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Halide perovskites, particularly zero-dimensional (0D) A2BX6-type structures, have garnered significant attention in diverse fields due to their exceptional photoelectric properties. This study focuses on the optical property regulation of 0D A2ZrCl6through nonprotonated cation substitution (A = [(CH3)3SO]+and [(CH3)4N]+) combined with different guest ions (i.e., Sb3+, Bi3+, and Mn2+). The varied host–guest interaction is regarded as the reason for the different luminescent behaviors. The Sb3+dopant has a weaker interaction with the host [(CH3)3SO]2ZrCl6than Mn2+does. As a result, Sb3+@[(CH3)3SO]2ZrCl6shows an excitation-dependent photoluminescence ranging from blue to orange, while Mn2+@[(CH3)3SO]2ZrCl6exhibits only Mn2+dopant emission under different excitation wavelengths. Besides the dopant effect on the host–guest interaction, the organic cation can impact the host–guest behavior as well. [(CH3)3SO]2ZrCl6and [(CH3)4N]2ZrCl6have different preferences for dopant ions. Sb3+and Mn2+are favorable in the host [(CH3)3SO]2ZrCl6, while Sb3+and Bi3+are adopted in [(CH3)4N]2ZrCl6. Due to the varied emission colors from Sb3+and Bi3+dopants, [(CH3)4N]2ZrCl6possesses diverse photoluminescence behaviors through dopant engineering. Inside [(CH3)4N]2ZrCl6, Sb3+and Bi3+have a weak host–guest interaction, showing a varied PL from the host and guest emission centers under different excitations.

Complicated nano- and atomic-scale processes with sub-angstrom spatial resolution and millisecond time resolution visualized by in situtransmission electron microscopy (TEM) are often highly dynamical and time consuming to analyze and interpret. Here, we report how variational autoencoders (VAEs) can provide an artificial intelligence’s interpretation of high-resolution in situTEM data by condensing and deconvoluting complicated atomic-scale dynamics into a latent space with reduced dimensionality. We designed a VAE model with high latent dimensions capable of deconvoluting information from complex high-resolution TEM data. We demonstrate how this model, with high latent dimensions trained on atomically resolved TEM images of lead sulfide (PbS) nanocrystals, is able to capture movements and perturbations of periodic lattices in both simulated and real in situTEM data. The VAE model shows the capability of detecting and deconvoluting dynamical nanoscale physical processes, such as the rotation of crystal lattices and intra-particle ripening during the annealing of semiconductor nanocrystals.

The safety of traditional Chinese medicine (TCM) has garnered considerable interest worldwide. In this study, a high-throughput method for the determination of 255 pesticide residues in decoctions of Radix Codonopsis and Angelica sinensiswas developed using liquid chromatography-time-of-flight/mass spectrometry. The methodological verification demonstrated the accuracy and reliability of this method. The frequently detected pesticides in Radix Codonopsis and Angelica sinensiswere determined to build a correlation between pesticide properties and the transfer rate of pesticide residues in their decoctions. Water solubility (WS) with a higher correlation coefficient (R) made a significant contribution to the accuracy of the transfer rate prediction model. The regression equations for Radix Codonopsis and Angelica sinensiswere T= 13.64 log WS + 10.56 with a correlation coefficient (R) of 0.8617 and T= 10.66 log WS + 25.48 with a correlation coefficient (R) of 0.8072, respectively. This study provides preliminary data on the potential risk of exposure to pesticide residues in Radix Codonopsis and Angelica sinensisdecoctions. Furthermore, as a case study on root TCM, this approach may serve as a model for other TCMs.

Shear phonons are collective atomic-layer motions in layered materials that carry critical information about mechanical, thermal and optoelectronic properties. Phonon branches with co-directional atomic-layer motions carry unique information about the global structure and hidden interfaces in layered crystals and heterostructures, but they are not detectable due to the very limited electron–phonon coupling. Here we utilize the propagating feature and mechanical coupling between shear phonons and localized plasmonic cavities to successfully realize direct characterization of ground-state shear phonons down to 4 cm−1in energy by introducing mechano-Raman spectroscopy (MRS). MRS has the ability to characterize the global crystal structure with more than 108-fold enhancement and to accurately measure subpicometre displacements under ambient conditions with a thermal-noise-free feature. The propagating behaviour and the capacity of MRS to detect optically hidden interfaces are demonstrated. The broad tunability of plasmons makes the MRS technique a robust tool for extensive applications, including global crystal flaw detection, mechanical sensing and the mechanical modulation of light.

The manufacturing industry involves innumerable complex tasks that require significant knowledge and experience to execute. With the rapid development of artificial intelligence, particularly with the emergence of powerful large language models such as ChatGPT, new opportunities have risen to provide knowledge through conversation. With its seemingly endless knowledge base and highly organized response style, ChatGPT is expected to revolutionize every aspect of the industry. However, the extent of ChatGPT's capabilities and how they could contribute to the industry's future revolution remains unclear. In light of this, this paper performed a systematic testing of ChatGPT to uncover its advantages and limitations. Based on the testing results, the authors provided some prospects and critical research questions of ChatGPT from a manufacturing perspective. Furthermore, the authors recommended a technology development roadmap to successfully integrate ChatGPT into the manufacturing industry.

Cross-modal hashing, favored for its effectiveness and efficiency, has received wide attention to facilitating efficient retrieval across different modalities. Nevertheless, most existing methods do not sufficiently exploit the discriminative power of semantic information when learning the hash codes while often involving time-consuming training procedure for handling the large-scale dataset. To tackle these issues, we formulate the learning of similarity-preserving hash codes in terms of orthogonally rotating the semantic data, so as to minimize the quantization loss of mapping such data to hamming space and propose an efficient fast discriminative discrete hashing (FDDH) approach for large-scale cross-modal retrieval. More specifically, FDDH introduces an orthogonal basis to regress the targeted hash codes of training examples to their corresponding semantic labels and utilizes the $\varepsilon $ -dragging technique to provide provable large semantic margins. Accordingly, the discriminative power of semantic information can be explicitly captured and maximized. Moreover, an orthogonal transformation scheme is further proposed to map the nonlinear embedding data into the semantic subspace, which can well guarantee the semantic consistency between the data feature and its semantic representation. Consequently, an efficient closed-form solution is derived for discriminative hash code learning, which is very computationally efficient. In addition, an effective and stable online learning strategy is presented for optimizing modality-specific projection functions, featuring adaptivity to different training sizes and streaming data. The proposed FDDH approach theoretically approximates the bi-Lipschitz continuity, runs sufficiently fast, and also significantly improves the retrieval performance over the state-of-the-art methods. The source code is released at https://github.com/starxliu/FDDH.

La alergia es una reacción de hipersensibilidad activada por mecanismos inmunitarios específicos mediados por células o anticuerpos. Las alergias han aumentado en los países industrializados durante las últimas décadas. El aumento de las enfermedades respiratorias alérgicas, como la rinitis alérgica (RA) y el asma alérgica (AA), es una amenaza potencial para la salud pública. Se realizaron búsquedas en PubMed, Google Scholar y Medline utilizando los siguientes términos clave: allergic rhinitis OR asthma AND probiotics, allergic airway inflammation AND immune disorders, probiotics OR gut microbiota AND allergic disease, probiotics AND inflammatory. Se incluyeron estudios de todos los años, específicamente aquellos publicados en los últimos diez años. Se buscó en algunos artículos de revisión y en su lista de referencias para identificar artículos relacionados. El papel de la microbiota en las enfermedades alérgicas respiratorias ha atraído cada vez más atención. Algunas pruebas sugieren que el desarrollo de las enfermedades alérgicas provoca un desequilibrio en la composición de la microbiota intestinal. En comparación con ratones colonizados, los ratones sin gérmenes presentan respuestas alérgicas exageradas en las vías respiratorias, lo que indica que las interacciones microbianas con el huésped tienen un papel importante en el desarrollo de las enfermedades alérgicas. Los probióticos modulan tanto la respuesta inmune innata como la adaptativa, y a menudo se emplean como suplementos dietéticos que aportan beneficios a la salud en los trastornos gastrointestinales. Los probióticos pueden actuar como inmunomoduladores y activadores de las vías de defensa del huésped. Asimismo, los probióticos orales pueden modular la respuesta inmune en el sistema respiratorio. Estudios recientes en humanos y animales han demostrado el papel de los probióticos en la RA y la AA. Para entender la caracterización de la microbiota y el efecto potencial de los probióticos en la AA/AR, esta revisión ofrece un panorama de las características clínicas de la AA y la RA y del uso de probióticos para la prevención y el tratamiento de la RA, los cambios en la microbiota intestinal y sus mecanismos de acción.

Enhancing the quality of junctions is crucial for optimizing carrier extraction and suppressing recombination in semiconductor devices. In recent years, metal halide perovskite has emerged as the most promising next-generation material for optoelectronic devices. However, the construction of high-quality perovskite junctions, as well as characterization and understanding of their carrier polarity and density, remains a challenge. In this study, using combined electrical and spectroscopic characterization techniques, we investigate the doping characteristics of perovskite films by remote molecules, which is corroborated by our theoretical simulations indicating Schottky defects consisting of double ions as effective charge dopants. Through a post-treatment process involving a combination of biammonium and monoammonium molecules, we create a surface layer of n-type low-dimensional perovskite. This surface layer forms a heterojunction with the underlying 3D perovskite film, resulting in a favorable doping profile that enhances carrier extraction. The fabricated device exhibits an outstanding open-circuit voltage (VOC) up to 1.34 V and achieves a certified efficiency of 19.31% for single-junction wide-bandgap (1.77 eV) perovskite solar cells, together with significantly enhanced operational stability, thanks to the improved separation of carriers. Furthermore, we demonstrate the potential of this wide-bandgap device by achieving a certified efficiency of 27.04% and a VOCof 2.12 V in a perovskite/perovskite tandem solar cell configuration.Effective electrical doping of perovskite caused by remote molecular dopants are precisely characterized and clarified, based on which a 3D-2D heterojunction structure is fabricated to achieve a high efficiency wide bandgap perovskite solar cell, and an all perovskite tandem solar cell with efficiency over 27%.

A breakthrough has been recently made in the hydrocarbon exploration of the Permian pyroclastic rocks in the Jianyang Area, western Sichuan Basin, China. With an aim to decipher the impacts of the eruption environment, the temperature of hydrothermal fluids, and the paleo-salinity on the formation of authigenic mineral assemblage and pores, this study implements comprehensive petrographic and geochemical studies through the integrated core and thin section analyses. The data presented demonstrate that the Permian volcanic intervals are intensively affected by an event of Emei taphrogeny. During basaltic magma upward migration, fractional crystallization of anorthose results in slightly-alkaline magma. The specific pyroclastic rocks are formed by the eruption of slightly-alkaline magma in the sea or a salt lake and subsequent hydrothermal alteration. During deposition and diagenesis, the authigenic mineral association is constrained jointly by the sodium-rich and high salinity water environment, and mid-high temperature, high-salinity hydrothermal fluid. Specifically, the sodium-rich hydrothermal fluid, which may sustain till the late diagenesis stage, caused pervasive albitization of pyroclastic rocks, then leading to mineral transformation and formation of a series of mineral associations. Therefore, zeolitization of volcanic glass and vesicle-infillings of zeolite is an essential condition for later mineral transformation and dissolution. Albitization of analcite, recrystallization induced by deep hydrothermal fluids, and both meteoric and deep burial dissolution expanding the micro-pore space ultimately formed porous pyroclastic reservoirs.

Increasing access to undergraduate research is critical in efforts to retain students pursuing careers in STEM. Alternatives to traditional research positions, such as course based undergraduate research experiences (CUREs), have played important roles in engaging more undergraduates in research. However, these opportunities are only a subset of possible nontraditional research experiences which can enrich the undergraduate experience. In this study, we critically examined and improved the research-group-led undergraduate research program (GURP) to better meet the needs of undergraduates seeking research. Specifically, we investigated if the program was successful with a greater diversity of data sets, if assessments of learning were consistent across different data sets and teaching environments, and if the program promoted student engagement in research. We have found that this model is scalable, robust, and adaptable to different implementations while producing consistent and positive learning outcomes for students. Especially remarkable are students’ increased self-identification as scientists and statistically significant gains in self-perceived competency across multiple domains of knowledge. This program model has shown promising results as a partially and fully online research experience for undergraduates and has benefited program alumni in their research careers. To assist research groups starting similar programs, we have created public data sets and instructional resources. We believe that GURP programs can work in a variety of situations and hope that they can become a tool to increase interest and build communities for young researchers.

Product usage context (PUC) identification is an effective approach to approximate the complex driver behind heterogeneous customer preference. With the sweeping trend of data-driven smart customization, a large volume of product usage data has allowed designers to understand contextual customer needs (CNs) and enable them to offer highly customized products and services in time. However, as the PUC ontology is not clearly defined, most of the existing PUC models are incomplete, ambiguous and imprecise. Inappropriate use of those models will result in failing to extract knowledge from data. In this paper, an ontology-based context modeling method is proposed, with the aim to help designers understand PUC in a comprehensive manner. A case study of robot vacuum cleaner (RVC) is used as an illustrative example. It is concluded that the proposed method can enable designers quickly establish a well-defined PUC model to support smart customization.

Colloidal superlattices are fascinating materials made of ordered nanocrystals, yet they are rarely called “atomically precise”. That is unsurprising, given how challenging it is to quantify the degree of structural order in these materials. However, once that order crosses a certain threshold, the constructive interference of X-rays diffracted by the nanocrystals dominates the diffraction pattern, offering a wealth of structural information. By treating nanocrystals as scattering sources forming a self-probing interferometer, we developed a multilayer diffraction method that enabled the accurate determination of the nanocrystal size, interparticle spacing, and their fluctuations for samples of self-assembled CsPbBr3and PbS nanomaterials. The multilayer diffraction method requires only a laboratory-grade diffractometer and an open-source fitting algorithm for data analysis. The average nanocrystal displacement of 0.33 to 1.43 Å in the studied superlattices provides a figure of merit for their structural perfection and approaches the atomic displacement parameters found in traditional crystals.

With the extended petroleum exploration of the carbonate reservoir in the Longwangmiao Formation, Lower Cambrian in Sichuan basin, looking for a new favorable exploration area is the primary task in current exploration. This paper focusing on the dolomite reservoir in the Longwangmiao Formation in the Northern Sichuan basin, will evaluate the reservoir conditions, including reservoir lithology, reservoir spaces, physical properties and other basic characteristics. Combined with sedimentary environment study and diagenesis analysis, the genetic mechanism of Longwangmiao reservoir in study area will be discussed. It indicates that the reservoir rocks of Longwangmiao Formation in the study area are composed of dolarenite and crystalline dolomite, and the main reservoir spaces are intergranular dissolved pores, intragranular dissolved pores and intercrystalline dissolved pores. However, most of dissolved pores have been filled with bitumen, which lead to the reservoir properties very poor, both the porosity and permeability are worse than that of central Sichuan basin, so the reservoir in the Longwangmiao Formation in the Northern Sichuan basin is low-porosity and low-permeability reservoir. During the Early Cambrian Longwangmiao period, the study was near the old-land, and the energy of sea water was not enough to deposit many grain shoals, which cause the sediments are small with lots of quartz and muds. Moreover, because lacking of large scale karstification in the late diagenesis, there isn't much dissolved pores and vugs develop in the Longwangmiao Formation. Some Intergranular dissolved pores and intercrystalline dissolved pores formed by the early atmosphere water dissolved exist as some reservoir spaces, but most of them have been filled with bitumen, which was residual when the ancient oil reservoir transformed. Above factors cause the Longwangmiao Formation in the Northern Sichuan basin become not a very favorable reservoir in Sichuan basin.

In contrast to research on active sites in nanomaterials, lithium tantalate single crystals, known for their exceptional optical properties and long-range ordered lattice structure, present a promising avenue for in-depth exploration of photocatalytic reaction systems with fewer constraints imposed by surface chemistry. Typically, the isotropy of a specific facet provides a perfect support for studying heteroatom doping. Herein, this work delves into the intrinsic catalytic sites for photocatalytic nitrogen fixation in iron-doped lithium tantalate single crystals. The presence of iron not only modifies the electronic structure of lithium tantalate, improving its light absorption capacity, but also functions as an active site for the nitrogen adsorption and activation. The photocatalytic ammonia production rate of the iron-doped lithium tantalate in pure water is maximum 26.95 μg cm−2h−1, which is three times higher than that of undoped lithium tantalate. The combination of first-principles simulations with in situ characterizations confirms that iron doping promotes the rate-determining step and changes the pathway of hydrogenation to associative alternating. This study provides a new perspective on in-depth investigation of intrinsic catalytic active sites in photocatalysis and other catalytic processes.

Recently, two-dimensional magnetic materials (2DMMs) have become a focused research direction in a broad range of two-dimensional materials, due to their underlying significance in fundamental research, as well as in technologically relevant applications for future spintronics, magnonics, quantum information and data storage. The rich toolbox of 2DMMs and their diverse tunability have enabled the unprecedented research concerning the two-dimensional magnetic order down to single atomic layer of materials, much beyond the classical thin film magnetism, showing an extremely promising avenue towards electronics, magneto-optics and photonics. Among various degrees of freedoms, the interaction between spin and phonon (i.e., quanta of lattice vibration), hence the so-called spin-phonon coupling, serves as an important tuning knob to explore the two-dimensional magnetism, creates new types of quasiparticles and controls the magnetic order. This review overviews the latest developments in spin-phonon coupling investigations in 2DMMs. Various techniques utilizing spin-phonon coupling to investigate two-dimensional magnetism are discussed. Recent progress in tuning two-dimensional magnetic order based on spin-phonon coupling is also summarized, with a focus to understand the new functionalities. Furthermore, device developments and concepts based on spin-phonon coupling are briefly discussed. This review will provide our perspectives on the existing challenges and future directions in spin-phonon coupling research in 2DMMs and their functional devices.

The synthesis quality of artificial inorganic nanocrystals is most often assessed by transmission electron microscopy (TEM) for which high-throughput advances have dramatically increased both the quantity and information richness of metal nanoparticle (mNP) characterization. Existing automated data analysis algorithms of TEM mNP images generally adopt a supervised approach, requiring a significant effort in human preparation of labeled data that reduces objectivity, efficiency, and generalizability. We have developed an unsupervised algorithm AutoDetect-mNP for automated analysis of TEM images that objectively extracts morphological information on convex mNPs from TEM images based on their shape attributes, requiring little to no human input in the process. The performance of AutoDetect-mNP is tested on two data sets of bright field TEM images of Au nanoparticles with different shapes and further extended to palladium nanocubes and cadmium selenide quantum dots, demonstrating that the algorithm is quantitatively reliable and can thus serve as a generalizable measure of the morphology distributions of any mNP synthesis. The AutoDetect-mNP algorithm will aid in future developments of high-throughput characterization of mNPs and the future advent of time-resolved TEM studies that can investigate reaction mechanisms of mNP synthesis and reactivity.

Based on stratigraphic variations of petrology, geochemistry (major, trace elements), and pyrite framboids, we study the sedimentary environment of siliceous rocks of the Wufeng Formation in Wuxi, Northeastern Chongqing, China. Coupled Al2O3/(Al2O3+Fe2O3), SiO2/Al2O3, with Al–Fe–Mn values indicate that Wufeng Formation are deposited in a continental margin and influenced by detrital input. UEF-MoEFand V/Cr–U/Th cross-plots suggest that the siliceous shale was formed in dysoxic to anoxic conditions. Redox proxies imply that the lower, the middle to upper, and the top part of the Wufeng sediments were deposited in an anoxic, dysoxic and oxic environment, respectively. Accordingly, the average size of pyrite framboids are gradually increased from bottom to top, showing that increased oxidisability. A complete vibratory third-order cycle of sea level fluctuations during the Wufeng deposition can be identified. During Wufeng to Longmaxi transition, the sedimentary environment exhibits a short-scale oscillatory pattern and was probably transformed from an outer shelf to inner shelf. Coupled multi-proxies are considered more reliable proxies for deciphering redox conditions in fine-grained sediment.

Antiferromagnets are promising components for spintronics due to their terahertz resonance, multilevel states and absence of stray fields. However, the zero net magnetic moment of antiferromagnets makes the detection of the antiferromagnetic order and the investigation of fundamental spin properties notoriously difficult. Here, we report an optical detection of Néel vector orientation through an ultra-sharp photoluminescence in the van der Waals antiferromagnet NiPS3from bulk to atomically thin flakes. The strong correlation between spin flipping and electric dipole oscillator results in a linear polarization of the sharp emission, which aligns perpendicular to the spin orientation in the crystal. By applying an in-plane magnetic field, we achieve manipulation of the photoluminescence polarization. This correlation between emitted photons and spins in layered magnets provides routes for investigating magneto-optics in two-dimensional materials, and hence opens a path for developing opto-spintronic devices and antiferromagnet-based quantum information technologies.

Advances in automation and data analytics can aid exploration of the complex chemistry of nanoparticles. Lead halide perovskite colloidal nanocrystals provide an interesting proving ground: there are reports of many different phases and transformations, which has made it hard to form a coherent conceptual framework for their controlled formation through traditional methods. In this work, we systematically explore the portion of Cs–Pb–Br synthesis space in which many optically distinguishable species are formed using high-throughput robotic synthesis to understand their formation reactions. We deploy an automated method that allows us to determine the relative amount of absorbance that can be attributed to each species in order to create maps of the synthetic space. These in turn facilitate improved understanding of the interplay between kinetic and thermodynamic factors that underlie which combination of species are likely to be prevalent under a given set of conditions. Based on these maps, we test potential transformation routes between perovskite nanocrystals of different shapes and phases. We find that shape is determined kinetically, but many reactions between different phases show equilibrium behavior. We demonstrate a dynamic equilibrium between complexes, monolayers, and nanocrystals of lead bromide, with substantial impact on the reaction outcomes. This allows us to construct a chemical reaction network that qualitatively explains our results as well as previous reports and can serve as a guide for those seeking to prepare a particular composition and shape.

The Sinian Dengying Formation in the Sichuan basin is an important potential reservoir for oil and gas exploration in the periphery of the Sichuan basin. Its reservoirs were well developed. And many kinds of fillings which lead to the decrease of pores can be seen in reservoir pores and caves. In this paper, the pore fillings of the Dengying Formation reservoir in Sichuan basin are the object of study. The types and characteristics of the fillings are studied in detail by means of rock slices analysis, cathode luminescence, trace elements and inclusion temperature measurement. The study shows that the fillings include dolomite fillings and siliceous quartz fillings and bitumen fillings. Among them, dolomite fillings can be divided into botryoidal dolomite fillings, foliated dolomite fillings, finely-medium crystalline dolomite fillings and coarse crystalline dolomite fillings. 50%–80% of the pores are filled by the dolomite fillings with botryoidal structure, and the pores can be partially full filled; 0%–20% of pores are filled by foliated dolomite fillings; 20–80% of the pores are filled by finely-medium dolomite fillings; 20–80% of the pores are filled by coarse crystalline dolomite fillings. 1%–5% of secondary pores are often filled by siliceous quartzs, and the pores can be partially full filled. Bitumen fillings often occur after the above-mentioned fillings, and the residual pores are often semi-filled by bitumens, which makes the original pores and throat smaller and reduces the effective porosity and permeability of the reservoir. So, it is a destructive diagenesis. The pore fillings make the secondary porosity in the reservoir significantly lower, which is not conducive to the formation and preservation of the Dengying Formation reservoir.

Design constraints play a critical role in product development. Management of constraints significantly affect achievements of functions. Conventionally, constraints analysis is driven by designers’ knowledge, cognition and experience. Besides, constraints analysis is an iterative work with high cost, time and efforts. As an emerging technology, digital twin enhances the information processing with its synchronization, high-quality model and real-time data exchange. Therefore, digital twin is expected to enhance the conventional constraints analysis. This report is written to envision the digital-twin driven analysis of design constraints. The envision will focus on constraints identification, boundaries detection and importance analytics. A case study of robot vacuum cleaner is used as an illustrative example. It is concluded that DT improves the overall reliability of constraints analysis while reducing human efforts into iterative work.

Customer reviews (CR) is an emerging source to obtain customer requirements about product features. Due to customers’ different preferences, identification of shared interests become important to maximize the overall satisfaction among the target group. This paper aims to provide a feature-based importance rating framework to extract, classify and analyze product features based on online CR data. The framework integrates multiple machine learning and artificial intelligence techniques, which enable CR data to be analyzed in large scale. Besides, social network analysis functions to rate the demand intensity and centrality of product features. An experimental case is conducted to showcase the applicability of the proposed framework.

For the automotive industry, promoting more value-adding services in usage stage is a long-standing challenge for global manufacturers. As many cars have an unknown history, it is proven difficult, if not impossible, to prevent scams and frauds when offering car services. As an emerging technology, blockchain is characterized by high immutability, transparency, security, and traceability. Such characteristics make blockchain a highly promising empowering technology to maintain mutual trust among stakeholders in vehicle product-service system (PSS). This paper presents a blockchain-based PSS framework, which is intended to address the trust issue vehicle PSS.

Supply chain planning is an essential element of global manufacturing. In the interest of reliability, efficiency, and productivity, global manufacturers call for a more digital, analytical, and responsive approach of supply chain planning. As an emerging technology, digital twin achieves deep synchronization and dynamic interaction between the physical and virtual worlds. This paper envisions new supply chain planning based on the theoretical foundations and enabling technologies of digital twin. The paper will elaborate the benefits and potentials of DT, in comparison with the existing planning approaches, in terms of demand forecast, aggregate planning and inventory planning.

Hydrogels are attracting increasing attention due to their potential use in various fields. However, most of the existing hydrogels have limitations in either dissipating mechanical energy or maintaining high stretchability under deformation, thus do not possess high mechanical properties. Herein, poly(vinyl alcohol) (PVA)–tannic acid (TA) hydrogels with both high mechanical strength and stretchability were obtained via a step-by-step physical cross-linking and molecular alignment method. Saline-triggered physical interactions serve as “sacrifice domains” to dissipate energy and endow PVA-based hydrogel with high mechanical strength (≈16 MPa) and stretchability (≈1000%). Due to the reversible arranging and disassociating property of physical interactions, PVA–TA hydrogels show excellent shape memory performance. We further demonstrated an effective approach to fabricate strong and aligned PVA–TA thread. The resultant well-aligned PVA–TA dry thread reveals an ultrahigh mechanical tensile strength of up to 750 MPa, nearly 45 times higher than PVA–TA thread with no alignment. Wide-angle X-ray two-dimensional diffraction images further confirmed the alignment of PVA fibers in stretching direction. In addition, we applied the PVA–TA hydrogel as suture and evaluated the cytotoxicity and biocompatibility of the PVA–TA suture.

Electron–phonon coupling in two-dimensional nanomaterials plays a fundamental role in determining their physical properties. Such interplay is particularly intriguing in semiconducting black phosphorus (BP) due to the highly anisotropic nature of its electronic structure and phonon dispersions. Here we report the direct observation of symmetry-dependent electron–phonon coupling in BP by performing the polarization-selective resonance Raman measurement in the visible and ultraviolet regimes, focusing on the out-of-plane Ag1and in-plane Ag2phonon modes. Their intrinsic resonance Raman excitation profiles (REPs) were extracted and quantitatively compared. The in-plane Ag2mode exhibits remarkably strong resonance enhancement across the excitation wavelengths when the excitation polarization is parallel to the armchair (Ag2//AC) direction. In contrast, a dramatically weak resonance effect was observed for the same mode with the polarization parallel to zigzag (Ag2//ZZ) direction and for the out-of-plane Ag1mode (Ag1//AC and Ag1//ZZ). Analysis on quantum perturbation theory and first-principles calculations on the anisotropic electron distributions in BP demonstrated that electron–phonon coupling considering the symmetry of the involved excited states and phonon vibration patterns is responsible for this phenomenon. Further analysis of the polarization-dependent REPs for Agphonons allows us to resolve the existing controversies on the physical origin of Raman anomaly in BP and its dependence on excitation energy, sample thickness, phonon modes, and crystalline orientation. Our study gives deep insights into the underlying interplay between electrons and phonons in BP and paves the way for manipulating the electron–phonon coupling in anisotropic nanomaterials for future device applications.

Control and manipulation of single charges and their internal degrees of freedom, such as spin, may enable applications in quantum information technology, spintronics and quantum sensing1,2. Recently, atomically thin semiconductors with a direct bandgap such as group VI-B transition-metal dichalcogenide monolayers have emerged as a platform for valleytronics—the study of the valley degree of freedom of charge carriers to store and control information. They offer optical, magnetic and electrical control of the valley index, which, with the spin, is locked into a robust spin-valley index3,4. However, because recombination lifetimes of photogenerated excitations in transition-metal dichalcogenides are of the order of a few picoseconds, optically generated valley excitons possess similar lifetimes. On the other hand, the valley polarization of free holes has a lifetime of microseconds5–9. Whereas progress has been made in optical control of the valley index in ensembles of charge carriers10–12, valley control of individual charges, which is crucial for valleytronics, remains unexplored. Here we provide unambiguous evidence for localized holes with a net spin in optically active WSe2quantum dots13–17and we initialize their spin-valley state with the helicity of the excitation laser under small magnetic fields. Under such conditions, we estimate a lower bound of the valley lifetime of a single charge in a quantum dot from the recombination time to be of the order of nanoseconds. Remarkably, neutral quantum dots do not exhibit such spin-valley initialization, which illustrates the role of the excess charge in prolonging the valley lifetime. Our work extends the field of two-dimensional valleytronics to the level of single spin- valleys, with implications for quantum information and sensing applications.

Quantum entanglement is a fundamental phenomenon that, on the one hand, reveals deep connections between quantum mechanics, gravity and spacetime1,2, and on the other hand, has practical applications as a key resource in quantum information processing3. Although it is routinely achieved in photon–atom ensembles4, entanglement involving solid-state5–7or macroscopic objects8remains challenging albeit promising for both fundamental physics and technological applications. Here, we report entanglement between collective, chiral vibrations in a two-dimensional WSe2host—chiral phonons (CPs)—and single-photons emitted from quantum dots9–13(QDs) present in it. CPs that carry angular momentum were recently observed in WSe2and are a distinguishing feature of the underlying honeycomb lattice14,15. The entanglement results from a ‘which-way’ scattering process, involving an optical excitation in a QD and doubly-degenerate CPs, which takes place via two indistinguishable paths. Our unveiling of entanglement involving a macroscopic, collective excitation together with strong interactions between CPs and QDs in two-dimensional materials opens up ways for phonon-driven entanglement of QDs and engineering chiral or non-reciprocal interactions at the single-photon level.

Phase control plays an important role in the precise synthesis of inorganic materials, as the phase structure has a profound influence on properties such as conductivity and chemical stability. Phase-controlled preparation has been challenging for the metallic-phase group-VI transition metal dichalcogenides (the transition metals are Mo and W, and the chalcogens are S, Se and Te), which show better performance in electrocatalysis than their semiconducting counterparts. Here, we report the large-scale preparation of micrometre-sized metallic-phase 1T′-MoX2(X = S, Se)-layered bulk crystals in high purity. We reveal that 1T′-MoS2crystals feature a distorted octahedral coordination structure and are convertible to 2H-MoS2following thermal annealing or laser irradiation. Electrochemical measurements show that the basal plane of 1T′-MoS2is much more active than that of 2H-MoS2for the electrocatalytic hydrogen evolution reaction in an acidic medium.