thermal power plants using natural gas, raising doubts about their ability to be scaled up rapidly to achieve emission reduction targets for climate mitigation.
"Concerningly, these results highlight a genuine warning signal about attempts to significantly advance a hydrogen economy," states Benjamin Sovacool, the primary and first author of the research, director of IGS, and professor of Earth and environment.
In contrast, projects involving solar energy and electricity grid transmission have the strongest construction history and are frequently finished ahead of time or at lower costs than anticipated. Wind farms also showed positive results in the financial risk evaluation.
According to Sovacool, the proof is evident: "Wind and solar, as low-carbon energy sources, offer significant climate and energy security advantages, in addition to financial benefits linked to reduced construction risks and a lower likelihood of delays," he states. "It serves as additional proof that these technologies possess a wide range of undervalued and overlooked social and economic benefits."
Employing a uniquely extensive and detailed dataset surpassing current sources, the research offers the most thorough comparative examination of risks related to construction cost overruns and delays for energy infrastructure initiatives worldwide.
The researchers gathered information on 662 energy infrastructure projects encompassing a wide range of technology types and capacities, constructed from 1936 to 2024 in 83 nations, amounting to $1.358 trillion in investments. This encompasses new advancements like geothermal and bioenergy, offering new perspectives on the pricing dynamics of these newly commercialized technologies.
The research assessed ten different project types: coal, oil, or natural gas-fired thermoelectric power plants; nuclear energy reactors; hydroelectric power stations; large-scale wind farms; large-scale solar photovoltaic and concentrated solar power plants; high-voltage transmission systems; bioenergy plants; geothermal energy plants; hydrogen production sites; and carbon capture and storage systems.
Comprehending the reasons why energy projects exceed budget and lag behind schedule—and identifying when that critical moment takes place—is another significant insight provided by this worldwide analysis. The research investigated diseconomies of scale, construction delays, and governance issues to pinpoint key limits where project expenses escalate, aiding in the development of improved risk management strategies.
"I'm especially impressed by our results regarding the diseconomies of scale, as projects that surpass 1,561 megawatts in capacity show a notably increased risk of cost overruns," states Hanee Ryu, second author and corresponding author, who is also a visiting researcher at IGS. "This implies that we might have to rethink our strategy for large-scale energy infrastructure planning, particularly as we allocate trillions to worldwide decarbonization initiatives."
Ryu explains that this could imply that smaller, modular renewable initiatives may not only provide environmental advantages, but could also lower financial risks and enhance budget predictability.
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Game-Changing Chip Integrates Sight, Thought, and Memory for Instantaneous AI
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Posted by Okachinepa on 05/19/2025 @
Courtesy of SynEVOL
Credit: RMIT University
Engineers from RMIT University have developed a small, brain-inspired device capable of sensing hand gestures, retaining visual memories, and processing data—all independently of an external computer.
This advancement, referred to as a neuromorphic device, imitates the functioning of the human brain. As stated by Professor Sumeet Walia, the primary researcher of the project, this could open opportunities for extremely rapid visual processing in autonomous vehicles, intelligent robots, and various advanced technologies aimed at interacting with humans in a more natural manner.
In contrast to conventional digital systems that require significant energy, neuromorphic vision technology employs analog-style processing akin to the operations of our brains. This method enables it to manage intricate visual tasks with much better energy efficiency.
"Neuromorphic vision systems aim to mimic the brain's analogue processing, which can significantly lower the energy consumption required for intricate visual tasks in comparison to current digital technologies,” stated Walia, Director of the RMIT Centre for Opto-electronic Materials and Sensors (COMAS).
The project unites neuromorphic materials with sophisticated signal processing under the leadership of Professor Akram Al-Hourani, Deputy Director of COMAS. Central to the device is molybdenum disulfide, known as MoS2—an atomic compound measuring only a few atoms in thickness.
In their most recent study, the researchers demonstrated how minute imperfections at the atomic scale in MoS2 can be utilized to sense light and transform it into electrical signals. This resembles the way neurons in the brain activate and exchange information, enabling the device to capture and process visual data instantaneously.
"This prototype device replicates the human eye’s capacity to capture light and the brain’s skill in processing visual data, allowing it to quickly detect environmental changes and create memories without relying on excessive data and energy," Walia stated.
"In contrast, modern digital systems are highly energy-intensive and struggle to adapt as data quantity and complexity grow, restricting their capacity to make ‘genuine’ real-time decisions."
In experiments, the device identified alterations in a waving hand’s motion without needing to record the events frame by frame – this process, called edge detection, necessitates much less data processing and energy.
When the alterations were recognized, the device recorded these occurrences as memories similar to a brain.
The team performed experiments within the visible spectrum of light, which was an extension of their prior neuromorphic investigations in the ultraviolet range.
“We showed that atomically thin molybdenum disulfide can effectively mimic the leaky integrate-and-fire (LIF) neuron behavior, a key component of spiking neural networks,” Thiha stated.
The previous UV work solely focused on detecting, creating memories, and processing static images. In both the visible-spectrum and UV devices, the memories could be reset, making the devices prepared for the upcoming task.
The team's breakthrough may someday enhance the reaction times of automated vehicles and sophisticated robotic systems to visual data, which could be vital, especially in hazardous and unpredictable settings.
Walia mentioned that “neuromorphic vision in such applications, which is still many years in the future, might identify alterations in a scene nearly instantaneously, eliminating the requirement to process vast amounts of data, thus allowing a significantly quicker response that could potentially save lives.”
“According to Al-Hourani, neuromorphic technology could facilitate more seamless interactions for robots collaborating with humans in manufacturing or functioning as personal assistants by promptly recognizing and responding to human behavior.”
The team is currently expanding the proof-of-concept single-pixel device to a bigger pixel array of MoS2-based devices.
The Australian Research Council has recently provided funding to the team through a Linkage Infrastructure, Equipment and Facilities (LIEF) grant to facilitate the expansion of their neuromorphic devices.
"Walia stated, 'Although our system replicates some features of the brain's neural functions, especially in vision, it remains a basic model.'"
"We will enhance the devices to handle particular real-world applications involving more intricate vision tasks, while also minimizing power consumption."
The team intends to create hybrid systems that combine their analogue technology with traditional digital electronics.
"Walia stated, 'We view our efforts as a complement to traditional computing, not as a substitute.'"
"Traditional systems perform well in various tasks, whereas our neuromorphic technology provides benefits for visual processing where energy efficiency and real-time functionality are essential."
The group is additionally exploring substances beyond MoS2 that could broaden functionalities into infrared, potentially allowing for immediate monitoring of worldwide emissions and smart detection of pollutants like harmful gases, pathogens, and chemicals.
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Princeton Engineers Create Metabot: A Material That's Also a Robot.
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Posted by Okachinepa on 05/19/2025 @
Courtesy of SynEVOL
Credit: Princeton University
In a development straight out of science fiction, engineers at Princeton University have engineered a groundbreaking material that blurs the lines between inanimate matter and intelligent machines. This innovative creation, dubbed a "metabot," can expand, morph its shape, move independently, and respond to electromagnetic commands with the agility of a remote-controlled robot – all without the need for motors or internal gears.
The research team, led by Glaucio Paulino, the Margareta Engman Augustine Professor of Engineering at Princeton, drew inspiration from the intricate art of origami to design a structure that bridges the traditional divide between robotics and materials science. Their findings, recently published in the prestigious journal Nature, detail the creation of a metamaterial – an engineered substance whose unique properties arise not from its chemical composition, but from its carefully designed physical architecture.
Constructed from a combination of common plastics and specialized magnetic composites, the metabot's structure can be manipulated remotely using an applied magnetic field. This allows researchers to induce a range of movements, including expansion, bending, and directional motion, all without any direct physical contact.
"You can transform between a material and a robot, and it is controllable with an external magnetic field," explained Professor Paulino, highlighting the dual nature of their invention.
Minjie Chen, a co-author of the study and an associate professor at Princeton's Andlinger Center for Energy and the Environment, emphasized the advanced power electronics underpinning the technology. "The electromagnetic fields carry power and signal at the same time," Chen stated. "Each behavior is very simple but when you put them together the behavior can be very complex. This research has pushed the boundaries of power electronics by demonstrating that torque can be passed remotely, instantaneously, and precisely over a distance to trigger intricate robotic motions."
The metabot's unique capabilities stem from its modular design, a collection of mirrored, reconfigurable unit cells. This "chirality," as it's known, allows for surprisingly complex behaviors. Tuo Zhao, a postdoctoral researcher in Paulino's lab, illustrated this by explaining how the metabot can execute significant contortions – twisting, contracting, and shrinking – in response to a simple magnetic nudge.
Experts in the field have lauded the research as a significant step forward. Xuanhe Zhao, a professor at MIT not involved in the study, hailed the work as "opening a new and exciting avenue in origami design and applications." He further noted the "extremely versatile mechanical metamaterials" achieved through the control of module assembly and chiral states, emphasizing the "truly impressive" versatility and potential functionality.
Davide Bigoni, a professor at the Universita' di Trento in Italy, described the work as "groundbreaking," suggesting it could "drive a paradigm shift across multiple fields including soft robotics, aerospace engineering, energy absorption, and spontaneous thermoregulation."
Looking towards practical applications, the Princeton team has already begun exploring the metabot's potential in robotics. Tuo Zhao utilized laser lithography to create a microscopic prototype, roughly the thickness of a human hair. The researchers envision such tiny robots one day delivering targeted medications within the body or assisting surgeons in delicate procedures.
Beyond robotics, the team demonstrated the metamaterial's ability to function as a thermoregulator. By shifting between a light-absorbing black surface and a reflective one in response to magnetic fields, they were able to manipulate the material's temperature significantly when exposed to sunlight.
Further potential applications are being explored in areas like antennae, lenses, and devices interacting with light wavelengths, where the material's unique geometric properties could offer novel solutions. The fundamental building blocks of the metabot are based on "Kresling Patterns," origami-inspired plastic tubes with supporting struts that twist when compressed and compress when twisted. By connecting mirrored Kresling tubes, the researchers created units that fold in opposite directions depending on the direction of the applied twist. This repeating pattern allows for independent control of each section using precisely engineered magnetic fields.
Professor Paulino highlighted an intriguing consequence of the metabot's chiral design: its ability to defy typical action-reaction rules. He demonstrated how the material could exhibit asymmetrical behavior, mimicking a phenomenon called hysteresis, where a system's response depends on its history. This unique property could even pave the way for physical simulations of complex systems found in engineering, physics, and economics.
Looking further into the future, the researchers speculate that this novel material could even be used to design physical structures that mimic the logic gates found in computer transistors, potentially offering a new avenue for physical computation.
"This gives us a physical method to simulate complex behavior, such as non-commutative states," concluded Professor Paulino, underscoring the profound implications of this transformative research.
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Quantum Computers Beat Supercomputers in Specific Task
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Posted by Okachinepa on 05/19/2025 @
Courtesy of SynEVOL
Credit: University of Southern California
In a significant advancement, scientists at USC have demonstrated that quantum computers can surpass the speed of the fastest supercomputers in tackling specific intricate issues.
This advancement, referred to as quantum advantage, was showcased through a specific method called quantum annealing. Consider it a more intelligent method to find good (not always ideal) resolutions to challenging puzzles that conventional computers find difficult. The findings were recently released in Physical Review Letters.
“Quantum annealing operates by identifying low-energy states in quantum systems, which are linked to optimal or near-optimal solutions for the problems addressed,” stated Daniel Lidar, the study's corresponding author and a professor of electrical and computer engineering, chemistry, and physics and astronomy at the USC Viterbi School of Engineering and USC Dornsife College of Letters, Arts and Sciences.
For many years, researchers have sought to demonstrate that quantum computers can expand in scale and continuously outperform classical systems as challenges increase in size. This research adopts a novel perspective by moving the emphasis from seeking ideal solutions to pursuing nearly perfect responses, which are frequently sufficient in practical scenarios.
This type of “approximate optimization” is particularly beneficial in fields such as finance, logistics, and machine learning, where arriving at a near-optimal solution quickly is more important than investing excessive time in pursuing perfection.
Through quantum annealing, the researchers achieved high-quality solutions more quickly than the top classical algorithms—signifying a significant advancement in practical quantum computing.
Quantum annealing is a particular form of quantum computing that employs principles of quantum physics to discover optimal solutions to challenging optimization issues. Instead of demanding precise optimal solutions, the research concentrated on identifying solutions that fall within a specific percentage (≥1%) of the optimal value.
Numerous real-life issues don’t need precise solutions, which makes this method practically applicable. For instance, when selecting stocks for a mutual fund, it is frequently sufficient to outperform a major market index instead of surpassing every other stock portfolio.
To illustrate algorithmic quantum scaling advantage, the researchers utilized a D-Wave Advantage quantum annealing processor, a specific kind of quantum computing machine located at USC’s Information Sciences Institute. As with all existing quantum computers, noise significantly impacts the degradation of quantum advantage in quantum annealing.
To address this issue, the team applied a method known as quantum annealing correction (QAC) on the D-Wave processor, resulting in the creation of more than 1,300 error-reduced logical qubits. This error suppression was crucial for gaining the upper hand over parallel tempering with isoenergetic cluster moves (PT-ICM), the most effective current classical method for similar issues.
To tackle this problem, the team utilized a technique called quantum annealing correction (QAC) on the D-Wave processor, leading to the generation of over 1,300 error-suppressed logical qubits. This error suppression was vital for achieving an advantage over parallel tempering with isoenergetic cluster moves (PT-ICM), the most efficient current classical method for comparable problems.
The research showcased quantum advantage by employing various methodologies and concentrated on a class of two-dimensional spin-glass issues with precise interactions. "Spin-glass issues represent a category of intricate optimization problems that arise from statistical physics models pertaining to disordered magnetic systems," Lidar remarked. Rather than pursuing precise solutions, the researchers evaluated “time-to-epsilon” performance, assessing how rapidly each method could identify solutions within a defined percentage of the ideal outcome.
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