Researchers at Incheon National University have developed biodegradable gas sensors designed to reduce electronic waste while improving air quality monitoring. The technology targets nitrogen dioxide, a pollutant linked to fossil fuel combustion and respiratory diseases.
The sensors are built using organic field-effect transistors, a lightweight and low-energy alternative suited for portable environmental monitoring devices. OFET-based systems are also easier to manufacture compared with traditional silicon electronics.
To create the sensing layer, the research team blended an organic semiconductor polymer, P3HT, with a biodegradable material, PBS. Each polymer was prepared separately in chloroform before being combined into a uniform solution.
Performance varied with solvent composition, with mixtures of chloroform and dichlorobenzene yielding the most consistent and sensitive sensor structures. High PBS concentrations remained effective without compromising detection accuracy.
Project lead Professor Park said the approach balances sustainability and performance, particularly for use in natural environments. The biodegradable design could contribute to long-term pollution monitoring and waste reduction.
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AI tools are already widely used in higher education, with more than half of surveyed students required to use them in coursework and nearly two-thirds using them for assignments. However, the survey suggests that students are largely learning to use AI on their own, relying mainly on informal experimentation rather than structured university-led training.
At the same time, awareness and participation in formal AI education remain limited. Only 31% of students said they were aware of AI-related courses offered by their college or university, and fewer than 20% had taken one, highlighting a gap between widespread use and institutional teaching.
Despite this, many students recognise AI’s growing importance for their careers. Around half believe proficiency with AI tools will be important in the future, reflecting expectations that AI skills will be increasingly valued in the workplace.
Overall, the findings point to an opportunity for universities to strengthen AI education by integrating practical, advanced, and ethical AI training into curricula, helping students move beyond basic use toward workplace-ready skills.
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Technology firms in China are rolling out large cash incentive campaigns to attract users to their AI chatbots ahead of the expected launch of new AI models later this month.
Alibaba Group has earmarked CNY 3 billion for users of its Qwen AI app, with the promotion beginning on 6 February to coincide with Lunar New Year celebrations.
Tencent Holdings and Baidu have announced similar offers, together committing around CNY 1.5 billion in cash rewards and consumer electronics, including smartphones and televisions.
To qualify for prizes, users must register on the platforms and interact with the chatbots during the promotional period by asking questions or completing everyday planning tasks.
The incentives reflect intensifying competition with global developers such as Google and OpenAI, while also strengthening efforts to position China-based firms as potential local AI partners for Apple in the Chinese market.
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Oracle is expanding AI data centres across the United States while pairing infrastructure growth with workforce development through its philanthropic education programme, Oracle Academy.
The initiative provides schools and educators with curriculum, cloud tools, software, and hands-on training designed to prepare students for enterprise-scale technology roles increasingly linked to AI operations.
As demand for specialised skills rises, Oracle Academy is introducing Data Centre Technician courses to fast-track learners into permanent roles supporting AI infrastructure development and maintenance.
The programme already works with hundreds of institutions across multiple US states, including Texas, Michigan, Wisconsin, and New Mexico, spanning disciplines from computer science and engineering to construction management and supply chain studies.
Alongside new courses in machine learning, generative AI, and analytics, Oracle says the approach is intended to close skills gaps and ensure local communities benefit from the rapid expansion of AI infrastructure.
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At the Summit for Clinical Operations Executives (SCOPE) 2026, major players in life sciences showcased artificial intelligence-enabled systems built to accelerate and optimise oncology clinical trials.
Massive Bio’s TrialRelay uses AI routing (“TrialRouter”) to orchestrate the enrolment process, reducing the risk that patients are lost in the referral pipeline after being matched to a study.
ConcertAI’s Accelerated Clinical Trials (ACT) platform, powered by its proprietary agentic AI, integrates real-world and proprietary datasets with advanced workflows to shorten trial timelines by 10–20 months, improve study design and reduce costly amendments, helping sponsors and contract research organisations (CROs) bring therapies to patients faster.
AI adoption in clinical research is rising across recruitment, trial design, data handling and operational forecasting, though integration challenges, regulatory alignment and rapid technological change remain obstacles.
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Web Summit Qatar is underway in Doha, drawing startups, investors, and technology leaders to discuss emerging trends shaping the global digital economy. Early sessions featured startup pitches, investor meetings, and discussions on AI, quantum technologies, and the creator economy.
More than 1,600 startups are taking part, with around 85% arriving from outside Qatar, joined by nearly 1,000 investors. Funds such as Amino Capital, Greycroft, and 500 Global are scouting opportunities, as journalists cover debates on tech geopolitics and innovation policy.
Germany is marking its strongest showing to date, bringing more than 200 startups, investors, and decision-makers. The German Pavilion showcases AI, cybersecurity, deep tech, and industrial innovation, highlighting plans to deepen cooperation with regional partners.
Beyond visibility, the summit emphasises partnerships, market entry, and long-term collaboration. Organisers and participants point to growing ties between Germany and Qatar as both countries seek to deepen cooperation across advanced technology and innovation ecosystems.
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European policymakers are sharpening their focus on digital sovereignty as concerns grow over the continent’s reliance on foreign technology providers. Control over key digital infrastructure and technologies is seen as vital to protecting Europe’s economic resilience.
At a fintech regulatory conference in Brussels, European Financial Services Commissioner Maria Luís Albuquerque stressed the need to retain control over core economic technologies. She warned that rising global isolationism is heightening the risks linked to external dependencies.
The comments reflected unease about Europe’s reliance on non-European tech companies, particularly those based in the United States. Such dependence, officials argue, could weaken Europe’s ability to protect its digital infrastructure and shape its own economic future.
Calls for greater digital autonomy are gaining momentum as the EU seeks to balance innovation with security. Policymakers see technological control as key to long-term stability, competitiveness, and strategic independence.
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Hamad Bin Khalifa University has unveiled the UNESCO Chair on Digital Technologies and Human Behaviour to strengthen global understanding of how emerging tools shape society.
An initiative, located in the College of Science and Engineering in Qatar, that will examine the relationship between digital adoption and human behaviour, focusing on digital well-being, ethical design and healthier online environments.
The Chair is set to address issues such as internet addiction, cyberbullying and misinformation through research and policy-oriented work.
By promoting dialogue among international organisations, governments and academic institutions, the programme aims to support the more responsible development of digital technologies rather than approaches that overlook societal impact.
HBKU’s long-standing emphasis on ethical innovation formed the foundation for the new initiative. The launch event brought together experts from several disciplines to discuss behavioural change driven by AI, mobile computing and social media.
An expert panel considered how GenAI can improve daily life while also increasing dependency, encouraging users to shift towards a more intentional and balanced relationship with AI systems.
UNESCO underlined the importance of linking scientific research with practical policymaking to guide institutions and communities.
The Chair is expected to strengthen cooperation across sectors and support progress on global development goals by ensuring digital transformation remains aligned with human dignity, social cohesion and inclusive growth.
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Bitcoin traded sideways on Tuesday after a short-lived rebound from a 10-month low, as caution continued to dominate derivatives markets. Early Asian trading saw limited movement, with prices hovering below $78,500 following a sharp sell-off the previous day.
Options positioning suggests nerves have yet to ease fully. Data from Deribit showed heavy put option concentrations around $75,000, marking a key support level, while the next downside area is seen closer to $70,000.
Although downside protection demand has softened, positioning indicates traders remain defensive.
Signals from perpetual futures markets reinforced the cautious tone. According to CryptoQuant, funding rates turned negative, their weakest since mid-2024, pointing to a market dominated by short sellers.
Implied volatility stayed elevated near 48.8, based on data from TradingView.
Some traders highlighted early signs of stabilisation after aggressive selling. Analysts at FalconX and STS Digital noted that a weekly close below $75,000 could reignite downside pressure, while holding above that level may support a near-term recovery.
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Scientists are increasingly applying generative AI models to address complex problems in materials science, such as predicting structures, simulating properties, and guiding the discovery of advanced materials with novel functions.
Traditional computational methods, such as density functional theory, can be slow and resource-intensive, whereas AI-based tools can learn from existing data and propose candidate materials more efficiently.
Early applications of these generative approaches include designing materials for energy storage, catalysis, and electronic applications, speeding up workflows that previously involved large amounts of trial and error.
Researchers emphasise that while AI does not yet replace physics-based modelling, it can complement it by narrowing the search space and suggesting promising leads for experimental validation.
The work reflects a broader trend of AI-augmented science, where machine learning and generative models act as accelerators for discovery across disciplines such as chemistry, physics and bioengineering.
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