90% of Science Is Lost: Frontiers’ revolutionary AI-powered service transforms data sharing to deliver breakthroughs faster
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Updates every hour. Last Updated: 16-Dec-2025 16:11 ET (16-Dec-2025 21:11 GMT/UTC)
Most scientific data never fuel the discoveries they should.
For every 100 datasets created, around 80 remain in the lab, 20 are shared but rarely reused, fewer than two meet FAIR standards, and only one typically drives new findings.
The result: delayed cancer treatments, climate models short on evidence, and research that cannot be reproduced.
Frontiers, the open-science publisher, is tackling this problem with the launch of Frontiers FAIR² Data Management, the world’s first all-in-one, AI-powered service for research data. Designed to transform how data is shared so it is reusable and credited, it brings together curation, compliance checks, AI-ready packaging, peer review, an interactive portal, certification, and lifetime hosting in a single workflow — ensuring that research funded today delivers faster breakthroughs in health, sustainability, and technology tomorrow.
With growing concerns over fossil fuel depletion and the environmental impacts of petrochemical production, scientists are actively exploring renewable strategies to produce essential industrial chemicals. A collaborative research team—led by Distinguished Professor Sang Yup Lee, Senior Vice President for Research, from the Department of Chemical and Biomolecular Engineering, together with Professor Sunkyu Han from the Department of Chemistry at the Korea Advanced Institute of Science and Technology (KAIST)—has developed an integrated chemobiological platform that converts renewable carbon sources such as glucose and glycerol into oxygenated precursors, which are subsequently deoxygenated in the same solvent system to yield benzene, toluene, ethylbenzene, and p-xylene (BTEX), which are fundamental aromatic hydrocarbons used in fuels, polymers, and consumer products.
This review addresses cancer therapy limitations (systemic toxicity, multidrug resistance, MDR) via innovative nanoparticle (NP) platforms. Innovations include dual-phase liposomes (co-deliver hydrophilic/hydrophobic drugs, e.g., HA-functionalized ones for CD44⁺ brain tumors), green-synthesized metal NPs (low toxicity), MOF NPs (induce pyroptosis to boost immunity), and cell membrane-coated NPs (avoid RES clearance). It combines passive (EPR effect) and active (ligand-receptor) targeting.
Clinically, NPs reduce toxicity, enable delivery to hard-to-reach sites (e.g., brain), and overcome MDR. While long-term safety needs validation, NPs offer promise for personalized, less toxic oncology care.
Bochum, Germany, October 29, 2025, Researchers from Research Center for Future Energy Materials and Systems at the Ruhr University Bochum, Software for Chemistry & Materials BV, and Vrije Universiteit Amsterdam have demonstrated that modern universal machine learning interatomic potentials (uMLIPs) can now accurately describe systems ranging from single molecules to bulk solids, representing a significant leap forward for uMLIPs in materials science. The study introduces the 0123D dataset, comprising 40,000 diverse structures specifically designed to benchmark model performance across all dimensionalities.
A research paper by scientists at the Soochow University proposed a novel magnetically actuated device based on a hybrid electromagnetic coil and permanent magnet control system.
The research paper, published on Jun. 24, 2025 in the journal Cyborg and Bionic Systems, presented a hybrid magnetic actuation system that extends the functional capabilities of miniature ferrofluidic robot (MFR) through synergistic multi-physical interactions.
Researchers from the Technical University of Munich have developed URNet, a novel artificial intelligence model that helps autonomous driving systems perceive their surroundings more clearly—even in dark, fast-changing environments. By combining an unconventional “event camera” with a self-aware framework, URNet allows vehicles to build reliable 3D maps that measure how far objects are—a process known as depth estimation—while understanding how confident they should be about what they “see.” This innovation could make next-generation self-driving cars safer and more capable of navigating complex real-world conditions.
A research paper by scientists at the Harbin Institute of Technology proposed a novel centimeter-scale quadruped piezo robot. The robot’s locomotion is generated by multi-dimensional vibration trajectories at the feet, which are produced through a novel built-in actuation method.
The research paper, published on Jul. 22, 2025 in the journal Cyborg and Bionic Systems, presented a novel centimeter-scale quadruped piezoelectric robot with high integration and strong robustness, which promises to bring new perspectives for the construction and application of centimeter-scale robots.