الوسم: digital twin

  • Digital Twin Boosts EV Battery Charging Speed and Longevity

    Digital Twin Boosts EV Battery Charging Speed and Longevity

    Electric vehicle batteries may soon be able to charge more quickly and last longer through a groundbreaking approach that creates a virtual replica of the battery’s internal structure.

    At the Korea Advanced Institute of Science and Technology (KAIST), scientists developed a three-dimensional “digital twin” of a commercial lithium-ion battery electrode. Their research, featured in the journal InfoMat, highlights that battery performance is influenced not only by the materials inside the electrode but also by the precise placement of those materials.

    Fast charging remains one of the biggest hurdles for electric vehicles. Consumers want to recharge their cars within minutes instead of hours. However, pushing lithium ions into a battery at a high rate can cause damage and reduce its lifespan.

    A typical lithium-ion battery’s graphite anode contains graphite particles that store lithium, along with a binder that holds these particles together and tiny pores filled with electrolyte. During charging, lithium ions move through the electrolyte and enter the graphite. When charging occurs too rapidly, some lithium ions can’t enter the graphite fast enough and instead form metallic lithium deposits on the surface—a process known as lithium plating, which can harm the battery.

    Think of it like a traffic jam at a parking lot entrance: if too many cars arrive simultaneously and can’t get in, congestion builds up outside. Meanwhile, other changes happen inside the battery: a protective layer called the solid electrolyte interphase (SEI) forms on graphite particles. While a thin SEI is necessary, if it becomes too thick or uneven, it hampers battery performance. Additionally, as graphite particles absorb lithium, they expand, creating mechanical stress within the electrode. Since these processes occur at microscopic scales, pinpointing where issues develop is challenging.

    To better understand these microscopic dynamics, researchers led by Professor Kang Taek Lee reconstructed a real graphite anode in 3D. This digital model included individual graphite particles, binder material, and the pores through which lithium ions travel. They then simulated various conditions—altering electrode thickness, pore sizes, and binder distribution—to see how these factors affect fast charging.

    The findings revealed that the arrangement of binder material inside the electrode can have a significant impact. For a 50-micrometer-thick anode, different binder placements resulted in less than a 4% variation in overall charging capacity—differences so slight that traditional tests might overlook them. However, beneath the surface, the internal differences were substantial.

    When excess binder accumulated near the separator, it restricted pathways for lithium ions, creating traffic-like bottlenecks. This led to over 10% more lithium plating in some regions compared to electrodes with a more uniform binder distribution. Properly distributed binder allowed lithium ions to flow smoothly and helped form a more even SEI layer, which is essential for battery health.

    These effects became even more pronounced in thicker electrodes—say, an 83-micrometer anode—where variations in binder placement caused about an 18% difference in charging capacity. The placement of pores also mattered: regions with more open space could better accommodate the expansion of graphite particles, reducing mechanical stress, whereas tightly packed areas experienced more strain.

    The study suggests that future electric vehicle batteries should be designed with a microscopic level of precision. Instead of just selecting how much graphite, binder, or pore space to include, engineers need to carefully control where these materials are located. Digital twin technology offers an efficient way to virtually test different internal arrangements before manufacturing, potentially accelerating the development of batteries that can charge faster, store more energy, and last longer.

  • AI uncovers hidden emotional dangers of type 2 diabetes

    AI uncovers hidden emotional dangers of type 2 diabetes

    Loneliness, inadequate sleep, and mental stress may quietly elevate the risk of developing type 2 diabetes more than many realize.

    A recent study led by Anglia Ruskin University employed advanced artificial intelligence to examine how daily life experiences influence long-term health outcomes.

    Published in the journal Frontiers in Digital Health, the research indicates that emotional and social factors might be just as crucial as diet and physical health in predicting the likelihood of diabetes.

    Type 2 diabetes is among the fastest-growing health issues worldwide, affecting over 500 million individuals. It occurs when the body不能 effectively use insulin to regulate blood sugar levels.

    Unlike type 1 diabetes, which results from an autoimmune disorder, type 2 diabetes is closely tied to lifestyle choices and daily habits. Traditional prediction models often focus on simple indicators like body weight, age, and blood pressure, but this new study took a different approach.

    Researchers used a “digital twin” model—an AI-powered virtual replica of an individual’s health profile—that simulates how shifts in daily behaviors might influence health over years. Analyzing data from 19,774 adults in the UK Biobank, tracking their health for up to 17 years, the study focused mainly on lifestyle and emotional factors rather than clinical tests.

    The findings revealed that loneliness, sleep issues, and mental health struggles independently significantly increased the risk of developing type 2 diabetes. The presence of all three factors together amplified the predicted risk exponentially.

    The link appears to be related to the body’s stress response. Chronic stress can elevate hormone levels, trigger inflammation, and interfere with blood sugar regulation, potentially leading to diabetes over time.

    Further, the study observed that individuals under stress and with poor mental health often had poorer diets, consuming more processed foods and sugar—highlighting the complex interaction of lifestyle factors that heighten risk.

    Notably, higher risk estimates were observed among people from South Asian, African, and Caribbean backgrounds, reinforcing previous public health findings.

    This research underscores that diabetes risk involves more than just biological factors; psychological and social influences play critical roles. Using digital twin technology could enable healthcare providers to identify high-risk individuals earlier and intervene proactively before the disease manifests.

    However, limitations exist—these results are based on AI predictions rather than direct cause-and-effect evidence. Further research is needed to validate and translate these findings into practical care strategies.

    In essence, the study emphasizes the strong link between mental well-being and physical health, suggesting that improving sleep, reducing loneliness, and supporting mental health may significantly contribute to preventing type 2 diabetes in the future.

    For those interested in the connection between diet and diabetes, exploring studies on potatoes and diabetes or low-calorie diets’ potential to reverse the condition might be helpful.

    Additional insights are available on recent research about protein’s role in diabetes management and the surprising benefits of pineapple for those with diabetes.