SAN ANTONIO — September 16, 2025 — Southwest Research Institute (SwRI) and The University of Texas at San Antonio (UT San Antonio) are collaborating to create a detection system to identify pre-ignition in hydrogen internal combustion engines (H₂-ICE). Researchers will combine machine learning (ML) algorithms and artificial intelligence with onboard sensors to help detect pre-ignitions based on their tell-tale signs.

An artificial intelligence (AI) deep learning tool that estimates the malignancy risk of lung nodules achieved high cancer detection rates while significantly reducing false-positive results. 

A research team has unveiled a non-destructive, highly accurate approach for determining the optimal timing of embryo rescue sampling.

As the world transitions to clean energy, hydrogen produced via water electrolysis offers a sustainable solution. However, sluggish reaction kinetics and catalyst instability under alkaline conditions hinder large-scale adoption. A breakthrough by researchers at China University of Petroleum, Beijing, introduces a nitrogen-doped carbon (NC)-enhanced homologous heterojunction (Ni₃S₂-MoS₂/NC) that overcomes these limitations. By optimizing the built-in electric field (BEF) strength, the catalyst achieves record-low overpotentials and long-term stability in alkaline environments. This work demonstrates how strategic electronic engineering can unlock the full potential of heterostructures for green hydrogen production.

A research team introduces Plant-MAE, a self-supervised learning framework designed to automate 3D segmentation of plant organs from point cloud data.

Aging leads to mitochondrial dysfunction in periodontal ligament stem cells (PDLSCs), significantly impairing their osteogenic capacity—a critical barrier to bone regeneration in elderly populations. Researchers from Huazhong University of Science and Technology and Peking University demonstrated that replenishing aged PDLSCs with functional mitochondria from young counterparts restores mitochondrial integrity, reduces oxidative stress, and reactivates osteogenic capacity. This breakthrough, mediated by the AKAP1/cAMP/PKA signaling pathway, highlights mitochondrial replenishment as a promising therapeutic strategy for age-related bone defects and broader regenerative medicine applications.

Low-frequency electromagnetic response in microwave technology exhibits unprecedented demand, benefiting applications such as 5G communications, Wi-Fi, and radar systems. To date, the purest low-frequency response materials are induced by magnetic metals. However, magnetic metals will demagnetize at high temperatures and cannot serve in high-temperature environments. Here, we introduced a SiC/CoSi/CeSi composite co-modified with transition metal Co and rare earth metal Ce, achieving a 14-fold increase in reflection loss (RL) from -4.74 dB to -66.48 dB. The effective absorption bandwidth (EAB, RL≤-10 dB) is 2.46 GHz. With the SiC/CoSi/CeSi composite, the effective absorption frequency is shifted to the low-frequency band (3.65 GHz), and the high-temperature stability (500 °C) is maintained, inheriting 94.5% effective absorption. Radar cross-section (RCS) simulation further confirms the excellent stealth capability of the composite, reducing the target reflection intensity by 22.7 dB m². Mechanism investigation indicates that the excellent EMW absorption performance of the composite is attributed to multiple reflections and scattering, conduction losses, abundant interface polarization, and good magnetic loss. This research supplies critical inspiration for developing efficient SiC-based absorbers with both low-frequency and high-temperature responses.