The electrochemical carbon dioxide (CO2) reduction reaction is a promising approach to mitigate atmospheric CO2 accumulation and achieve carbon neutrality, but it is severely limited by low catalytic activity, poor selectivity, and the competing hydrogen evolution reaction (HER). Herein, a 3-aminopropyltriethoxysilane (APTES) molecule modification of spiky bimetallic Au/Ag nanostars is designed to enhance the catalytic activity and selectivity and suppress the HER for the CO2 electroreduction to CO. A remarkable CO Faraday efficiency was increased by 20% from 61% to 81% at -0.9 V vs reversible hydrogen electrode after the APTES modification, along with enhanced catalytic activity and stability. Operando electrochemical surface-enhanced Raman spectroscopy reveals APTES modification not only stabilizes the key *COOH intermediate to promote its conversion to *CO but also tailors the interfacial water structure rendering K+-H2O to strengthen CO2 activation and suppress HER. This study proves molecular modification is an efficient way to enhance CO2 electroreduction performance, providing a rational design strategy for high-selectivity CO2 electroreduction electrocatalysts.

Small data sets make developing calibration models using deep neural networks difficult because it is easy to overfit the system. We developed two deep neural network architectures by revising two existing network architectures: the U-Net and the attention mechanism. The major changes were to use 1D convolutional layers to replace the fully connected layers. We also designed and combined average pooling and maximum pooling in our revised networks, respectively. We applied these revised network architectures to three publicly available data sets and the resulting calibration models can generate acceptable results for general quantitative analysis. It also generated rather good results for data sets that concern calibration transfer. It demonstrates that constructing network architectures by properly revising existing successful network architectures may provide additional choices in the exploration of the application of deep neural network in analytical chemistry.

Reduced-state sulfur nanodots (r-SDs) with reducibility, satisfactory fluorescence properties and high stability were synthesized for the sensitive and selective analysis of metal ions, including Hg2+, Fe3+ and Cu2+. The reduction property of SDs was discovered for the first time, and the detailed reduction mechanisms of r-SDs were investigated. The reducibility of r-SDs exhibits the in situ reduction of Au3+ to Au nanoparticles (AuNPs/r-SDs) and also the reduction of Fe3+ and Cu2+ to Fe2+ and Cu+, respectively. On the one hand, selective analysis of Hg2+ can be achieved through dual-mode fluorescence and colorimetric probes of thymine-modified AuNPs/r-SDs (T-AuNPs/r-SDs) on account of the special bonding of T-Hg2+-T, as verified by density functional theory simulations. Furthermore, the fluorescent probes r-SDs-1, 10-Phenanthroline (r-SDs-Phen) and r-SDs-neocuproine (r-SDs-Nc) were applied to the quantitative analysis of Fe3+ and Cu2+ by the specific recognition of Phen-Fe2+ and Nc-Cu+ after the reduction of Fe3+ and Cu2+ to Fe2+ and Cu+ by r-SDs. The linear ranges of T-AuNPs/r-SDs, r-SDs-Phen, and r-SDs-Nc for Hg2+, Fe3+, and Cu2+ were 5.0–70.0 nmol/L (fluorescence), 10.0–500.0 nmol/L (colorimetric), 1.0–100.0 μmol/L, and 1.0–50.0 μmol/L, with limits of detection of 0.82 nmol/L, 4.05 nmol/L, 0.36 μmol/L, and 0.56 μmol/L, respectively. In addition, good recoveries for practical applications in environmental water samples can be obtained to confirm the analysis accuracy. The successful results provided a new idea for the application of nanomaterials with reducibility and fluorescence properties in analytical chemistry.

Alpha-glucosidase (alpha-Glu) plays a crucial role in regulating the normal physiological function of the body; therefore, alpha-Glu activity detection is crucial in clinical studies. In this study, a nickel-based metal-organic framework (Ni-MOF) co-doped with sulfur dots (SDs) and iron (Fe) was designed and constructed for the colorimetric detection of alpha-Glu. The SDs/Fe/Ni-MOF shows a very low Michaelis-Menten constant (0.0466 mM) for H2O2, suggesting a very high affinity for H2O2. Additionally, the free radicals generated by the nanozymecatalyzed reaction were analyzed, and the feasibility of the nanozyme-catalyzed process was further verified using density functional theory. The bimetallic (Fe and Ni) can improve the catalytic activity of the material, and sulfur can improve the affinity with the substrate to further enhance the catalytic performance. Notably, hydroquinone (HQ) inhibits nanozyme activity, whereas alpha-Glu hydrolyzes alpha-arbutin (alpha-Arb) and subsequently produces HQ. Therefore, this study developed a method for detecting alpha-Glu activity using alpha-Arb as a substrate. This method has high selectivity, a wide detection range (1.00-100 U L-1), and a low detection limit (0.525 U L-1). Finally, the method was used to alpha-Glu activity detected in serum samples with good accuracy. This study provides a new method for the detection of alpha-Glu.

分析化学简答题是分析化学习题和考试中常用的考查形式.传统的做法更多是采用文字表述的方式进行解题,而文字的叙述其实并不清晰,容易产生歧义.本文介绍基于"量"的观念,采用严格的数学分析的方法来解答分析化学的简答题,使得解答过程更为严谨,更易于理解.

The detection of pharmaceuticals has been a matter of concern among scientists and health researchers in the past few decades. However, it is still difficult to realize the sensitivity and selectivity detection of pharmaceuticals with similar structures. Herein, the pharmaceutical molecules of 2-mercaptobenzimidazole (MBI) and 2-mercaptobenzothiazole (MBT) with so similar structures can be selectively detected by surface-enhanced Raman spectroscopy (SERS) taking advantage of the fingerprint identification on Au/MIL-101(Cr), with sensitive detection limits of 0.5 ng·mL-1 for MBI and 1 ng·mL-1 for MBT. MBI is selectively enriched by Au/MIL-101(Cr) from the mixture solution and detected by SERS below 30 ng·mL-1. MBI can also be selectively detected in the serum samples with a detection limit of 10 ng·mL-1. Density functional theory calculations combined with the SERS experiments explained that the high sensitivity and selectivity are caused by the intrinsic differences in Raman intensity and different adsorption energies from the pharmaceutical molecules adsorbed on Au/MIL-101(Cr), respectively. This study provides an effective way to enrich and detect pharmaceutical molecules with similar structures.

A simple deep convolutional neural network architecture had been developed and applied to the establishment of a quantitative model based on near infrared spectroscopy techniques. The network architecture only contained general convolutional layers and dilated convolutional layers. The determination coefficient was used as a criterion to stop the training process of the neural network. Three data sets were used to test the performance of the neural network. The major results are (1) quantitative model can be established within one million iterations; (2) the quantitative model established on one spectrometer can be applied to other spectrometers of same manufacturer and even the same kind of spectrometer of different manufacturer; (3) simultaneous quantitative analysis of four components in grain samples. This study provided a new strategy to apply techniques of deep neural network in quantitative analysis.

A dual mode optical sensor for mercury ion (Hg 2+ ) was fabricated by using new techniques. We first synthesized reduced state SDs (r-SDs) via sublimed sulfur with PEG-400 under alkaline conditions. The r-SDs were then used to reduce chloroauric acid to form gold nanoparticles (AuNPs) without the addition of any other reducers or stabilizers. The AuNPs/r-SDs composites were finally modified by thymine (T-AuNPs/r-SDs). The T-AuNPs/r-SDs demonstrated high selectivity for Hg 2+ that the fluorescence intensity was enhanced while the UV–vis absorption spectra at about 530 nm were reduced and generated a new absorption band at about 700 nm in the presence of Hg 2+ . The T-AuNPs/r-SDs composites were used to dual-mode fluorescence and colorimetric quantitative detection of Hg 2+ in water. The limit of detection for fluorescence and colorimetric methods were about 0.82 nM and 4.05 nM, respectively. Rather good results were obtained when the sensor was applied to determine Hg 2+ in environmental water samples.

A new dual-mode ratiometric fluorescence and colorimetric probe for selective determination of Cu2+ was developed based on blue-emission sulfur quantum dots (SQDs) and yellow-emission carbon quantum dots (CQDs). The fluorescence and absorbance of CQDs increased in the presence of Cu2+ due to the Cu2+ -oxidized o-phenylenediamine group on the surface of the CQDs. Because of the inner filter effect between SQDs and CQDs-Cu2+, the fluorescence response of SQDs decreased following the introduction of Cu2+. Furthermore, in the presence of Cu2+, the dual-mode SQD–CQD probe showed visible color changes under both ultraviolet light and sunlight. Under optimal conditions, the dual-mode probe was used to quantitatively detect Cu2+ with a linear range of 0.1–5.0 μM for ratiometric fluorescence and colorimetry, with a limit of detection of about 31 nM and 47 nM, respectively. Finally, the dual-mode probe was used for the determination of Cu2+ in practical samples to expand the practical application, and the difference between ratiometric fluorescence and colorimetric methods was compared. The recovery results confirmed the high accuracy of the dual-mode probe, showing that it has immense potential for sensitive and selective detection of Cu2+ in practical samples.

介绍一个酸碱滴定和配位滴定辅助教学软件包.该软件包的核心部分基于酸碱滴定通式和配位滴定通式用C++语言编写而成.本软件包设计成以参数文件方式控制运行,用户只需根据一定的规则编写参数文件即可计算复杂体系的酸碱滴定和配位滴定曲线.本软件包还提供了图形用户界面,使应用更为方便.本软件包可用于酸碱滴定和配位滴定分析理论的辅助教学.

A novel fluorescent probe based on sulfur quantum dots (SQDs) was fabricated for sensitive and selective detection of tetracycline (TC) in milk samples. The blue emitting SQDs were synthesized via a top-down method with assistance of H2O2. The synthesized SQDs showed excellent monodispersity, water solubility and fluorescence stability, with a quantum yield (QY) of 6.30%. Furthermore, the blue fluorescence of the obtained SQDs could be effectively quenched in the presence of TC through the static quenching effect (SQE) and inner filter effect (IFE) between TC and SQDs. Under the optimum conditions, a rapid detection of TC could be accomplished within 1 min and a wide linear range could be obtained from 0.1 to 50.0 μM with a limit of detection (LOD) of 28.0 nM at a signal-to-noise ratio of 3. Finally, the SQD-based fluorescent probe was successfully applied for TC determination in milk samples with satisfactory recovery and good relative standard deviation (RSD). These results indicate that the SQD-based fluorescent probe shows great potential in practical analysis of TC in real samples with high rapidity, selectivity, and sensitivity.

: Analytical chemistry has a breadth of audience in colleges and universities, because it is one of the basic courses for most disciplines. As analytical chemistry course starts at the early college year, it will play important influence on the formation of the correct ideological and political opinion of students. The authors made deep exploration on the ideological and political elements in classroom teaching of acid-base titration, complexation titration and Ringbom’s equation. The results show that ideological and political elements can be integrated into teaching process if we hold the idea of cultural inheritance and innovation.

This paper provides a primary analysis and discuss on the mathematization of quantitative analysis. By analyzing the present situation of chemical quantitative analysis, instrumental analysis and chemometrics in the establishment and application of mathematical theories, it pointed out that the mathematization of quantitative analysis has not been realized. The mathematization of quantitative analysis should be realized by establishing mathematical equation that contains chemical parameters, is self-contained and can be evolved into mathematical theorem.

We provide a solution for absolute analysis that has been an unrealized goal for decades. We performed hard modeling of a titration curve to generate a calculation formula to directly estimate the stoichiometric point directly. We show that the method error is negligible when the formation constant of a titration reaction is moderately large. Two examples are given to show how to apply the developed theory in practical quantitative analysis.

A 44-year-old woman was transferred to the ICU of the First Affiliated Hospital of Jinan University for 2 days of persistent epigastric pain and 7 hours of unconsciousness. Her admission diagnosis was severe acute necrotizing pancreatitis (hypertriglyceridemia type) with multiple organ dysfunctions. The results of CT revealed a small area of necrotizing pancreatitis, which was not consistent with the severe clinical manifestations. Considering lack of hair and history of postpartum hemorrhage, hormone examination was carried out. According to the results of the examination, she was further diagnosed as Sheehan's syndrome and pituitary crisis. After hormone replacement therapy, her condition improved rapidly.

当前国内外的分析化学教材中滴定终点误差的计算方式尚未达成统一.国内流行采用林帮公式,但此公式存在许多的问题.本文从终点误差的主流定义出发对林帮的终点误差计算式进行了理论分析.结果表明林帮公式的终点误差值必然与主流定义得到的结果不同.本工作可以为合理地确立滴定终点误差计算式提供理论依据.

Gold nanoparticles (GNPs) have always been used as doxorubicin (DOX) transport vectors for tumor diagnosis and therapy; however, the synthesis process of these vectors is to prepare GNPs via chemical reduction method firstly, followed by conjugation with DOX or specific peptides, so these meth•ods faced some common problems including multiple steps, high cost, time consuming, complicated preparation, and post-processing. Here, we present a one-step strategy to prepare the DOX-conjugated GNPs on the basis of DOX's chemical constitution for the first time. Moreover, we prepare a multifunctional GNPs (DRN-GNPs) with a one-step method by the aid of the reductive functional groups possessed by DOX, RGD peptides, and nuclear localization peptides (NLS), which only needs 30 min. The results of scattering images and cell TEM studies indicated that the DRN-GNPs could target the Hela cells' nucleus. The tumor inhibition rates of DRN-GNPs via tumor and tail vein injection of nude mice were 66.7% and 57.7%, respectively, which were significantly enhanced compared to control groups. One step synthesis of multifunctional GNPs not only saves time, materials, but also it is in line with the development direction of green chemistry, and it would lay the foundation for large-scale applications within the near future. Our results suggested that the fabrication strategy is efficient, and our prepared DRN-GNPs possess good colloidal stability in the physiological system; they are a potentially contrast agent and an efficient DOX transport vector for cervical cancer diagnosis and therapy.

New bimetallic gold/silver nanoclusters (NCs) are reported that display strong blue fluorescence with excitation/emission maxima at 370/455 nm, decay times of around 14 ns for the main components, and a quantum yield of around 20%. The NCs were synthesized by using L-tryptophan (L-Trp) as the template to react with tetrachloroauric acid and silver nitrate at 120 °C for 4 h in a one-pot reaction. Their fluorescence is around 5 times stronger than that of pure gold nanoclusters. The fluorescence of the bimetallic NCs is strongly reduced in the presence of the antitumor drugs methotrexate (MTX) and doxorubicin (DOX) due to an inner filter effect. Response to MTX is linear in the 2.5–150 μM concentration range, and to DOX in the 2.5–150 μM concentration range. The detection limits are as low as 2.5 nM and 3 nM, respectively. The recoveries from spiked serum are between 87.7% - 101.2% for MTX and between 86.2%–105.4% for DOX.

Novel graphitic carbon nitride nanocones (g-CNNCs) were synthesized for the first time in this study. The SEM, TEM, XPS and FT-IR were used to research the structure of the g-CNNCs. We found that the g-CNNCs showed high selective and sensitive for fluorescence enhancement detection of Pb2+ ion via covalent interaction. In addition, the g-CNNCs exhibit stable and specific concentration-dependent fluorescence intensity in the presence of Pb2+ ion in the range of 1-200 mu mol.dm(-3), and the limit of detection was estimated to be 0.0438 mu mol.dm(-3) (3S/k). More importantly, the g-CNNCs were used to detect practical samples with satisfactory results. (C) 2019 Elsevier B.V. All rights reserved.

Sensor array was used to rapidly evaluate the composition and content of volatile organic compounds (VOCs) in tobacco package materials. Abstract odor factor maps (AOFMs) extracted from signal data of sensor array were used as characteristic map of samples, and then similarity measure was implemented to evaluate VOCs in samples. By using this method, 8 types of packing paper samples with different VOCs and 2 types of packing paper samples with similar composition and content of VOCs were determined. As comparisons, principal component analysis (PCA) only discriminated 2 types of samples and parallel factor analysis (PARAFAC) discriminated 6 samples. Hence, similarity measurement of AOFMs provided higher recognition accuracy than the other two methods. The advantages of this method were in three aspects, basing on a correct signal model targeted to sensor array, employing an objective and well. defined evaluation standard, and using standard deviation of samples' signal data to assist evaluation.