Energy storage salt cavern construction and evaluation technology

With the demand for peak-shaving of renewable energy and the approach of carbon peaking and carbon neutrality goals, salt caverns are expected to play a more effective role in oil and gas storage, compressed air energy storage, large-scale hydrogen storage, and temporary carbon dioxide storage. In order to effectively utilize the underground space of salt mines on a sound scientific basis, the construction of salt caverns for energy storage should implement the maximum utilization of salt layers, improve the cavern construction efficiency, shorten the construction period, and ensure cavern safety. In this work, built upon design experience and on-site practice in salt cavern gas storage, the four pivotal construction stages-conceptual design, solution mining simulation, tightness assessment, and stability evaluation-have been thoroughly enhanced, strengthening the technical framework for salt cavern energy storage.Document Type: PerspectiveCited as: Wan, J., Meng, T., Li, J., Liu, W. Energy storage salt cavern construction and evaluation technology. Advances in Geo-Energy Research, 2023, 9(3): 141-145. https://doi.org/10.46690/ager.2023.09.0

Two-dimensional amine and hydroxy functionalized fused aromatic covalent organic framework

Ordered two-dimensional covalent organic frameworks (COFs) have generally been synthesized using reversible reactions. It has been difficult to synthesize a similar degree of ordered COFs using irreversible reactions. Developing COFs with a fused aromatic ring system via an irreversible reaction is highly desirable but has remained a significant challenge. Here we demonstrate a COF that can be synthesized from organic building blocks via irreversible condensation (aromatization). The as-synthesized robust fused aromatic COF (F-COF) exhibits high crystallinity. Its lattice structure is characterized by scanning tunneling microscopy and X-ray diffraction pattern. Because of its fused aromatic ring system, the F-COF structure possesses high physiochemical stability, due to the absence of hydrolysable weak covalent bonds

Ultrasensitive refractive index sensor based on graphene coated hollow core fiber

A high-quality nanolayer graphene (NLG) coated hollow core fiber (HCF) platform has been demonstrated for accurate monitoring of refractive index (RI) changes so far mainly operate in liquids but not in air. The NLG with high index is deposited on the outer surface of the HCF, and an enhanced anti-resonant reflecting guidance is formed, which induces sharp periodic lossy dips in the transmission spectrum. A cute experiment conducted interrogating the transmission intensity of the lossy dip demonstrates a high resolution of 2.73×10-6 RIU and a sensitivity of -365.9 dB/RIU, which is two or three times higher than that of intensity-modulated RI sensors reported previously. We believe that this configuration opens research directions for highly sensitive sensing in researches of chemistry, medicine, and biology

Fault diagnosis method of rolling bearing of mine main fan based on transfer learning

The condition monitoring and fault diagnosis of the rolling bearings of the main fan in the mine are significant to the safety of coal mine production. The existing fault diagnosis methods of rolling bearing have the problems of insufficient training and accuracy when applied directly in actual working conditions. Moreover, the rolling bearings of the mine main fan are in normal operation for a long time, and the number of normal samples is much more than the faulty samples, so there is a sample imbalance problem. Therefore, this paper proposes a fault diagnosis method for rolling bearings of mine main fan based on transfer learning. The method takes the conventional rolling bearing data as the source domain data and the mine main fan rolling bearing data as the target domain data. Firstly, the one-dimensional vibration signal is converted into two-dimensional SDP images using the SDP method, and then the conventional rolling bearing fault diagnosis model is trained using sufficient source domain image samples. After training, the parameters of the diagnostic model are transferred to the mine main fan rolling bearing fault diagnosis model, and the lower layer network is locked and the higher layer network of the model is fine-tuned by the target domain image samples during the transfer process, and finally the mine main fan rolling bearing fault diagnosis model with optimized parameter weights is obtained. Meanwhile, in order to solve the sample imbalance problem, a weighted cross-entropy loss function is added to the model for training, so that the diagnosis model gives higher weights to the fault samples as a minority class and pays more attention to the fault samples in the diagnosis process, thus improving the diagnosis accuracy. In order to verify the effectiveness of the proposed method, this paper uses a conventional rolling bearing fault test bench and the rolling bearing data of the mine main fan fan in actual working conditions for experimental verification. The results show that the proposed method can accurately identify and classify the operating status of the mine main fan rolling bearings, and the accuracy rate is 99.28%

Bis[bis­(2,2′-bipyridine-κ2 N,N′)chloridocopper(II)] bis­(μ-2,6-pyridine­dicarboxyl­ato)-κ4 O 2,N,O 6:O 6;κ4 O 2:O 2,N,O 6-bis­[aqua­dichloridobismuthate(III)] penta­hydrate

In the title compound, [CuCl(C10H8N2)2]2[Bi2Cl4(C7H3NO4)2(H2O)2]·5H2O, the dianion [Bi2Cl4(C7H3NO4)2(H2O)2]2− is located about an inversion center. The CuII atom of the cation is coordinated by four N atoms of the two chelating 2,2′-bypyridine ligands and one Cl− ion, completing a distorted trigonal–bipyramidal coordination environment. In the anion, each BiIII atom is seven-coordinate and is bonded to a tridentate pyridine-2,6-dicarboxyl­ate ligand, a water mol­ecule, two chloride ions and a bridging carboxyl­ate O atom of another carboxyl­ate ligand. The coordination geometry of BiIII is distorted penta­gonal–bipyramidal with the Cl− ions located in axial positions. The structure of the dianion is additionally stabilized by an intra­molecular O—H⋯O hydrogen bond between the coordinated water mol­ecule and carboxyl­ate O atom. In the crystal, O—H⋯O hydrogen bonds occur . The H atoms of the solvent water mol­ecules could not be located

Electrochemical Properties of Boron-Doped Diamond Electrodes Prepared by Hot Cathode Direct Current Plasma CVD

A series of boron-doped diamond (BDD) films were deposited by using a hot cathode direct current plasma chemical vapor deposition(HCDC-PCVD) system with different ratios of CH4/H2/B(OCH3)3 (trimethylborate) gas mixture. The morphology, structure and quality of BDD films were controled by SEM, XRD and Raman measurements. The electrochemical properties of the BDD films were investigated by electrochemical methods. Cyclic voltammetric performances of the BDD films indicated that the main determinant in the electrochemical characteristics of BDD films was the boron doping amount. The threshold potential for oxygen evolution increased from 1 V to 2.5 V. Meanwhile, the electrochemical potential window of BDD films was enlarged from 2.2 V to 4.5 V when the B content was increased from 1.75 × 1019cm-3 to 2.4 × 1021 cm−3. The cyclic voltammograms of BDD films in K4Fe(CN)6 and K3Fe(CN)6 mixed solution indicated that the behavior of Fe(CN)6-3/-4 redox couple could be regarded as semi-reversible

Competitive Fixed-Bed Adsorption of Pb(II), Cu(II), and Ni(II) from Aqueous Solution Using Chitosan-Coated Bentonite

Fixed-bed adsorption studies using chitosan-coated bentonite (CCB) as adsorbent media were investigated for the simultaneous adsorption of Pb(II), Cu(II), and Ni(II) from a multimetal system. The effects of operational parameters such as bed height, flow rate, and initial concentration on the length of mass transfer zone, breakthrough time, exhaustion time, and adsorption capacity at breakthrough were evaluated. With increasing bed height and decreasing flow rate and initial concentration, the breakthrough and exhaustion time were observed to favorably increase. Moreover, the adsorption capacity at breakthrough was observed to increase with decreasing initial concentration and flow rate and increasing bed height. The maximum adsorption capacity at breakthrough of 13.49 mg/g for Pb(II), 12.14 mg/g for Cu(II), and 10.29 mg/g for Ni(II) was attained at an initial influent concentration of 200 mg/L, bed height of 2.0 cm, and flow rate of 0.4 mL/min. Adsorption data were fitted with Adams-Bohart, Thomas, and Yoon-Nelson models. Experimental breakthrough curves were observed to be in good agreement (R2>0.85 and E%<50%) with the predicted curves generated by the kinetic models. This study demonstrates the effectiveness of CCB in the removal of Pb(II), Cu(II), and Ni(II) from a ternary metal solution

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Pattern changes in determinants of Chinese emissions

Chinese economy has been recovering slowly from the global financial crisis, but it cannot achieve the same rapid development of the pre-recession period. Instead, the country has entered a new phase of economic development – a "new normal". We use a structural decomposition analysis (SDA) and environmental input-output analysis (IOA) to estimate the determinants of China's carbon emission changes during 2005-2012. China's imports are linked to a global multi-regional input-output (MRIO) model based on the Global Trade and Analysis Project (GTAP) database to calculate the embodied CO2 emissions in imports. We find that the global financial crisis has affected the drivers of China's carbon emissions growth. From 2007 to 2010, the CO2 emissions induced by China's exports dropped, whereas emissions induced by capital formation grew rapidly. In the "new normal", the strongest factors that offset CO2 emissions have shifted from efficiency gains to structural upgrading. Efficiency was the strongest factor offsetting China's CO2 emissions before 2010 but drove a 1.4% increase in emissions in the period 2010-2012. By contrast, production structure and consumption patterns caused a 2.6% and 1.3% decrease, respectively, in China's carbon emissions from 2010 to 2012. In addition, China tends to shift gradually from an investment to a consumption-driven economy. The proportion of CO2 emissions induced by consumption had a declining trend before 2010 but grew from 28.6% to 29.1% during 2010-2012