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An ideal anti-counterfeiting technique has to be inexpensive, mass-producible, nondestructive, unclonable and convenient for authentication. Although many anti-counterfeiting technologies have been developed, very few of them fulfill all the above requirements. Here we report a non-destructive, inkjet-printable, artificial intelligence (AI)-decodable and unclonable security label. The stochastic pinning points at the three-phase contact line of the ink droplets is crucial for the successful inkjet printing of the unclonable security labels. Upon the solvent evaporation, the three-phase contact lines are pinned around the pinning points, where the quantum dots in the ink droplets deposited on, forming physically unclonable flower-like patterns. By utilizing the RGB emission quantum dots, full-color fluorescence security labels can be produced. A convenient and reliable AI-based authentication strategy is developed, allowing for the fast authentication of the covert, unclonable flower-like dot patterns with different sharpness, brightness, rotations, amplifications and the mixture of these parameters. Anti-counterfeiting technologies should ideally be unclonable, yet simple to fabricate and decode. Here, the authors develop an inkjet-printable and unclonable security label based on random patterning of quantum dot inks, and accompany it with an artificial intelligence decoding mechanism capable of authenticating the patterns.

Colloidal quantum dot (QD) emitters show great promise in the development of next-generation displays. Although various solution-processed techniques have been developed for nanomaterials, high-resolution and uniform patterning technology amicable to manufacturing is still missing. Here, we present large-area, high-resolution, full-color QD patterning utilizing a selective electrophoretic deposition (SEPD) technique. This technique utilizes photolithography combined with SEPD to achieve uniform and fast fabrication, low-cost QD patterning in large-area beyond 1,000 pixels-per-inch. The QD patterns only deposited on selective electrodes with precisely controlled thickness in a large range, which could cater for various optoelectronic devices. The adjustable surface morphology, packing density and refractive index of QD films enable higher efficiency compared to conventional solution-processed methods. We further demonstrate the versatility of our approach to integrate various QDs into large-area arrays of full-color emitting pixels and QLEDs with good performance. The results suggest a manufacture-viable technology for commercialization of QD-based displays. Colloidal quantum dots are promising for next-generation displays, yet the technology to realise high-resolution and uniform patterning is still scarce. Here, the authors report full-colour QD large area patterning by combining photolithography and selective electrophoretic deposition technique.

Biofilms are a common survival strategy employed by bacteria in healthcare settings, which enhances their resistance to antimicrobial and biocidal agents making infections difficult to treat. Mechanisms of biofilm-induced antimicrobial resistance involve reduced penetration of antimicrobial agents, increased expression of efflux pumps, altered microbial physiology, and genetic changes in the bacterial population. Factors contributing to the formation of biofilms include nutrient availability, temperature, pH, surface properties, and microbial interactions. Biofilm-associated infections can have serious consequences for patient outcomes, and standard antimicrobial therapies are often ineffective against biofilm-associated bacteria, making diagnosis and treatment challenging. Novel strategies, including antibiotics combination therapies (such as daptomycin and vancomycin, colistin and azithromycin), biofilm-targeted agents (such as small molecules (LP3134, LP3145, LP4010, LP1062) target c-di-GMP), and immunomodulatory therapies (such as the anti-PcrV IgY antibodies which target Type IIIsecretion system), are being developed to combat biofilm-induced antimicrobial resistance. A multifaceted approach to diagnosis, treatment, and prevention is necessary to address this emerging problem in healthcare settings.

Transition metal ions (TMIs) are effective catalysts for atmospheric multiphase reactions that produces secondary air pollutants. The reactivity of TMIs depends on many factors, including metal's solubility and aqueous speciation, which can be complex in the urban air pollution conditions. In this study, we examined the aqueous speciation of Cu(II) within the fine particulate matters (PM 2.5 ) in Beijing air pollution. Using visual MINTEQ model and the Beijing PM 2.5 composition data obtained from previous publications, we predicted the distribution of Cu(II) in the forms of free ions, metal-organic complexes, and metal-inorganic complexes. Such a distribution is affected by pH and PM 2.5 composition with a seasonal variation, which may further arise from the anthropogenic emission patterns. Our finding may provide useful dataset for parameterizing the kinetics of TMI-catalyzed multiphase reactions.

As a typical form of material imperfection, cracks generally cannot be avoided and are critical for load bearing capability and integrity of engineering structures. This paper presents a topology optimization method for generating structural layouts that are insensitive/sensitive as required to initial cracks at specified locations. Based on the linear elastic fracture mechanics model (LEFM), the stress intensity of initial cracks in the structure is analyzed by using singularity finite elements positioned at the crack tip to describe the near-tip stress field. In the topology optimization formulation, the J integral, as a criterion for predicting crack opening under certain loading and boundary conditions, is introduced into the objective function to be minimized or maximized. In this context, the adjoint variable sensitivity analysis scheme is derived, which enables the optimization problem to be solved with a gradient-based algorithm. Numerical examples are given to demonstrate effectiveness of the proposed method on generating structures with desired overall stiffness and fracture strength property. This method provides an applicable framework incorporating linear fracture mechanics criteria into topology optimization for conceptual design of crack insensitive or easily detachable structures for particular applications.

Negative Poisson’s ratio (NPR) metamaterials are attractive for their unique mechanical behaviors and potential applications in deformation control and energy absorption. However, when subjected to significant stretching, NPR metamaterials designed under small strain assumption may experience a rapid degradation in NPR performance. To address this issue, this study aims to design metamaterials maintaining a targeted NPR under large deformation by taking advantage of the geometry nonlinearity mechanism. A representative periodic unit cell is modeled considering geometry nonlinearity, and its topology is designed using a gradient-free method. The unit cell microstructural topologies are described with the material-field series-expansion (MFSE) method. The MFSE method assumes spatial correlation of the material distribution, which greatly reduces the number of required design variables. To conveniently design metamaterials with desired NPR under large deformation, we propose a two-stage gradient-free metamaterial topology optimization method, which fully takes advantage of the dimension reduction benefits of the MFSE method and the Kriging surrogate model technique. Initially, we use homogenization to find a preliminary NPR design under a small deformation assumption. In the second stage, we begin with this preliminary design and minimize deviations in NPR from a targeted value under large deformation. Using this strategy and solution technique, we successfully obtain a group of NPR metamaterials that can sustain different desired NPRs in the range of [−0.8, −0.1] under uniaxial stretching up to 20% strain. Furthermore, typical microstructure designs are fabricated and tested through experiments. The experimental results show good consistency with our numerical results, demonstrating the effectiveness of the present gradient-free NPR metamaterial design strategy.

Assembly ubiquitously occurs in nature and gives birth to numerous functional biomaterials and sophisticated organisms. In this work, chiral hydrogen-bonded organic-inorganic frameworks (HOIFs) are synthesized via biomimicking the self-assembly process from amino acids to proteins. Enjoying the homohelical configurations analogous to α -helix, the HOIFs exhibit remarkable chiroptical activity including the chiral fluorescence ( g lum  = 1.7 × 10 −3 ) that is untouched among the previously reported hydrogen-bonded frameworks. Benefitting from the dynamic feature of hydrogen bonding, HOIFs enable enantio-discrimination of chiral aliphatic substrates with imperceivable steric discrepancy based on fluorescent change. Moreover, the disassembled HOIFs after recognition applications are capable of being facilely regenerated and self-purified via aprotic solvent-induced reassembly, leading to at least three consecutive cycles without losing the enantioselectivity. The underlying mechanism of chirality bias is decoded by the experimental isothermal titration calorimetry together with theoretic simulation. Assembly is an interesting strategy to build chiral hierarchies with premade properties and functionalities. Here, the authors present assembled chiral hydrogen-bonded organic-inorganic frameworks with dynamical chiroptical activities and employ them as powerful and recoverable platforms for enantioselective recognition of chiral aliphatic substrates.

Thorium, as an important radioactive element, is widely present in nature, and its accompanying environmental pollution is also serious. Extracellular polymeric substances (EPS) are commonly found on the surface of microbial bodies and have strong adsorption capacity for metal ions. In this study, four methods were used to extract EPS from indigenous bacteria of rare earth tailings and to determine the best extraction method. The extracted EPS was applied to treat Th4+, and the changes in functional groups and composition of EPS were investigated. The results showed that the ultrasonic method was more efficient than other methods. The best removal efficiency was observed at pH 3.5, Th4+ concentration of 20 mg/L, and EPS dosage of 30 mL at 25 °C. After 9 h, the adsorption process reached equilibrium with a maximum removal efficiency of 75.93% and a maximum theoretical adsorption capacity of 25.96 mg/g. The Th4+ removal process was consistent with the Langmuir and Freundlich adsorption isotherms and the kinetic data were consistent with the pseudo-second-order kinetic model, which is mainly based on chemisorption. Amide I and amide II of proteins, C–H from aliphatic, as well as O–H and C = O from carboxylic acid play important roles in the adsorption process.

Ecosystem stability represents the ability of the ecosystem to maintain and restore its functions. The indicators of ecosystem stability include temporal stability, resistance, and resilience, which are crucial parameters to predict the basic functions of the earth under global change. However, the correlation between the indicators of ecosystem stability and the dimensions of ecosystem stability at global scale remains unclear. Here, we quantified the global dimensions of ecosystem stability using moderate resolution imaging spectrometer (MODIS) enhanced vegetation index (EVI) data from 2001 to 2018 as well as climate variables and land standard species richness data. We revealed a strong positive correlation between temporal stability and resistance and no correlation between resistance and resilience at global scale. The dimension of ecosystem stability changed along the gradients of latitude or altitude. The dimensions of ecosystem stability were different among biomes, showing the lowest in the evergreen broad‐leaved forest (EBF) and the highest in the grassland (GRA). Climate factors were strongly associated with the changes in dimensions of ecosystem stability at global scale. These findings highlight the crucial role of dimensions in exploring ecosystem stability, potentially eliminating contradictions in the ecosystem service mechanism of the earth.

The main curative treatments for hepatocellular carcinoma (HCC) are surgical resection and liver transplantation, which only benefits 15% to 25% of patients. In addition, HCC is highly refractory and resistant to cytotoxic chemotherapy. Although several multi-kinase inhibitors, such as sorafenib, regorafenib, and lenvatinib, have been approved for treating advanced HCC, only a short increase of median overall survival in HCC patients was achieved. Therefore, there is an urgent need to design more effective strategies for advanced HCC patients. Human ribonucleotide reductase is responsible for the conversion of ribonucleoside diphosphate to 2′-deoxyribonucleoside diphosphate to maintain the homeostasis of nucleotide pools. In this study, mining the cancer genomics and proteomics data revealed that ribonucleotide reductase regulatory subunit M2 (RRM2) serves as a prognosis biomarker and a therapeutic target for HCC. The RNA sequencing (RNA-Seq) analysis and public microarray data mining found that RRM2 was a novel molecular target of sorafenib in HCC cells. In vitro experiments validated that sorafenib inhibits RRM2 expression in HCC cells, which is positively associated with the anticancer activity of sorafenib. Although both RRM2 knockdown and sorafenib induced autophagy in HCC cells, restoration of RRM2 expression did not rescue HCC cells from sorafenib-induced autophagy and growth inhibition. However, long-term colony formation assay indicated that RRM2 overexpression partially rescues HCC cells from the cytotoxicity of sorafenib. Therefore, this study identifies that RRM2 is a novel target of sorafenib, partially contributing to its anticancer activity in HCC cells.