Aurelia Butler

Each year, more than 1.2 billion smartphones are produced globally. The production of electronic devices is not only energy-intensive but also consumes valuable natural resources. Additionally, the manufacturing and delivery processes release a significant amount of CO2 into the atmosphere. Meanwhile, devices are aging faster than ever — users replace their still-functional phones on average every 2 to 3 years. At best, old devices are recycled; at worst, they end up in landfills.
Although the most sustainable solution would be to change consumer behavior and consider more carefully whether every new model truly requires replacing the old one, this is easier said than done. Rapid technological development quickly renders older devices obsolete. Therefore, alternative solutions are needed — such as extending the lifespan of devices by giving them an entirely new purpose.
This is precisely the approach tested by researchers Huber Flores, Ulrich Norbisrath, and Zhigang Yin from the University of Tartu’s Institute of Computer Science, along with Perseverance Ngoy from the Institute of Technology and their international colleagues. “Innovation often begins not with something new, but with a new way of thinking about the old, re-imagining its role in shaping the future,” explained Huber Flores, Associate Professor of Pervasive Computing. They demonstrated that old smartphones can be successfully repurposed into tiny data centers capable of efficiently processing and storing data. They also found that building such a data center is remarkably inexpensive — around 8 euros per device.
These tiny data centers have a wide range of applications. For example, they could be used in urban environments like bus stops to collect real-time data on the number of passengers, which could then be used to optimize public transportation networks.
In the project’s first stage, the researchers removed the phones’ batteries and replaced them with external power sources to reduce the risk of chemical leakage into the environment. Then, four phones were connected together, fitted with 3D-printed casings and holders, and turned into a working prototype ready to be re-used, fostering sustainable practices for old electronics.
The prototype was then successfully tested underwater, where it participated in marine life monitoring by helping to count different sea species. Normally, these kinds of tasks require a scuba diver to record video and bring it to the surface for analysis. But with the prototype, the whole process was done automatically underwater.
The team’s results show that outdated technology doesn’t have to end up as waste. With minimal resources, these devices can be given a new purpose, contributing to the development of more environmentally friendly and sustainable digital solutions.
“Sustainability is not just about preserving the future — it’s about reimagining the present, where yesterday’s devices become tomorrow’s opportunities,” commented Ulrich Norbisrath, Associate Professor of Software Engineering. More

Unlike birds, which navigate unknown environments with remarkable speed and agility, drones typically rely on external guidance or pre-mapped routes. However, a groundbreaking development by Professor Fu Zhang and researchers from the Department of Mechanical Engineering of Faculty of Engineering at the University of Hong Kong (HKU), has enabled drones and micro air vehicles (MAVs) to emulate the flight capabilities of birds more closely than ever before.
The team has developed the Safety-Assured High-Speed Aerial Robot (SUPER), capable of flying at speeds exceeding 20 meters per second and avoiding obstacles as thin as 2.5 millimeters – such as power lines or twigs – using solely on onboard sensors and computing power. With a compact design featuring a wheelbase of just 280 mm and a takeoff weight of 1.5 kg, SUPER demonstrates exceptional agility, navigating dense forests at night and skillfully avoiding thin wires.
Professor Zhang describes this invention as a game-changer in the field of drone technology, “Picture a ‘Robot Bird’ swiftly maneuvering through the forest, effortlessly dodging branches and obstacles at high speeds. This is a significant step forward in autonomous flight technology. Our system allows MAVs to navigate complex environments at high speeds with a level of safety previously unattainable. It’s like giving the drone the reflexes of a bird, enabling it to dodge obstacles in real-time while racing toward its goal.”
The breakthrough lies in the sophisticated integration of hardware and software. SUPER utilizes a lightweight 3D light detection and ranging (LIDAR) sensor capable of detecting obstacles up to 70 meters away with pinpoint accuracy. This is paired with an advanced planning framework that generates two trajectories during flight: one that optimizing speed by venturing into unknown spaces and another prioritizing safety by remaining within known, obstacle-free zones.
By processing LIDAR data directly as point clouds, the system significantly reduces computation time, enabling rapid decision-making even at high velocities. The technology has been tested in various real-life applications, such as the autonomous exploration of ancient sites, and has demonstrated seamless navigation in both indoor and outdoor environments.
“The ability to avoid thin obstacles and navigate tight spaces opens up new possibilities for applications like search and rescue, where every second counts. SUPER’s robustness in various lighting conditions, including nighttime, makes it a reliable tool for round-the-clock operations.” said Mr Yunfan Ren, the lead author of the research paper.
The research team envisions a wide range of applications for this innovative technology, including autonomous delivery, power line inspection, forest monitoring, autonomous exploration, and mapping. In search and rescue missions, MAVs equipped with SUPER technology could swiftly navigate disaster zones – such as collapsed buildings or dense forests – day and night, locating survivors or assessing hazards more efficiently than current drones. Moreover, in disaster relief scenarios, they could deliver crucial supplies to remote and inaccessible areas. More

Hailed as one of the greatest inventions of the 20th century, transistors are integral components of modern electronics that amplify or switch electrical signals. As electronics become smaller, it is becoming increasingly difficult to continue scaling down silicon-based transistors. Has the development of our electronics hit a wall?
Now, a research team led by the Institute of Industrial Science, The University of Tokyo, has sought a solution. As detailed in their new paper, to be issued in 2025 Symposium on VLSI Technology and Circuits , the team ditched the silicon and instead opted to create a transistor made from gallium-doped indium oxide (InGaOx). This material can be structured as a crystalline oxide, whose orderly, crystal lattice is well suited for electron mobility.
“We also wanted our crystalline oxide transistor to feature a ‘gate-all-around’ structure, whereby the gate, which turns the current on or off, surrounds the channel where the current flows,” explains Anlan Chen, lead author of the study. “By wrapping the gate entirely around the channel, we can enhance efficiency and scalability compared with traditional gates.”
With these goals in mind, the team got to work. The researchers knew that they would need to introduce impurities to the indium oxide by ‘doping’ it with gallium. This would make the material react with electricity in a more favorable way.
“Indium oxide contains oxygen-vacancy defects, which facilitate carrier scattering and thus lower device stability,” says Masaharu Kobayashi, senior author. “We doped indium oxide with gallium to suppress oxygen vacancies and in turn improve transistor reliability.”
The team used atomic-layer deposition to coat the channel region of a gate-all-around transistor with a thin film of InGaOx, one atomic layer at a time. After deposition, the film was heated to transform it into the crystalline structure needed for electron mobility. This process ultimately enabled the fabrication of a gate-all-around ‘metal oxide-based field-effect transistor’ (MOSFET).
“Our gate-all-around MOSFET, containing a gallium-doped indium oxide layer, achieves high mobility of 44.5 cm2/Vs,” explains Dr Chen. “Crucially, the device demonstrates promising reliability by operating stably under applied stress for nearly three hours. In fact, our MOSFET outperformed similar devices that have previously been reported.”
The efforts shown by the team have provided the field with a new transistor design that considers the importance of both materials and structure. The research is a step towards the development of reliable, high-density electronic components suited for applications with high computational demand, such as big data and artificial intelligence. These tiny transistors promise to help next-gen technology run smoothly, making a big difference to our everyday lives.
The article “A Gate-All-Around Nanosheet Oxide Semiconductor Transistor by Selective Crystallization of InGaOx for Performance and Reliability Enhancement” was issued in 2025 Symposium on VLSI Technology and Circuits. More

The effects of artificial intelligence on adolescents are nuanced and complex, according to a report from the American Psychological Association that calls on developers to prioritize features that protect young people from exploitation, manipulation and the erosion of real-world relationships.
“AI offers new efficiencies and opportunities, yet its deeper integration into daily life requires careful consideration to ensure that AI tools are safe, especially for adolescents,” according to the report, entitled “Artificial Intelligence and Adolescent Well-being: An APA Health Advisory.” “We urge all stakeholders to ensure youth safety is considered relatively early in the evolution of AI. It is critical that we do not repeat the same harmful mistakes made with social media.”
The report was written by an expert advisory panel and follows on two other APA reports on social media use in adolescence and healthy video content recommendations.
The AI report notes that adolescence — which it defines as ages 10-25 — is a long development period and that age is “not a foolproof marker for maturity or psychological competence.” It is also a time of critical brain development, which argues for special safeguards aimed at younger users.
“Like social media, AI is neither inherently good nor bad,” said APA Chief of Psychology Mitch Prinstein, PhD, who spearheaded the report’s development. “But we have already seen instances where adolescents developed unhealthy and even dangerous ‘relationships’ with chatbots, for example. Some adolescents may not even know they are interacting with AI, which is why it is crucial that developers put guardrails in place now.”
The report makes a number of recommendations to make certain that adolescents can use AI safely. These include:
Ensuring there are healthy boundaries with simulated human relationships. Adolescents are less likely than adults to question the accuracy and intent of information offered by a bot, rather than a human.

Creating age-appropriate defaults in privacy settings, interaction limits and content. This will involve transparency, human oversight and support and rigorous testing, according to the report.
Encouraging uses of AI that can promote healthy development. AI can assist in brainstorming, creating, summarizing and synthesizing information — all of which can make it easier for students to understand and retain key concepts, the report notes. But it is critical for students to be aware of AI’s limitations.
Limiting access to and engagement with harmful and inaccurate content. AI developers should build in protections to prevent adolescents’ exposure to harmful content.
Protecting adolescents’ data privacy and likenesses. This includes limiting the use of adolescents’ data for targeted advertising and the sale of their data to third parties.
The report also calls for comprehensive AI literacy education, integrating it into core curricula and developing national and state guidelines for literacy education.
“Many of these changes can be made immediately, by parents, educators and adolescents themselves,” Prinstein said. “Others will require more substantial changes by developers, policymakers and other technology professionals.”
Report: https://www.apa.org/topics/artificial-intelligence-machine-learning/health-advisory-ai-adolescent-well-being
In addition to the report, further resources and guidance for parents on AI and keeping teens safe and for teens on AI literacy are available at APA.org. More

Human-AI interactions are well understood in terms of trust and companionship. However, the role of attachment and experiences in such relationships is not entirely clear. In a new breakthrough, researchers from Waseda University have devised a novel self-report scale and highlighted the concepts of attachment anxiety and avoidance toward AI. Their work is expected to serve as a guideline to further explore human-AI relationships and incorporate ethical considerations in AI design.
Artificial intelligence (AI) is ubiquitous in this era. As a result, human-AI interactions are becoming more frequent and complex, and this trend is expected to accelerate soon. Therefore, scientists have made remarkable efforts to better understand human-AI relationships in terms of trust and companionship. However, these man-machine interactions can possibly also be understood in terms of attachment-related functions and experiences, which have traditionally been used to explain human interpersonal bonds.
In an innovative work, which incorporates two pilot studies and one formal study, a group of researchers from Waseda University, Japan, including Research Associate Fan Yang and Professor Atsushi Oshio from the Faculty of Letters, Arts and Sciences, has utilized attachment theory to examine human-AI relationships. Their findings were recently published online in the journal Current Psychology on May 9, 2025.
Mr. Yang explains the motivation behind their research. “As researchers in attachment and social psychology, we have long been interested in how people form emotional bonds. In recent years, generative AI such as ChatGPT has become increasingly stronger and wiser, offering not only informational support but also a sense of security. These characteristics resemble what attachment theory describes as the basis for forming secure relationships. As people begin to interact with AI not just for problem-solving or learning, but also for emotional support and companionship, their emotional connection or security experience with AI demands attention. This research is our attempt to explore that possibility.”
Notably, the team developed a new self-report scale called the Experiences in Human-AI Relationships Scale, or EHARS, to measure attachment-related tendencies toward AI. They found that some individuals seek emotional support and guidance from AI, similar to how they interact with people. Nearly 75% of participants turned to AI for advice, while about 39% perceived AI as a constant, dependable presence.
This study differentiated two dimensions of human attachment to AI: anxiety and avoidance. An individual with high attachment anxiety toward AI needs emotional reassurance and harbors a fear of receiving inadequate responses from AI. In contrast, a high attachment avoidance toward AI is characterized by discomfort with closeness and a consequent preference for emotional distance from AI.
However, these findings do not mean that humans are currently forming genuine emotional attachments to AI. Rather, the study demonstrates that psychological frameworks used for human relationships may also apply to human-AI interactions. The present results can inform the ethical design of AI companions and mental health support tools. For instance, AI chatbots used in loneliness interventions or therapy apps could be tailored to different users’ emotional needs, providing more empathetic responses for users with high attachment anxiety or maintaining respectful distance for users with avoidant tendencies. The results also suggest a need for transparency in AI systems that simulate emotional relationships, such as romantic AI apps or caregiver robots, to prevent emotional overdependence or manipulation.
Furthermore, the proposed EHARS could be used by developers or psychologists to assess how people relate to AI emotionally and adjust AI interaction strategies accordingly.
“As AI becomes increasingly integrated into everyday life, people may begin to seek not only information but also emotional support from AI systems. Our research highlights the psychological dynamics behind these interactions and offers tools to assess emotional tendencies toward AI. Lastly, it promotes a better understanding of how humans connect with technology on a societal level, helping to guide policy and design practices that prioritize psychological well-being,” concludes Mr. Yang. More

As artificial intelligence and smart devices continue to evolve, machine vision is taking an increasingly pivotal role as a key enabler of modern technologies. Unfortunately, despite much progress, machine vision systems still face a major problem: processing the enormous amounts of visual data generated every second requires substantial power, storage, and computational resources. This limitation makes it difficult to deploy visual recognition capabilities in edge devices — such as smartphones, drones, or autonomous vehicles.
Interestingly, the human visual system offers a compelling alternative model. Unlike conventional machine vision systems that have to capture and process every detail, our eyes and brain selectively filter information, allowing for higher efficiency in visual processing while consuming minimal power. Neuromorphic computing, which mimics the structure and function of biological neural systems, has thus emerged as a promising approach to overcome existing hurdles in computer vision. However, two major challenges have persisted. The first is achieving color recognition comparable to human vision, whereas the second is eliminating the need for external power sources to minimize energy consumption.
Against this backdrop, a research team led by Associate Professor Takashi Ikuno from the School of Advanced Engineering, Department of Electronic Systems Engineering, Tokyo University of Science (TUS), Japan, has developed a groundbreaking solution. Their paper, published in Volume 15 of the journal Scientific Reports on May 12, 2025, introduces a self-powered artificial synapse capable of distinguishing colors with remarkable precision. The study was co-authored by Mr. Hiroaki Komatsu and Ms. Norika Hosoda, also from TUS.
The researchers created their device by integrating two different dye-sensitized solar cells, which respond differently to various wavelengths of light. Unlike conventional optoelectronic artificial synapses that require external power sources, the proposed synapse generates its electricity via solar energy conversion. This self-powering capability makes it particularly suitable for edge computing applications, where energy efficiency is crucial.
As evidenced through extensive experiments, the resulting system can distinguish between colors with a resolution of 10 nanometers across the visible spectrum — a level of discrimination approaching that of the human eye. Moreover, the device also exhibited bipolar responses, producing positive voltage under blue light and negative voltage under red light. This makes it possible to perform complex logic operations that would typically require multiple conventional devices. “The results show great potential for the application of this next-generation optoelectronic device, which enables high-resolution color discrimination and logical operations simultaneously, to low-power artificial intelligence (AI) systems with visual recognition,” notes Dr. Ikuno.
To demonstrate a real-world application, the team used their device in a physical reservoir computing framework to recognize different human movements recorded in red, green, and blue. The system achieved an impressive 82% accuracy when classifying 18 different combinations of colors and movements using just a single device, rather than the multiple photodiodes needed in conventional systems.
The implications of this research extend across multiple industries. In autonomous vehicles, these devices could enable more efficient recognition of traffic lights, road signs, and obstacles. In healthcare, they could power wearable devices that monitor vital signs like blood oxygen levels with minimal battery drain. For consumer electronics, this technology could lead to smartphones and augmented/virtual reality headsets with dramatically improved battery life while maintaining sophisticated visual recognition capabilities. “We believe this technology will contribute to the realization of low-power machine vision systems with color discrimination capabilities close to those of the human eye, with applications in optical sensors for self-driving cars, low-power biometric sensors for medical use, and portable recognition devices,” remarks Dr. Ikuno.
Overall, this work represents a significant step toward bringing the wonders of computer vision to edge devices, enabling our everyday devices to see the world more like we do. More

A University of Nebraska-Lincoln engineering team is another step closer to developing soft robotics and wearable systems that mimic the ability of human and plant skin to detect and self-heal injuries.
Engineer Eric Markvicka, along with graduate students Ethan Krings and Patrick McManigal, recently presented a paper at the IEEE International Conference on Robotics and Automation in Atlanta, Georgia, that sets forth a systems-level approach for a soft robotics technology that can identify damage from a puncture or extreme pressure, pinpoint its location and autonomously initiate self-repair.
The paper was among the 39 of 1,606 submissions selected as an ICRA 2025 Best Paper Award finalist. It was also a finalist for the Best Student Paper Award and in the mechanism and design category.
The team’s strategy may help overcome a longstanding problem in developing soft robotics systems that import nature-inspired design principles.
“In our community, there is a huge push toward replicating traditional rigid systems using soft materials, and a huge movement toward biomimicry,” said Markvicka, Robert F. and Myrna L. Krohn Assistant Professor of Biomedical Engineering. “While we’ve been able to create stretchable electronics and actuators that are soft and conformal, they often don’t mimic biology in their ability to respond to damage and then initiate self-repair.”
To fill that gap, his team developed an intelligent, self-healing artificial muscle featuring a multi-layer architecture that enables the system to identify and locate damage, then initiate a self-repair mechanism — all without external intervention.
“The human body and animals are amazing. We can get cut and bruised and get some pretty serious injuries. And in most cases, with very limited external applications of bandages and medications, we’re able to self-heal a lot of things,” Markvicka said. “If we could replicate that within synthetic systems, that would really transform the field and how we think about electronics and machines.”
The team’s “muscle” — or actuator, the part of a robot that converts energy into physical movement — has three layers. The bottom one — the damage detection layer — is a soft electronic skin composed of liquid metal microdroplets embedded in a silicone elastomer. That skin is adhered to the middle layer, the self-healing component, which is a stiff thermoplastic elastomer. On top is the actuation layer, which kick-starts the muscle’s motion when pressurized with water.

To begin the process, the team induces five monitoring currents across the bottom “skin” of the muscle, which is connected to a microcontroller and sensing circuit. Puncture or pressure damage to that layer triggers formation of an electrical network between the traces. The system recognizes this electrical footprint as evidence of damage and subsequently increases the current running through the newly formed electrical network.
This enables that network to function as a local Joule heater, converting the energy of the electric current into heat around the areas of damage. After a few minutes, this heat melts and reprocesses the middle thermoplastic layer, which seals the damage — effectively self-healing the wound.
The last step is resetting the system back to its original state by erasing the bottom layer’s electrical footprint of damage. To do this, Markvicka’s team is exploiting the effects of electromigration, a process in which an electrical current causes metal atoms to migrate. The phenomenon is traditionally viewed as a hindrance in metallic circuits because moving atoms deform and cause gaps in a circuit’s materials, leading to device failure and breakage.
In a major innovation, the researchers are using electromigration to solve a problem that has long plagued their efforts to create an autonomous, self-healing system: the seeming permanency of the damage-induced electrical networks in the bottom layer. Without the ability to reset the baseline monitoring traces, the system cannot complete more than one cycle of damage and repair.
It struck the researchers that electromigration — with its ability to physically separate metal ions and trigger open-circuit failure — might be the key to erasing the newly formed traces. The strategy worked: By further ramping up the current, the team can induce electromigration and thermal failure mechanisms that reset the damage detection network.
“Electromigration is generally seen as a huge negative,” Markvicka said. “It’s one of the bottlenecks that has prevented the miniaturization of electronics. We use it in a unique and really positive way here. Instead of trying to prevent it from happening, we are, for the first time, harnessing it to erase traces that we used to think were permanent.”
Autonomously self-healing technology has potential to revolutionize many industries. In agricultural states like Nebraska, it could be a boon for robotics systems that frequently encounter sharp objects like twigs, thorns, plastic and glass. It could also revolutionize wearable health monitoring devices that must withstand daily wear and tear.

The technology would also benefit society more broadly. Most consumer-based electronics have lifespans of only one or two years, contributing to billions of pounds of electronic waste each year. This waste contains toxins like lead and mercury, which threaten human and environmental health. Self-healing technology could help stem the tide.
“If we can begin to create materials that are able to passably and autonomously detect when damage has happened, and then initiate these self-repair mechanisms, it would really be transformative,” Markvicka said. More