Study of the pyrolysis mechanism of SiBCN polymer precursor

The pyrolysis mechanisms occurring during the conversion of polyborosilazane (PBSZ) into amorphous SiBCN cerasmic have been investigated. TGA–TDG experiment have been applied to investigate the mass loss behaviour during ceramization. Solid-state 11B, 13C and 29Si NMR spectroscopy has been applied to probe the local environment of all NMR active nuclei in the precursor, the thermolysis intermediates and the ceramic residue. IR spectroscopy has been performed to receive valuable information on the chemical bonding in all materials. At temperature below 400oC, Si-N bonds are formed via condensation reaction involving N-H and Si-H units with hydrogen released. It is followed by evolution of hydrocarbons due to the cleavage of bonds and formation of methane and hydrogen at 600 oC. After heating to 1000 oC, ceramization complete and free carbon, BN3 domains as well as Si–C–N units coexist SiCxN4-x,x=0,1,2,3. And BN3 keep unchanged during the whole ceramization stage

Unsupervised Prototype Adapter for Vision-Language Models

Recently, large-scale pre-trained vision-language models (e.g. CLIP and ALIGN) have demonstrated remarkable effectiveness in acquiring transferable visual representations. To leverage the valuable knowledge encoded within these models for downstream tasks, several fine-tuning approaches, including prompt tuning methods and adapter-based methods, have been developed to adapt vision-language models effectively with supervision. However, these methods rely on the availability of annotated samples, which can be labor-intensive and time-consuming to acquire, thus limiting scalability. To address this issue, in this work, we design an unsupervised fine-tuning approach for vision-language models called Unsupervised Prototype Adapter (UP-Adapter). Specifically, for the unannotated target datasets, we leverage the text-image aligning capability of CLIP to automatically select the most confident samples for each class. Utilizing these selected samples, we generate class prototypes, which serve as the initialization for the learnable prototype model. After fine-tuning, the prototype model prediction is combined with the original CLIP's prediction by a residual connection to perform downstream recognition tasks. Our extensive experimental results on image recognition and domain generalization show that the proposed unsupervised method outperforms 8-shot CoOp, 8-shot Tip-Adapter, and also the state-of-the-art UPL method by large margins.Comment: Accepted by PRCV 202

Learning to Adapt CLIP for Few-Shot Monocular Depth Estimation

Pre-trained Vision-Language Models (VLMs), such as CLIP, have shown enhanced performance across a range of tasks that involve the integration of visual and linguistic modalities. When CLIP is used for depth estimation tasks, the patches, divided from the input images, can be combined with a series of semantic descriptions of the depth information to obtain similarity results. The coarse estimation of depth is then achieved by weighting and summing the depth values, called depth bins, corresponding to the predefined semantic descriptions. The zero-shot approach circumvents the computational and time-intensive nature of traditional fully-supervised depth estimation methods. However, this method, utilizing fixed depth bins, may not effectively generalize as images from different scenes may exhibit distinct depth distributions. To address this challenge, we propose a few-shot-based method which learns to adapt the VLMs for monocular depth estimation to balance training costs and generalization capabilities. Specifically, it assigns different depth bins for different scenes, which can be selected by the model during inference. Additionally, we incorporate learnable prompts to preprocess the input text to convert the easily human-understood text into easily model-understood vectors and further enhance the performance. With only one image per scene for training, our extensive experiment results on the NYU V2 and KITTI dataset demonstrate that our method outperforms the previous state-of-the-art method by up to 10.6\% in terms of MARE.Comment: Accepted by WACV 202

Recent progress in carbon-based electrochemical catalysts: From structure design to potential applications

Advances in research and development of carbon-based metal-free electrocatalysts (C-MFECs) have provided potential alternatives to precious metal catalysts for various reactions important to renewable energy and environmental remediation. This timely but critical review provides an overview of recent breakthroughs (within the past 5 years or so) on C-MFECs in all aspects, including the design and regulation of intrinsic catalytic active sites, design and synthesis of carbon composite and hybrid carbon catalysts, mechanism understanding, and potential applications in clean energy storage and energy/chemical conversion. Current challenges and future opportunities in the field of metal-free carbon electrocatalysis are also discussed to provide forward-looking opportunities for their potential applications in various catalytic processes of practical significance

Strain-induced enhancement of TcT_c in infinite-layer Pr0.8_{0.8}Sr0.2_{0.2}NiO2_2 films

The mechanism of unconventional superconductivity in correlated materials remains a great challenge in condensed matter physics. The recent discovery of superconductivity in infinite-layer nickelates, as analog to high-Tc cuprates, has opened a new route to tackle this challenge. By growing 8 nm Pr0.8Sr0.2NiO2 films on the (LaAlO3)0.3(Sr2AlTaO6)0.7 substrate, we successfully raise the transition temperature Tc from 9 K in the widely studied SrTiO3-substrated nickelates into 15 K. By combining x-ray absorption spectroscopy with the first-principles and many-body simulations, we find a positive correlation between Tc and the pre-edge peak intensity, which can be attributed to the hybridization between Ni and O orbitals induced by the strain. Our result suggests that structural engineering can further enhance unconventional superconductivity, and the charge-transfer property plays a crucial role in the pairing strength.Comment: 8 pages, 4 figure

Correction: Multi-angle tracking synthetic kinetics of phase evolution in Li-rich Mn-based cathodes

Correction for ‘Multi-angle tracking synthetic kinetics of phase evolution in Li-rich Mn-based cathodes’ by Shenyang Xu et al., Energy Environ. Sci., 2024, https://doi.org/10.1039/d3ee04199a. The affiliation for the author Tianyi Li should have read as follows: X-Ray Science Division, Argonne National Laboratory, Lemont, IL 60439, USA. The Royal Society of Chemistry apologises for these errors and any consequent inconvenience to authors and readers

Result of a year-long animal survey in a state-owned forest farm in Beijing, China

BackgroundArtificial forest can have great potential in serving as habitat to wildlife, depending on different management methods. As the state-owned forest farms now play a new role in ecological conservation in China, the biological richness of this kind of land-use type is understudied. Once owned by a mining company, a largest state-owned forest farm, Jingxi Forest Farm, has been reformed to be a state-owned forest farm with the purpose of conservation since 2017. Although this 116.4 km2 forest farm holds a near-healthy montaine ecosystem very representative in North China, a large proportion of artificial coniferous forest in the forest farm has been proven to hold less biodiversity than natural vegetation. This situation, however, provides a great opportunity for ecological restoration and biodiversity conservation. Therefore, from November 2019 to December 2020, we conducted a set of biodiversity surveys, whose results will serve as a baseline for further restoration and conservation.New informationHere, we report the result of a multi-taxa fauna diversity survey conducted in Jingxi Forest Farm mainly in year 2020 with explicit spatial information. It is the first survey of its kind conducted in this area, revealing a total of 19 species of mammals, 86 birds, four reptiles, two amphibians and one fish species, as well as 101 species of insects. Four species of mammals are identified as data-poor species as they have less than 100 occurrence records with coordination in the GBIF database. One species of insect, representing one new provincial record genus of Beijing, is reported

Human Streptococcus suis Outbreak, Sichuan, China

Streptococcus suis outbreak was associated with exposure to sick or dead pigs