查找使用阿拉丁产品的科研文献

Raman spectroscopy based detection of corrosive sulfur in transformer oil: Method and application

Ziyi Wang,Ruimin Song,Weigen Chen,Xinyuan Zhang,Pinyi Wang

In order to overcome the shortcomings of traditional methods for corrosive sulfur detection in transformer oil, Raman spectroscopy based detection is proposed in this paper. The widely concerned corrosive sulfur, Dibenzyl Disulfide (DBDS), was chosen as the characteristic molecule to be detected. A series of oil samples with different DBDS concentrations was prepared. And these samples were extracted by 1-methyl-2-pyrrolidinone for DBDS enrichment to improve the sensitivity of detection. Then Raman spectra of samples were obtained, and a linear model was established by analysing the relationship between the characteristic peak and the DBDS concentration. The limit of detection reached 7.98 mg/kg. For determining the DBDS concentrations causing sulfur corrosion, the sulfur weight content on the copper conductor surface was measured by Scanning Electron Microscope-Energy Dispersive Spectrometer after a corrosion test. The results show that the corrosion limitation highly depends on the type of transformer oil, and the Raman spectroscopy detection can meet the limit of detection requirement in practical condition. Finally, an on-site oil sample and five Lab-made samples were detected via our new method and the current Gas Chromatography-Mass Spectrometry based method. It is found that there is no significant divergence between the measurement results. And good applicability was also demonstrated in on-site sample test.

Thermodynamic Properties of Ternary Ionic Liquids as New Working Pairs for Absorption Heat Transformer

Hao Yunze,Gong Yutong,Liu Feng,Lv Yanlong,Wang Yuhao,Li Jinping

In response to increasing energy demands, absorption heat transformers (AHTs) have been widely employed as efficient energy conversion devices across various fields. However, existing working pairs (e.g., LiBr/H 2 O and NH 3 /H 2 O) exhibit high corrosiveness and limited thermal stability, significantly restricting their applicability in high-temperature environments. Therefore, the development of high-performance working pairs is crucial for improving the efficiency and stability of AHT systems. In this study, four groups of ionic liquid-based ternary matrix pairs: LiBr-[EMIM]Cl/H 2 O (1:2), LiBr-[EMIM]Cl/H 2 O (1:3), LiBr-[EMIM][DEP]/H 2 O (1:3), and LiBr-[EMIM][DMP]/H 2 O (1:3), were systematically evaluated through short-term corrosion experiments. The effects of corrosiveness, thermal stability, density, viscosity, and specific heat capacity were analyzed. Experimental results and data analysis clarified the high-temperature properties of ionic liquids, while thermogravimetric analysis and viscosity measurements were conducted to evaluate the relative merits of different working pairs. Results indicate that the LiBr-[EMIM]Cl/H 2 O (1:2) system exhibits the lowest corrosiveness and good thermal stability, making it suitable for corrosion-sensitive AHT systems, while the LiBr-[EMIM][DMP]/H 2 O (1:3) system demonstrates optimal thermal stability at high temperatures, rendering it a complementary solution for high-temperature applications. This study establishes an experimental basis for optimizing AHT working pairs and provides essential data to inform their selection in AHT systems.

Preparation and characterisation of carboxymethyl-chitosan/sodium phytate composite membranes for adsorption in transformer oil

Kewang Zheng,Wei Li,Wei Wang,Hujian Chen,Chaofan Huang,Qiaolin Ren,Caiqin Qin

Adsorption of metal impurities from transformer oil was studied using a novel porous membrane. A solution of N , O ‑carboxymethyl‑chitosan (CMC) and sodium phytate (SP) was blended to prepare a novel porous membrane for the metal impurities adsorption from transformer oil. The chemical structure of the membranes was characterised by their FTIR spectra, scanning electron microscopy (SEM), thermogravimetric analysis (TGA), and video camera observations. The effects of the SP content of the membrane, contact time, and contact temperature on adsorption of copper, iron, and aluminium impurities were studied. The FTIR spectra and thermogravimetric curves of the membranes indicated good compatibility between CMC and SP. The SEM and video camera observations suggested that CMC-SP composite membranes had a mature, porous structure. The experimental results showed that the SP content significantly affected the adsorption capacity of a CMC membrane. The maximum adsorption percentages of elemental copper, iron, and aluminium were 88.12%, 82.35%, and 80.36% when the SP ratio was 80% at 60 °C.

A rapid method for determination of acid value in transformer oil by PPy modified electrode

Xiong Ying,He De-liang,Feng Yong,Zhou Zhou,Chang Xin-yuan,Liu Fu-rong

A polypyrrole-modified glassy carbon electrode (PPy/GC electrode) was prepared and its electrocatalytic behavior towards naphthoquinone in the presence of acid was characterized by linear sweep voltammetry (LSV). A well-defined new reduction peak appeared at a more positive potential than the original reduction peak. The new reduction peak current was linearly related to the acid value (AV) of oil. Based on it, a rapid electrochemical method for determining AV of transformer oil was developed using PPy/GC electrode. A working curve was obtained in the AV range of 0.01 to 0.40 mg(KOH)·g −1 , with a sensitivity of 39.42 μA 0.5 /(mg(KOH)·g −1 ) and the detection limit of 0.0014 mg(KOH)·g −1 (signal-to-noise ratio is 3, standard deviation is 2.247%). Moreover, the proposed method has been successfully applied to AV determination of several transformer oil samples with advantages of rapidness, high sensitivity and accuracy compared to the conventional method.

Adsorption performance of activated bentonite, zeolite 13X and activated carbon for aminophenazone in transformer oil

Peng Fu,Jian Wu,Yihua Qian,Jiayu Chen,Jiajin Huang,Jing Wu,Yaohong Zhao,Qibin Xia

Aminophenazone (AP) is one kind of harmful additives in transformer oil. It results in a significant drop of the insulation property of transformer oil and thus leads to substation accidents. Adsorption method has proved to be an efficient approach for AP removal. In this work, activated bentonite, zeolite 13X, and activated carbon were chosen as adsorbents for the separation of AP from the polluted transformer oil. At 25 ℃ and initial AP content is 400 ppmw, the AP uptake of activated bentonite (151.2 mg/g) is much higher than that of zeolite 13X (52.1 mg/g) and activated carbon (45.0 mg/g). The desorption activation energy (E d ) of AP on the three adsorbents follow in the order: activated bentonite (115.73 kJ/mol) > activated carbon (52.51 kJ/mol) > zeolite 13X (51.23 kJ/mol). Activated bentonite exhibits the highest AP uptake due to the existence of acidic sites that can strongly interact with alkaline AP and the pore sizes that facilitate AP molecules to more easily enter into the adsorbent channels. Activated bentonite is an industrially promising adsorbent for the removal of AP from the polluted transformer oil.

A versatile nano-transformer for efficient localization-specific imaging and synergistic therapy of bladder cancer

Fanqi Liu,Chang Guo,Xindi Li,Yumin Li,Suying Xu,Tony D. James,Leyu Wang

A stepwise morphologic transformation is highly desirable but rarely reported for promoting drug penetration at tumor sites via reducing transport barriers. Herein, an adhesive multifunctional nano-transformer (CTMF NPs) with cascading structural transformation was constructed, which afforded tumor microenvironment (TME)-activatable zero-background 19 F-magnetic resonance imaging and ratiometric photoacoustic imaging-guided synergistic tumor therapy. CTMF NPs were synthesized via a one-pot encapsulation and dynamic coordination strategy, where copper sulfide nanoparticles (CuS NPs, photothermal agent) were co-encapsulated with perfluoro-15-crown-5-ether (PFCE, 19 F MRI agent) by the dopamine grafted amphiphilic polymer, followed by coating with metal (Mn 2+ )-polyphenol shell ( 19 F signal quencher and therapeutic agent). Benefiting from polyphenol enhanced cell adherence as well as in situ generated reactive quinone , the CTMF NPs attached to tumor sites and exhibited efficient internalization under TME promoted decomposition and oxidation . Moreover, these nano-platforms were further decomposed under laser irradiation , which amplified cellular oxidative stress , leading to mitochondrial structural damage and dysfunction, as well as facilitating cuproptosis by interfering with the lipoylated tricarboxylic acid cycle . Cell apoptosis subsequently resulted in significant immunogenic cell death and afforded a versatile nano-transformer for precise imaging-guided bladder cancer therapy.

Efficient Photocatalytic Reduction of Cr(VI) on N-Doped Sludge/Cellulose-Derived Porous Carbon Using Synergistic Experimental–Deep Learning Approach

Na Huang,Shengwen Chen,Wanhe Du

The photocatalytic reduction of hexavalent chromium (Cr(VI)) in wastewater represents a critical environmental challenge, given its high toxicity and mobility in wastewater. Conventional optimization methods relying on repetitive batch experiments with excessive reagent consumption. Herein, we proposed a synergistic experimental–deep learning approach to realize efficient photocatalytic reduction of Cr(VI). Sludge and cellulose precursors were used to prepare N-doped porous carbon through a green fabrication method at low temperature. After optimizing the composition and experimental factors, the removal efficiency of Cr(VI) could reach 92.7% after visible light irradiation in an acidic environment. The high efficiency originated from the coupled adsorption and photocatalytic mechanism. Innovatively, after comparing three algorithms, TCN and Transformer were employed to predict the desirable removal efficiency with <5% prediction error under different reaction conditions. This work highlights the novel experimental–deep learning method for heavy metal remediation using N-doped waste-derived porous carbon.

Tuning Epoxy for Medium Frequency Transformer Application: Resin Optimization and Characterization of Nanocomposites at High Temperature

Muhammad Awais,Xiangrong Chen,Chao Dai,Fan-Bo Meng,Ashish Paramane,Yasuhiro Tanaka

Fabrication of pH-sensitive cellulose colorimetric papers for rapid detection of water content in transformer oil

Kai Xu,Xuefeng Zhang,Ming Zhang,Lanhe Zhang,Zicheng Chen

The combination of highly hydrophilic plant fiber and water molecule sensitive material can effectively detect the water content in transformer oil. In this study, two types of rapid response cellulose colorimetric papers (Rp and Bp) were fabricated through a simple impregnation method, with cellulosic fiber serving as the substrate, cresol red/thymol blue as the color developer, boric acid as the pH regulator, and silica aerosol as the filler. Rp and Bp were tested and analyzed using various characterization methods, and their performance in detecting bound water content in transformer oil was investigated. The results indicate that Rp changes from magenta to light yellow and Bp changes from lavender to light yellow with the increase of water content of transformer oil. The water content detection accuracy of both is 92 % and 95 %, respectively. The rapid color change of them is due to boric acid's acidity triggering molecular structure changes in the color developers. After six cycles of use, Rp and Bp still exhibited excellent color-changing properties. Therefore, colorimetric papers have the attributes of rapidity, high efficiency, low cost, and desired accuracy, providing an alternative approach for evaluating transformer oil's water content and showing promising application potential.

Transformer-driven Ag@5/Ag-Cu@20/PSS SERS Biosensor for Early Diagnosis of Hepatobiliary Diseases

Zelong Li,Xuemei Lin,Zengshan Yu,Guochao Shi,Wenying Zhou,Jiahao Cui,Shan Guo,Mingli Wang

Accurate and sensitive detection of bilirubin, cholic acid, and Alanine aminotransferase (ALT) is essential for the early detection of hepatobiliary diseases in healthcare and the medical field. Integrating surface-enhanced Raman scattering (SERS) with deep learning algorithm has shown great application prospect in the early identification of markers of hepatobiliary diseases. Here, an regular Ag decorated Cu-Ag nanoisland-liked SERS biosensor (Ag@5/Ag-Cu@20/PSS) was constructed by using pattered sappire substrate as a template. An additional 5 mins of Ag nanofilm significantly improved the SERS signal intensity and homogeneity, and the sensitivity was enhanced by two orders of magnitude up to 10^-10 M for 4-aminothiophenol (4-ATP). Importantly, deep learning algorithms included temporal convolutional networks (TCN), convolutional neural networks (CNN), recurrent neural network (RNN) and Transformer were used to deeply mine SERS spectral data of bilirubin, cholic acid and ALT, extract effective features, and establish an accurate classification and prediction model. Results indicating that the developed SERS biosensor combined with Transformer model demonstrated excellent accuracy (ACC) of 0.9816±0.0090 in qualitatively and quantitatively analyzing of bilirubin, cholic acid, and ALT. The successful application of the SERS biosensor will help improve the accuracy of early identification of bilirubin, cholic acid, and ALT disease markers and promote the early intervention and treatment of hepatobiliary diseases.

Efficient surface Hydroxyl-to-Hydroxyl radical conversion on layered double hydroxide via High-Efficiency hydroxyl Transformer

Xiaoyu Li,Yuying Wang,Jiahong Zou,Xing’an Dong,Linpiao Cheng,Wenyang Fu,Yan Jiang,Guangming Jiang,Shams Ali Baig

Promoting the activation of surface or edges hydroxyl groups in layered double hydroxides (LDHs) to facilitate its conversion to hydroxyl radicals (·OH) in photocatalytic process has received wider attention in research communities. However, the pristine LDHs are unable to convert surface or edges hydroxyl groups to ·OH with the energy of visible light illumination, so it is necessary to structurally modulate them to improve their conversion of surface hydroxyl groups to ·OH under light illumination. Herein, we innovatively combined nickel-iron layered double hydroxide (NiFe-LDHs, hydroxyl groups library) with bismuth carbonate oxide ((BiO) 2 CO 3 , BOC, ·OH generator), enabling a sustained and efficient transformation of hydroxyl groups on the surface or edges of NiFe-LDHs into ·OH. Mechanism studies supported by in-situ spectroscopic analyses and theoretical simulations, showed that under the visible light illumination the hot holes generated on energy band-matched BOC can capture OH - located at the surface/edge of NiFe-LDHs nanosheets and further convert them into ·OH and efficiently promoted the oxidation of NO to NO 3 - . The NO removal efficiency of BOC/NiFe-LDHs composite material is about 54.5%, which was 2.23 times that of the original BOC.

Protocol for cerebrospinal fluid analysis using enrichment-enhanced surface-enhanced Raman spectroscopy and transformer-enabled spectral classification

Zhaoyi Li,Dongjie Zhang,Zhaoyang Cheng,Hanju Zhang,Huandi Li,Lin Shi,Nan Wang,Qi Zeng,Xueli Chen

The rapid detection and precise classification of cerebrospinal fluid in acute leukemia patients constitute a crucial clinical imperative. Here, we present a protocol for cerebrospinal fluid analysis deep learning with enrichment-enhanced surface-enhanced Raman spectroscopy (DL-SERS) detection and transformer-enabled spectral classification. We describe steps for preparing SERS-active materials and samples and acquiring SERS spectral data. We then detail procedures for deep learning-based classification. This protocol enables highly sensitive and efficient identification of acute leukemia patients. For complete details on the use and execution of this protocol, please refer to Zhang et al. 1