Ultra-fast self-assembly and stabilization of reactive nanoparticles in reduced graphene oxide films.

Nanoparticles hosted in conductive matrices are ubiquitous in electrochemical energy storage, catalysis and energetic devices. However, agglomeration and surface oxidation remain as two major challenges towards their ultimate utility, especially for highly reactive materials. Here we report uniformly distributed nanoparticles with diameters around 10 nm can be self-assembled within a reduced graphene oxide matrix in 10 ms. Microsized particles in reduced graphene oxide are Joule heated to high temperature (∼1,700 K) and rapidly quenched to preserve the resultant nano-architecture. A possible formation mechanism is that microsized particles melt under high temperature, are separated by defects in reduced graphene oxide and self-assemble into nanoparticles on cooling. The ultra-fast manufacturing approach can be applied to a wide range of materials, including aluminium, silicon, tin and so on. One unique application of this technique is the stabilization of aluminium nanoparticles in reduced graphene oxide film, which we demonstrate to have excellent performance as a switchable energetic material

Overview and prospect of the detection capability of China's first precipitation measurement satellite FY-3G

Based on introducing the technical characteristics of FY-3G, which is China's first precipitation measurement satellite and successfully launched at 09∶36 BT on April 16 in 2023, this paper focuses on the precipitation detection capabilities and application prospect in rainstorm monitoring of FY-3G. The results show that, with an orbit at 407 km and an inclination angle of 50°, and equipped with a dual-frequency Ka/Ku band precipitation measurement radar, microwave, and optical imaging instruments, the FY-3G satellite can detect the three-dimensional structure of disastrous weather systems such as typhoon, heavy rainfall, and other strong convection events in most of China. At the design level, FY-3G has precipitation detection capabilities comparable to the current US Second Generation Global Precipitation Measurement Program (GPM) Core Satellite (GPMCO), but better payload types, quantities, and channel settings compared with the GPMCO satellite. After the service operation, the FY-3G satellite, together with other polar-orbiting meteorological satellites such as FY-3 AM, PM, and EM, as well as high-orbit geostationary satellites, will form the Fengyun precipitation detection constellation system, which will improve the overall precipitation detection capability of the Fengyun Satellite constellation and provide stronger basic support for meteorological disaster prevention and mitigation

Protein target highlights in CASP15: Analysis of models by structure providers

We present an in-depth analysis of selected CASP15 targets, focusing on their biological and functional significance. The authors of the structures identify and discuss key protein features and evaluate how effectively these aspects were captured in the submitted predictions. While the overall ability to predict three-dimensional protein structures continues to impress, reproducing uncommon features not previously observed in experimental structures is still a challenge. Furthermore, instances with conformational flexibility and large multimeric complexes highlight the need for novel scoring strategies to better emphasize biologically relevant structural regions. Looking ahead, closer integration of computational and experimental techniques will play a key role in determining the next challenges to be unraveled in the field of structural molecular biology

Neuromatch Academy: a 3-week, online summer school in computational neuroscience

Neuromatch Academy (https://academy.neuromatch.io; (van Viegen et al., 2021)) was designed as an online summer school to cover the basics of computational neuroscience in three weeks. The materials cover dominant and emerging computational neuroscience tools, how they complement one another, and specifically focus on how they can help us to better understand how the brain functions. An original component of the materials is its focus on modeling choices, i.e. how do we choose the right approach, how do we build models, and how can we evaluate models to determine if they provide real (meaningful) insight. This meta-modeling component of the instructional materials asks what questions can be answered by different techniques, and how to apply them meaningfully to get insight about brain function

Carbon Welding by Ultrafast Joule Heating

Carbon nanomaterials exhibit outstanding electrical and mechanical properties, but these superior properties are often compromised as nanomaterials are assembled into bulk structures. This issue of scaling limits the use of carbon nanostructures and can be attributed to poor physical contacts between nanostructures. To address this challenge, we propose a novel technique to build a 3D interconnected carbon matrix by forming covalent bonds between carbon nanostructures. High temperature Joule heating was applied to bring the carbon nanofiber (CNF) film to temperatures greater than 2500 K at a heating rate of 200 K/min to fuse together adjacent carbon nanofibers with graphitic carbon bonds, forming a 3D continuous carbon network. The bulk electrical conductivity of the carbon matrix increased four orders of magnitude to 380 S/cm with a sheet resistance of 1.75 Ω/sq. The high temperature Joule heating not only enables fast graphitization of carbon materials at high temperature, but also provides a new strategy to build covalently bonded graphitic carbon networks from amorphous carbon source. Because of the high electrical conductivity, good mechanical structures, and anticorrosion properties, the 3D interconnected carbon membrane shows promising applications in energy storage and electrocatalysis fields

Carbon Welding by Ultrafast Joule Heating

Carbon nanomaterials exhibit outstanding electrical and mechanical properties, but these superior properties are often compromised as nanomaterials are assembled into bulk structures. This issue of scaling limits the use of carbon nanostructures and can be attributed to poor physical contacts between nanostructures. To address this challenge, we propose a novel technique to build a 3D interconnected carbon matrix by forming covalent bonds between carbon nanostructures. High temperature Joule heating was applied to bring the carbon nanofiber (CNF) film to temperatures greater than 2500 K at a heating rate of 200 K/min to fuse together adjacent carbon nanofibers with graphitic carbon bonds, forming a 3D continuous carbon network. The bulk electrical conductivity of the carbon matrix increased four orders of magnitude to 380 S/cm with a sheet resistance of 1.75 Ω/sq. The high temperature Joule heating not only enables fast graphitization of carbon materials at high temperature, but also provides a new strategy to build covalently bonded graphitic carbon networks from amorphous carbon source. Because of the high electrical conductivity, good mechanical structures, and anticorrosion properties, the 3D interconnected carbon membrane shows promising applications in energy storage and electrocatalysis fields