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Abstract Quasicrystals are of interest because of their unique nonperiodic structures and physical properties. Motivated by naturally occurring icosahedral AlCuFe- and decagonal AlNiFe-phases hosted in a shocked meteorite, different laboratories have undertaken a series of shock recovery experiments to understand their formation mechanism. Shock experiments generate a complex series of processes and conditions, including a near-instantaneous excursion to high pressure and high temperature, large shear stresses, local melting, rapid decompression, fast quenching and post-shock annealing. This highly dynamic scenario offers a very useful but imperfect tool for exploring the stability of novel alloys, such as quasicrystals. So far, all the shock-synthesized quasicrystals differ considerably in composition from any thermodynamically stable or metastable quasicrystals synthesized by metallurgical techniques at low pressure, leaving plenty of questions to be answered about their formation conditions and their nucleation and growth mechanisms occurring during shock experiments. In this Perspective, we summarize the previous studies of shock-synthesized quasicrystals and discuss the advantages and difficulties caused by the experimental complexity. We also propose a few directions for future experiments to better control the shock conditions and understand the properties of quasicrystals.

Abstract 2-dimensional (2D) piezoelectric materials have gained significant attention due to their potential applications in flexible energy harvesting and storage devices. Recently, niobium oxide dihalides NbOI2 stands out as a multifunctional anisotropic semiconductor family with an exceptionally high lateral piezoelectric constant (~21.8 pm/V), making it a promising candidate for energy conversion applications. Here we report the experimental observation of anisotropic in-plane piezoelectricity in multilayer NbOI2. Current-voltage relationships reveal a significant piezotronic effect in two typical crystalline orientations. Additionally, cyclic tensile and release experiments demonstrate an intrinsic current output of up to 140 pA when subjected to a tensile strain of 0.51%. A flexible piezoelectric nanogenerator prototype is demonstrated on the human finger and wrist, which opens up new avenues for the development of wearable electronic devices and provides valuable insights for further exploration in this field.

Abstract δ-MnO2 is an important component of environmental minerals and is among the strongest sorbents and oxidants. The crystalline morphology of δ-MnO2 is one of the key factors affecting its reactivity. In this work, δ-MnO2 was initially synthesized and placed in an acidic environment to react with Mn2+ and undergo a crystalline transformation. During the transformation of crystalline δ-MnO2, kinetic sampling was conducted, followed by analyses of the structures and morphologies of the samples. The results showed that at pH 2.5 and 4, δ-MnO2 nanoflakes spontaneously self-assembled into nanoribbons via edge-to-edge assembly in the initial stage. Subsequently, these nanoribbons attached to each other to form primary nanorods through a face-to-face assembly along the c-axis. These primary nanorods then assembled along the (001) planes and lateral surfaces, achieving further growth and thickening. Since a lower pH is more favorable for the formation of vacancies in δ-MnO2, δ-MnO2 can rapidly adsorb Mn2+ directly onto the vacancies to form tunnel walls. At the same time, the rapid formation of the tunnel walls leads to a quick establishment of hydrogen bonding between adjacent nanoribbons, enabling the assembly of these nanoribbons into primary nanorods. Therefore, in a solution with the same concentration of Mn2+, the structure transformation and morphology evolution of δ-MnO2 to α-MnO2 occur faster at pH 2.5 than at pH 4. These findings provide insights into the mechanism for crystal growth from layer-based to tunnel-based nanorods and methods for efficient and controlled syntheses of nanomaterials.

Abstract Multi-functional cysteine-targeting covalent warheads possess significant therapeutic potential in medicinal chemistry and chemical biology. Herein, we present novel unsaturated and asymmetric ketone (oxazolinosene) scaffolds that selectively conjugate cysteine residues of peptides and bovine serum albumin under normal physiological conditions. This unsaturated saccharide depletes GSH in NCI-H1299 cells, leading to anti-tumor effects in vitro. The acetyl group of the ketal moiety on the saccharide ring can be converted to other carboxylic acids in a one-pot synthesis. In this way, the loaded acid can be click-released during cysteine conjugation, making the oxazolinosene a potential multifunctional therapeutic agent. The reaction kinetic model for oxazolinosene conjugation to GSH is well established and was used to evaluate oxazolinosene reactivity. The aforementioned oxazolinosenes were stereoselectively synthesized via a one-step reaction of nitriles with saccharides and conveniently converted into a series of α, β-unsaturated ketone N-glycosides as prevalent synthetic building blocks. The reaction mechanisms of oxazolinosene synthesis were investigated through calculations and validated with control experiments. Overall, these oxazolinosenes can be easily synthesized and developed as cysteine-targeted covalent warheads carrying useful click-releasing groups.

Abstract Layered bismuth (Bi) has been focused on two Peierls distortion derivatives, i.e., bulk stable β-phase (A7 phase), black phosphorus-like α-phase (A17 phase), and their mutated structures. Metastable structures beyond Peierls distortion system are yet rarely accessible. Here, Bi in square symmetry ( $${C}_{4v}$$ C 4 v ), called s-Bi, was grown via physical vapor deposition. The co-existence of three 120°-associated s-Bi crystal grains was analyzed using transmission electron microscopy. 120°-oriented one-dimensional (1D) nuclei indicate s-Bi heteroepitaxy on six-fold symmetric ( $${C}_{6v}$$ C 6 v ) mica (001). A subsequent nanorod-like nuclei coalescing could promote a morphology evolution, resulting in triangular or hexagonal nanosheets with the unique triple s-Bi structure suitable for later β-Bi growth. Lattice misfit and strain calculations suggest a supercell match between $$4\times 7$$ 4 × 7 s-Bi and $$3\times 3$$ 3 × 3 mica (001). This work demonstrates the metastable s-Bi structure via anisotropic heteroepitaxy of $${C}_{4v}$$ C 4 v s-Bi on $${C}_{6v}$$ C 6 v mica.

The Tibetan Plateau (TP) plays a key role in the regional environment and global climate change; however, the lack of vertical observations of atmospheric species, such as HONO and O3, hinders a deeper understanding of the atmospheric chemistry and atmospheric oxidation capacity (AOC) on the TP. In this study, we conducted multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements at Nam Co, the central TP, to observe the vertical profiles of aerosol, water vapor (H2O), NO2, HONO and O3 from May to July 2019. In addition to NO2 mainly exhibiting a Gaussian shape with the maximum value appearing at 300=-400 m, the other four species all showed an exponential shape and decreased with the increase in height. The maximum values of monthly averaged aerosol (0.17 km−1) and O3 (66.71 ppb) occurred in May, H2O (3.68 × 1017 molec. cm−3) and HONO (0.13 ppb) appeared in July, and NO2 (0.39 ppb) occurred in June at the 200–400 m layer. H2O, HONO and O3 all exhibited a multi-peak pattern, and aerosol appeared to have a bi-peak pattern for its averaged diurnal variations. The averaged vertical profiles of OH production rates from O3 and HONO all exhibited an exponential shape decreasing with the increase in height, with maximum values of 2.61 and 0.49 ppb h−1 at the bottom layer, respectively. The total OH production rate contributed by HONO and O3 on the TP was obviously larger than that in low-altitude areas. In addition, source analysis was conducted for HONO and O3 at different height layers. The heterogeneous reaction of NO2 on wet surfaces was a significant source of HONO. The maximum values of HONO/NO2 appeared when H2O concentrations were approximately 1.0 × 1017 molec. cm−3 and aerosol concentrations were larger than 0.15 km−1 below 1.0 km. The maximum values were usually accompanied by H2O concentrations of 1.0–2.0 × 1017 molec. cm−3 and aerosol concentrations greater than 0.02 km−1 at 1.0–2.0 km. O3 was potentially sourced from the South Asian subcontinent and Himalayas through long-range transport. Our results contribute to the new understanding of vertical distribution of atmospheric components and explain the strong AOC on the TP.

Fungicides are an indispensable tool in plant disease control. Various modes of action (MOAs) have been identified in different fungicides to suppress plant pathogens. The combined use of fungicides with distinct MOAs has been recommended to prevent the development of pathogen resistance. In studying MOAs, metabolomics has been proven to be a robust and high-throughput method. Because metabolites are unique and distinct depending on the biological activities of an organism, MOAs can be identified and classified by establishing metabolic fingerprinting and metabolic profiles. Similarly, if fungicide resistance is developed in a pathogen, the metabolome will change, which can be identified. In this review, we have discussed the principles and advanced applications of metabolomics in the study of MOAs and resistance mechanisms of fungicides, and the potential of metabolic data in understanding the interaction between fungicides and pathogens. Challenges are also discussed in the application of metabolomics, improvement of the study on the mechanism of fungicides in their functions against pathogens and advancing the development of novel fungicides.

Abundance sensitivity is an important technical index of magnetic mass spectrometer, which describes the extent to which the tailing of intense ion peaks at a mass number in its neighborhood affects the weak ion peaks during isotope ratio measurement. It is particularly important in the measurement of isotope ratios containing low abundance nuclides, such as 234U/238U, 236U/238U, and 230Th/232Th. However, the abundance sensitivity of magnetic mass spectrometer is only of the order of 10−6 without taking additional technical measures. To further improve the abundance sensitivity, the techniques of tandem mass spectrometer, such as magnetic-electric, magnetic-magnetic and magnetic-electric-quadrupole tandem mass spectrometer, and retarding filter can be adopted. In fact, while various tandem mass spectrometer techniques can effectively improve the abundance sensitivity of an instrument, they also significantly increase the size, complexity, and cost of instrument, and therefore are not widely used. In contrast, due to its simple structure, small size, and excellent performance, the retarding filter has become a key component for commercial magnetic mass spectrometers to improve abundance sensitivity. Based on the basic principles of ion optics, a retarding filter consisting of five electrodes with a compact structure of only (40×50×50) mm3 was developed by utilizing the ion optics simulation software SIMION8.1. In addition to the function of energy retarding, the retarding filter also has the function of direction retarding, which greatly enhances the filtering capability to scatter ions. To test the ion transmission efficiency and the abundance sensitivity under different voltages, the retarding filter was installed on a domestic double-focusing thermal ionization mass spectrometer (TIMS). The instrument mainly consists of a thermal ionization source, a double focusing mass analyzer consisting of an electrostatic analyzer and a magnetic mass analyzer, a zoom lens, and a multi-collector detector, which can be configured with up to 16 faraday cups, 4 electron multipliers, and 2 retarding filters. The results showed that the abundance sensitivity of the mass spectrometer is successfully improved from

New psychoactive substances (NPS) have become a global health and social problem. Their structures are variable and can be easily modified to produce new compounds. Traditional analytical techniques mostly rely on standard substances and mass spectrometry databases. The increased structural diversity of NPS makes the mass spectrometry databases be unable to comprehensively cover the mass spectra of all possible NPS, which in turn makes it difficult to perform structural identification of completely unknown compounds. Advances in machine learning have emerged as a potential solution to this dilemma. In this study, the k-nearestneighbor (KNN), support vector machine (SVM), random forests (RF) and artificial neural network (ANN) algorithms were constructed based on a dataset of mass spectra of 871 compounds. The four algorithmic models for identifying new psychoactive substances were used for structural classification prediction. The training and test sets were divided according to the ratio of 7:3, and the fit method was invoked on the training set to construct the model and train the parameters of the model, and the generalization ability of the model was evaluated on the test set. A grid search with 5-fold cross-validation was used to optimize the hyperparameters of the models. The performance of the four classification prediction models was evaluated by using the confusion matrix, accuracy, precision, recall and f-scores for each of the four models for characterizing 261 samples from the test set. Overall, the RF prediction model has the best classification prediction for the seven NPS as well as negative samples, with an overall accuracy of 89.27%, which is higher than the other three classification prediction models. The overall accuracies of the KNN, SVM, and ANN models are 79.31%, 83.14%, and 83.52%, respectively. In addition, the RF prediction model also has high accuracy for the NPS prediction of specific classes, and the accuracies for synthetic cathinones, fentanyl, synthetic cannabinoids, and benzodiazepines are 100%, 93%, 95%, and 100%, respectively, which can warrant good prediction for the structural classes of unknown compounds. In conclusion, this study develops a strategy for rapid analysis of new psychoactive substances using machine learning algorithms based on mass spectral datasets, realizing the classification prediction of structural classes of unknown compounds, thus providing a basis for the structural identification of unknown psychoactive compounds.

High resolution isotope ratio mass spectrometry (HR-IRMS) is often used to measure the abundance of deuterium to verify the efficiency of isotope isolation of a cryogenic distillation column system. In order to achieve precise quantification of hydrogen isotope abundance by HR-IRMS, a fine tuning procedure was performed by using molecular hydrogen to optimize the source parameters, steering parameters and analyzer parameters. The mass resolution can reach 10 000 after tuning, which is high enough to separate all potential hydrogen and helium isotopes except for 3He+ and T+. The test results of peak center stability, peak top flatness, resolution and sensitivity stability showed that the performance of the mass spectrometer can meet the demand for hydrogen isotope analysis. The inlet pressure should be in the range of 4-33 Pa to obtain stable sensitivity, and the accelerating voltage of the ion source should not be less than 8 V because it is negatively correlated with the production rate of trimmers (H3+, D3+, H2D+ and HD2+ etc.). As the accelerating voltage decreasing, the production rate of trimers increases. Another key factor affecting the production rate of trimers is the inlet pressure, the square of which is proportional to the production rate of trimers. Therefore, optimizing the ion source parameters to obtain higher sensitivity is a better way than increasing the sample inlet pressure. On this basis, the equilibrium hydrogen isotope standards which are essential to obtain the sensitivity of each component of hydrogen isotopes were prepared by a self-made standard gas preparation device, and the sensitivity values of each component were corrected by pure gases and the self-prepared standard with verified compositions. The molecular leak rate for the inlet hole was determined by monitoring the pressure for H2 and D2 as a function of time as the gas leaked out, and the leak rate of the other components could be calculated using the leak rate of H2 or D2 because the leak rate is inversely proportional to the square root of the molar mass. Standard mixtures were analyzed to test precision and trueness of this method. The results showed that the measurement precision is better than 1% for samples with natural deuterium abundance and better than 0.5% for samples with medium to high abundance of deuterium. The measured values are in good agreement with the standard values. Compared to the low resolution mass spectrometry, this method is simple and reliable, does not need to resolve the mass overlap peak, and the accuracy of the measurement does not depend on the degree of hydrogen isotope balance in the sample.

Abstract In recent years, significant advancements have been made in molecular generation algorithms aimed at facilitating drug development, and molecular diversity holds paramount importance within the realm of molecular generation. Nonetheless, the effective quantification of molecular diversity remains an elusive challenge, as extant metrics exemplified by Richness and Internal Diversity fall short in concurrently encapsulating the two main aspects of such diversity: quantity and dissimilarity. To address this quandary, we propose Hamiltonian diversity, a novel molecular diversity metric predicated upon the shortest Hamiltonian circuit. This metric embodies both aspects of molecular diversity in principle, and we implement its calculation with high efficiency and accuracy. Furthermore, through empirical experiments we demonstrate the high consistency of Hamiltonian diversity with real-world chemical diversity, and substantiate its effects in promoting diversity of molecular generation algorithms. Our implementation of Hamiltonian diversity in Python is available at: https://github.com/HXYfighter/HamDiv . Scientific contribution We propose a more rational molecular diversity metric for the community of cheminformatics and drug development. This metric can be applied to evaluation of existing molecular generation methods and enhancing drug design algorithms.

A series of emission control measures implemented by the Chinese government have effectively reduced air pollution by multiple pollutants in many regions of the country in recent decades. However, the impacts of these control measures on environmental persistent free radicals (EPFRs) and reactive oxygen species (ROSs), the two groups of chemical species that are known to be linked with adverse human health effects, are still not clear. In this study, we investigated the levels, patterns, and sources of EPFRs and gas- and particle-phase ROSs (referred to as G-ROSs and P-ROSs, respectively) in Beijing during the 2015 China Victory Day Parade period when short-term air quality control measures were imposed. EPFRs in the non-control period (NCP) tended to be radicals centered on a mixture of carbon and oxygen, while those in the control period (CP) were mainly oxygen-centered free radicals. The contribution of G-ROSs to the atmospheric oxidizing capacity increased, and that of P-ROSs decreased during the CP compared to the NCP. The strict control measures reduced ambient EPFRs, G-ROSs, and P-ROSs by 18.3 %, 24.1 %, and 46.9 %, respectively; these amounts were smaller than the decreases in most other measured pollutants. Although particle-matter-based air quality control measures have performed well in achieving “Parade Blue”, it is difficult to simultaneously reduce the negative impacts of the atmosphere on human health. The Parade Blue days were largely attributed to the dramatic reduction in secondary aerosols, which were also largely responsible for EPFR and ROS reductions. Compared to the cases during the NCP, the source-sector-based concentrations of PM2.5, EPFRs, G-ROSs, and P-ROSs during the CP were reduced by 78.7 %–80.8 % when coming from secondary aerosols, by 59.3 %–65.0 % when coming from dust sources, by 65.3 %–67.0 % when coming from industrial emissions, and by 32.6 %–43.8 % when coming from vehicle emissions, while concentrations from other sources increased by 1.61 %–71.5 %. Vehicle emissions and other sources may play complex roles in air quality and public health. This insight will prompt policymakers to reevaluate current air quality management strategies to more effectively address the challenges posed by pollutants such as EPFRs and ROSs.

The cloud condensation nuclei (CCN) activity of black carbon (BC) particles importantly determines their impacts on cloud microphysics and atmospheric lifetime. This process is crucially influenced by the number of hygroscopic coating materials that BC acquire during the ageing process. It remains a challenge for ambient measurements to capture this process and link this with CCN activity of BC. Here, we directly measured the droplet activation diameter (D50) and activation fraction of BC-containing (BCc) particles (Fact,BC) in suburban Beijing using coupled measurements of size-resolved number concentrations of CCN at configured water supersaturation (SS) and BCc particles. The number concentration of BCc particles was found to peak at diameter 180–210 nm after acquiring coatings, larger than that for all particles (50–150 nm). Consequently, the initially smaller BC particles become enlarged and more hygroscopic, thereby exhibiting CCN activities than other particles. The Fact,BC increased from 42 % to 69 % in number and from 67 % to 85 % in mass as SS increased from 0.1 % to 0.2 % but tended to reach a plateau when SS > 0.2 %. Notably, Fact,BC and D50 linearly correlated with equivalent photochemical age, at a rate of +2 % h−1 and −3 nm h−1, respectively. The results suggest BCc particles from anthropogenic sources can readily serve as CCN at a relatively low SS, and more than half of the BC population can be activated within a few hours, indicating that the surface-sourced BC can efficiently incorporate into clouds and potentially exert important indirect radiative impacts.

Abstract Chirality and luminescence are important for both chemistry and biology, which are highly influenced by aggregation. In this work, a pair of metalated tetraphenylethylene(TPE)‐based organic cage enantiomers are reported, which feature a quadrangular prismatic cage structure. These homochiral cages exhibit concentration‐dependent chiral behaviors alongside a propensity for thermodynamic aggregation. Aggregation caused quench effect is found for these cages accompanying the increasing of the concentrations. When a poor solvent is added to produce a kinetical aggregation, the aggregation‐annihilation circular dichroism and aggregation‐induced emission behaviors are observed for these enantiomeric cages. By comparing these observations with the photophysical behaviors of a pair of structurally similar organic molecular enantiomers, the unique photophysical properties observed are intricately linked to the metal‐integrated TPE‐functionalized cage structures.

Kuding tea (KT) is the general name of a set of bitter-tasting herbal tea made from varied original plant species. However, limited information was reported about the difference of bioactive constituents, heavy metals, and bioactivities among those original species. In the present study, comparison analyses among heavy metals, polysaccharides, phenolics, flavonoids, and saponins constituents, as well as the antioxidant and antidiabetic activities were performed through colorimetry, UPLC-QTOF-MS, enzymatic assay and molecular docking techniques on the six KT original plants mainly from the genus Ilex. Results showed that Cd contents in the four KT original plants other than Ilex pubescens (IP) and Ilex cornuta (IC) and heavy metal contents including Pb, Cu, As and Hg in the all six plants were lower than standard limit values. Furthermore, contents of carbohydrate in polysaccharides (470.06 and 548.51 mg GLE/g), total phenolics (33.84 and 48.85 mg GAE/g), flavonoids (30.86 and 109.97 mg RE/g), phenolic acids (49.68 and 61.48 mg CAE/g), flavonols (18.47 and 19.19 mg RE/g), flavanols (0.18 and 0.14 mg CE/g), saponins (90.81 and 97.33 mg GSE /g) in IP and Ligustrum japonicum (LJ), as well as their antioxidant activity levels (IC50 607.41–780.44, and 547.06–754.00 mg/L) were all significantly higher than those in other four KT original plants. Moreover, a total of 6 and 9 compounds were tentatively characterized from IP and LJ, respectively, and molecular docking and molecular dynamics simulation were further used to analysis the interaction between α-glucosidase and bioactive compounds in IP. At last, principal component, hierarchical cluster, and correlation analysis indicated that carbohydrate content of polysaccharides, total phenols, flavonoids and phenolic acids were the main influencing factors to antioxidant abilities. Overall, according to our systematic analysis, IP possessed the highest antioxidant and antidiabetic potentials, thus might be a better KT original plants from the genus Ilex for further development and utilization.

Abstract 2-Hydroxyacyl-CoA lyase/synthase (HACL/S) is a thiamine diphosphate (ThDP)-dependent versatile enzyme originally discovered in the mammalian α-oxidation pathway. HACL/S natively cleaves 2-hydroxyacyl-CoAs and, in its reverse direction, condenses formyl-CoA with aldehydes or ketones. The one-carbon elongation biochemistry based on HACL/S has enabled the use of molecules derived from greenhouse gases as biomanufacturing feedstocks. We investigated several HACL/S family members with high activity in the condensation of formyl-CoA and aldehydes, and distinct chain-length specificities and kinetic parameters. Our analysis revealed the structures of enzymes in complex with acyl-CoA substrates and products, several covalent intermediates, bound ThDP and ADP, as well as the C-terminal active site region. One of these observed states corresponds to the intermediary α–carbanion with hydroxymethyl-CoA covalently attached to ThDP. This research distinguishes HACL/S from related sub-families and identifies key residues involved in substrate binding and catalysis. These findings expand our knowledge of acyloin-condensation biochemistry and offer attractive prospects for biocatalysis using carbon elongation.