AI meets nuclear physics: toward more accurate photonuclear cross sections
Peer-Reviewed Publication
Updates every hour. Last Updated: 21-Jul-2025 10:11 ET (21-Jul-2025 14:11 GMT/UTC)
Researchers from Shanghai Institute of Applied Physics and Shanghai Advanced Research Institute utilized Bayesian neural networks (BNN) to achieve highly reliable fitting of photonuclear (γ,n) reaction cross-sections, significantly improving prediction accuracy and generalization capabilities. This advancement enhances the efficiency of experimental data usage and paves the way for future progress in nuclear astrophysics and radiation detection technologies.Researchers from Shanghai Institute of Applied Physics and Shanghai Advanced Research Institute utilized Bayesian neural networks (BNN) to achieve highly reliable fitting of photonuclear (γ,n) reaction cross-sections, significantly improving prediction accuracy and generalization capabilities. This advancement enhances the efficiency of experimental data usage and paves the way for future progress in nuclear astrophysics and radiation detection technologies.
In a research paper, scientists from the Tsinghua University proposed a novel enhanced Digital Light Processing (DLP) 3D printing technology, capable of printing composite magnetic structures with different material sin a single step. Furthermore, a soft robot with a hard magnetic material-superparamagnetic material composite was designed and printed.
Triboelectric nanogenerators (TENGs) represent a cutting-edge class of devices for energy conversion and self-powered sensing. The selection of appropriate triboelectric and conductive materials is critical in determining the performance of TENGs. In recent years, MXenes, particularly Ti3C2 MXene, have emerged as promising candidates for triboelectric/conductive materials in TENGs. To elucidate the multifaceted roles of MXenes, this review examines their applications from a materials science perspective. The applications are categorized into four types based on the functional layers of TENGs where MXenes are applied: (1) MXene films as conductive layers, (2) MXene films as triboelectric layers, (3) MXene nanosheets as fillers in polymer-based triboelectric layers, and (4) MXene films as charge trapping layers. The rationale and advantages of utilizing MXenes in each application are analyzed and elucidated. Owing to their unique combination of properties, including electronegativity, electrical conductivity and flexibility, MXenes demonstrate remarkable versatility in all functional layers, either as pure films or composite films. Systematic analysis reveals that MXene composite films are particularly promising for the applications. This review represents the first comprehensive attempt to classify MXene applications in TENGs and articulate their inherent advantages, thereby providing a foundation for the design and development of high-performance MXene-based TENGs.
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The BRICS nations have committed to reach carbon neutrality: Brazil and South Africa by 2050, China and Russia by 2060, and India by 2070. A joint study by researchers from Tsinghua and Shanghai Jiaotong universities shows that achieving such targets necessitates a significant increase in electrification and non-fossil fuel use, with 65% to 82% of energy to be supplied from renewables and 55% to 80% in form of electricity. Besides, carbon capture and removal technologies will play an important role, which are expected to contribute 27% to 64% of emission reductions after 2030 across BRICS. The mitigation costs vary by country, ranging from 250 to 390 USD per ton of CO2 by the carbon neutrality year. Annual investments in the energy sector are projected to be equivalent to 0.8%–3.5% of GDP.
Nano Research Energy has been selected for inclusion in the Web of Science™ (Emerging Sources Citation Index).
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Researchers from Jiangxi Normal University in China and Institute of Botany, Chinese Academy of Sciences have investigated the influence of road networks on the floristic collections in China. Their findings reveal that floristic collections have increasingly clustered around roads from 1960s to 2010s, suggesting an increased reliance of biological surveys on road networks.
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