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China is currently the world's top carbon emitter due to the acceleration of urbanization, the rapid growth of energy consumption and the rise in carbon emissions, with the construction industry leading the three energy sectors in terms of emission reduction potential. Among the various sectors, the construction industry holds immense potential for emission reduction, with public buildings playing a crucial role. In China, the expansion of public building spaces is closely linked to the pace of urbanization and contributes to a rising share of total building area. Public buildings, characterized by high energy usage, offer a great opportunity for energy conservation and emission reduction. Changsha is experiencing rapid growth and change, and the city is becoming more industrialized and urbanized, which leads to a prominent contradiction between energy supply and demand. There is also great potential for energy conservation and emission reduction in public buildings. Additionally, Changsha is an important node city in the Yangtze River urban agglomeration and the middle reaches of the Yangtze River Economic Belt. It is a typical area that has hot summer and cold winter, thus Changsha is selected as the research case to examine the carbon emission path of public buildings. The primary influencing factors of carbon emissions of public buildings in Changsha City are determined by using the LMDI factor decomposition method addition model. The scenario analysis method is adopted to set the two energy consumption forecast scenarios, which are the baseline scenario and the green scenario. Based on LEAP model and GREAT framework structure, the LEAP prediction model is constructed to predict the carbon emissions of public buildings in Changsha City from 2021 to 2035. The Baseline scenario indicates that while carbon emissions from public buildings in Changsha continue to rise, they are expected to decline starting in 2030. The peak carbon emission of 34.279 million tons of CO2 is predicted for 2032. In contrast, the Green scenario reveals a significantly slower growth rate in carbon emissions from public buildings, with the peak carbon emission projected to reach 27.054 million tons in 2030. This aligns with China's national goal. The findings of this study support the accuracy of the long-term prediction of the model, and offer recommendations for energy conservation and emission reduction in Changsha. This study also provides an example and certain guidance for other provinces and cities that have similar development models and climate conditions. Pertinent development strategies serve as a point of reference for other typical hot summer and cold winter regions.

This study aimed to compare the postoperative analgesic efficacy and motor recovery of a novel lumbar plexus block (LPB) with that of a femoral nerve block (FNB) after total knee arthroplasty (TKA). Forty patients who underwent TKA were randomised equally into an lumbar plexus and sciatic nerve (LS) group (receiving novel LPB) and an femoral and sciatic nerves (FS) group (receiving FNB). The assessed variables were the onset time of pain, time to the first analgesic request, pain scores, motor block at 6, 12, and 24 h after TKA, and the number of patients receiving successful blockade for each branch of the lumbar plexus. In the LS group, the femoral, lateral femoral cutaneous, genitofemoral, iliohypogastric, ilioinguinal, and obturator nerves were blocked in 18, 20, 16, 18, 15, and 19 patients. Compared to the FS group, the LS group had a significantly shorter onset time of pain and time to the first analgesic request, a significantly larger total postoperative dose of sufentanil, significantly higher numeric rating scale scores for both rest and dynamic pain at 6, 12, and 24 h, and faster motor recovery. Novel ultrasound-guided LPB has a high blocking success rate and provides inferior postoperative analgesia, but faster motor recovery after TKA than FNB.

Na-ion batteries (SIBs) require novel anode materials which have high ion storage capability and low working voltage to make SIBs competitive compared to Li-ion batteries (LIBs). From this perspective, we present the origin of improved electrochemical performances of phosphate doped hard carbon (P-HC) which can meet the two requirements mentioned above through combining experiment with the calculations of atomic/electronic structures. We disclosed that the capacity enhancement is accompanied by the changed voltage profile, which results from the introduced phosphate functional groups. The emerged redox peak turned out to be generated by the electrochemical reaction of Na ions near the phosphate-carbon environment. First-principles calculations elaborated that the phosphate introduction here generates electron holes near the Fermi level that is generally considered as evidence of p-type semiconductors to improve electronic conductivity. This expectation has been proven by comparatively measuring the electrical conductivities of pristine hard carbon and P-HC. A close investigation into charge distribution indicated that the electron hole is generated mainly by the higher reducibility of the doped phosphate than the surrounding carbon atoms in P-HC. This discovery well explains the underlying principles for the enhanced electrochemical performance of P-HC, thereby showing a way to design highly functional hard carbon structures toward higher capacity with Na ions.

The rapidly growing technological demand for lithium-ion batteries has prompted the development of novel cathode materials with high energy density, low cost, and improved safety. High voltage spinel, LiNi0.5Mn1.5O4 (LNMO), is one of the most promising candidates yet to be commercialized. The two primary obstacles for this material are the inferior electronic conductivity and fast capacity degradation in full cells due to the high operating voltage. By systematically addressing these limitations, we successfully develop a thick LNMO electrode with areal capacity loadings up to 3 mAh·cm−2. The optimized thick electrode is paired with a commercial graphite anode at both the coin cell and pouch cell level, achieving a full cell capacity retention as high as 72% and 78%, respectively, after 300 cycles. We attribute this superior cycling stability to careful optimizations of cell components and testing conditions, with a specific focus improving electronic conductivity and high voltage compatibility. These results suggest precise control of materials quality, electrode architecture and electrolyte optimization can soon support the development of a cobalt-free battery system based on a thick LNMO cathode (>4 mAh·cm2), which will eventually meet the needs of next-generation Li-ion batteries with reduced cost, improved safety, and assured sustainability.

As the key equipment of long-distance oil and gas pipeline stations, the tubular heater system of the long-distance pipeline in China has realized the automatic control based on the solidification procedure of PLC by now. However, due to its complex dynamic characteristics and cumbersome process flow, the research on unattended intelligent operation technology of the heater is still in the initial stage. Herein, the current situation of the automatic control system for tubular heater of the long-distance pipeline in China was analyzed, and the technical framework was put forward for the intelligent operation of tubular heater for the long-distance oil and gas pipeline according to the development concept of “intelligent pipeline and intelligent pipeline network”. On this basis, the key technologies that restrict the unattended intelligent operation of tubular heater were discussed, with the solutions proposed and technical prospects made. Specifically, the supporting equipment of tubular heater was intellectualized through the intelligent upgrading technology of supporting equipment and the optimization technology of I/O points. Finally, the intelligent operation and perception of the heater was finally achieved with the intelligent monitoring video system of the station based on the intelligent control technology integrated with the neural network and PID, as well as the forecasting, early warning and fault diagnosis technology of the heater, thus facilitating the intelligent construction of the long-distance oil and gas pipeline station.