Search

Electrochemical sensors play a crucial role in the detection of different analytes in complex matrices, and their performance is highly dependent on the electrode capacity. However, most of the available electrodes can only be used for single-component detection, so it is urgent to develop electrodes with high sensitivity and selectivity for different components. Herein, we report an amphiprotic amino-bonded carbon nanotube–Ag/Cu/Al nanoparticle/polystyrene-coated paper electrode (CNT–Ag–Cu–Al/PS electrode), which can be used for the measurement of glucose (Glc), oxytetracycline (OTC), and hydroquinone (HQ), respectively. The results showed that the analytical sensitivity and selectivity of the CNT–Ag–Cu–Al/PS electrode were comparable to those of single metal-coated paper substrate. The developed electrode also exhibited excellent linear responses for Glc, OTC, and HQ in the ranges of 1.0–1000.0 μM, 1.0 × 10−2to 10.0 μM, and 5.0 × 10−3to 50.0 μM, and the limits of detection (LODs) were 0.2055 μM (Glc), 0.0074 μM (OTC), and 0.0048 μM (HQ). Owing to the characteristics of good selectivity, anti-interference, stability, and reproducibility, the CNT–Ag–Cu–Al/PS paper electrode has been successfully applied to the detection of these analytes in complex human body fluids, food, and environmental waters. The paper electrode is promising for the detection of target compounds in complex matrices.

Electrospray-related ion sources are promising for direct mass spectrometric analysis of complex samples, but current protocols suffer from complicated components and low analytical sensitivity. Here, we propose a surface charge-induced electrospray ionization (SCIESI) inspired by flashover on an insulator surface under high voltage. This protocol not only effectively avoids contact between the sample solution and metal electrode, but also allows completion of the entire analytical process in less than 40 seconds and limits of detection in the pictogram per milliliter range. SCIESI coupled to mass spectrometry can also be used to monitor electro-chemical processes, and a number of oxidation and reduction reactions have been studied, demonstrating that it is a powerful tool for understanding electrochemical reaction mechanisms.

A fully integrated near-microphone keyword spotting (KWS) chip is proposed to directly interact with a passive microphone and achieve submicrowatt power for the Internet of Things (IoT) devices. First, an on-chip analog frontend (AFE) is designed to avoid the inclusion of power-intensive off-chip active microphones. Second, a real-point serial fast Fourier transform (FFT)-based Mel-frequency cepstral coefficient (MFCC) feature extractor, cooperating with a genetic algorithm (GA) optimized bit-width quantization, is specifically customized to reduce the MFCC power by 67.4%. Finally, a binarized temporal depthwise separable CNN (TDSCN) is proposed, featuring hardware optimization through a parallel adder tree (PAT)-based PE with near-memory computing. This results in a 78.9% reduction in computation as compared to the traditional depthwise separable convolutional neural networks (CNNs). Fabricated in a 28-nm CMOS process, the proposed KWS chip consumes the lowest power of 0.61 $\mu \text{W}$ at 0.36-V neural network (NN), 0.9-V AFE, and 8-KHz frequency, while keeping 95.8% accuracy for two-KWS on Google speech command dataset (GSCD).

As a widely used speech-triggered interface, deep-learning-based keyword spotting (KWS) chips require both ultra-low power and high detection accuracy. We propose a sub-microwatt KWS chip with an acoustic activity detection (AAD) to achieve the above two requirements, including the following techniques: first, an optimized feature extractor circuit using nonoverlapping-framed serial Mel frequency cepstral coefficient (MFCC) to save half of the computations and data storage; second, a zero-cost AAD by using MFCC’s 1st-order output to clock gate neural network (NN) and postprocessing (PP) unit, with 0 miss rate; third, a tunable detection window to adapt to different keyword lengths for better accuracy; and finally, a true form computation method to decrease data transitions and optimized PP. Implemented in a 28-nm CMOS process, this AAD-KWS chip has a 0.4-V supply, an 8-kHz frequency for MFCC, and a 200-kHz frequency for other parts. It consumes $0.36~\mu \text{W}$ in quiet scenarios when AAD is enabled and $0.8~\mu \text{W}$ in normal scenarios, where the MFCC circuit consumes only 170 nW. Its accuracy reaches 97.8% for two keywords in the Google Speech Command Dataset (GSCD).

Developing a general, highly efficient, and enantioselective catalytic method for the synthesis of chiral alcohols is still a formidable challenge. We report in this article the asymmetric transfer hydrogenation (ATH) of N-methyliminodiacetyl (MIDA) acylboronates as a general substrate-independent entry to enantioenriched secondary alcohols. ATH of acyl-MIDA-boronates with (het)aryl, alkyl, alkynyl, alkenyl, and carbonyl substituents delivers a variety of enantioenriched α-boryl alcohols. The latter are used in a range of stereospecific transformations based on the boron moiety, enabling the synthesis of carbinols with two closely related α-substituents, which cannot be obtained with high enantioselectivities using direct asymmetric hydrogenation methods, such as the (R)-cloperastine intermediate. Computational studies illustrate that the BMIDA group is a privileged enantioselectivity-directing group in Noyori–Ikariya ATH compared to the conventionally used aryl and alkynyl groups due to the favorable CH–O attractive electrostatic interaction between the η6-arene-CH of the catalyst and the σ-bonded oxygen atoms in BMIDA. The work expands the domain of conventional ATH and shows its huge potential in addressing challenges in symmetric synthesis.

Brønsted-base-catalyzed diversified annulations between ethylidene 1,3-indenediones and vinyl 1,2-diketones have been achieved, delivering three types of products containing oxabicyclo[3.2.1]octane, spiro[4.5]decane, and branched triquinane skeletons, respectively, which widely exist in natural products and bioactive substances. Two unprecedented reaction modes have been disclosed, and the reactions could be readily scaled up. The protocol shows the potential of 1,2-diketone-mediated reactions in the rapid construction of complicated polycyclic scaffolds.

As well-known, the excessive discharge of heavy-metal mercury not only destroys the ecological environment, bust also leads to severe damage of human health after ingestion via drinking and bioaccumulation of food chains, and mercury ion (Hg2+) is designated as one of most prevalent toxic metal ions in drinking water. Thus, the high-performance monitoring of mercury pollution is necessary. Functional nucleic acids have been widely used as recognition probes in biochemical sensing. In this work, a carbazole derivative, ethyl-4-[3,6-bis(1-methyl-4-vinylpyridium iodine)-9H-carbazol −9-yl)] butanoate (EBCB), has been synthesized and found as a target-lighted DNA fluorescent indicator. As a proof-of-concept, Hg2+detection was carried out based on EBCB and Hg2+-mediated conformation transformation of a designed DNA probe. By comparison with conventional nucleic acid indicators, EBCB held excellent advantages, such as minimal background interference and maximal sensitivity. Outstanding detection capabilities were displayed, especially including simple operation (add-and-read manner), ultrarapidity (30 s), and low detection limit (0.82 nM). Furthermore, based on these advantages, the potential for high-performance screening of mercury antagonists was also demonstrated by the fluorescence change of EBCB. Therefore, we believe that this work is meaningful in pollution monitoring, environment restoration and emergency treatment, and may pave a way to apply EBCB as an ideal signal transducer for development of high-performance sensing strategies.

Because of their important roles in cellular functions, life activities, drug screening, and disease treatment, the development of efficient methods for monitoring protein-ligand interaction is essential. In this study, inspired by our previous studies on DNA conformation-selective fluorescent indicators, we developed a new sensing platform for monitoring protein-ligand interaction and detecting protein activity based on binding-mediated DNA protection and the dsDNA-lighted fluorophore, ethyl-4-[3,6-bis (1-methyl-4-vinylpyridium iodine)-9H-carbazol-9-yl)] butanoate (EBCB). The ligand was purposefully linked to the 3ʹ-terminal of a hairpin DNA probe to selectively bind with the target protein and protect the DNA from cleavage by exonuclease III. By virtue of EBCB’s outstanding capacity to discriminate DNA conformation, the protein-ligand interaction could be effectively monitored through a fluorescence change in EBCB. A high fluorescence signal was detected when the hairpin DNA was protected in the presence of the target protein, whereas a much lower signal was observed in the presence of nontarget proteins. Our results demonstrated that the proposed strategy had high potential, such as high selectivity and relatively high sensitivity, for monitoring protein-ligand interaction and detecting protein activity. We believe these results will pave the way for applying dsDNA-lighted fluorophore EBCB as an effective signal transducer for DNA conformation transformation-mediated biochemical sensing.

Yield stress values of silicon nitride suspensions were measured via a novel slotted plate device and a constant stress rheometer and the results were compared. Test platform velocity, associated with the slotted plate method, was found to have a substantial effect on dynamic yield stress but not on static yield stress. The effects of suspension concentration and temperature on yield stress values were investigated. Yield stress measurements on mixtures of silicon nitride and alumina particles, as well as creep tests were performed.