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We present a novel, to the best of our knowledge, magneto-optical (MO) metasurface composed of a bismuth iron garnet (BIG) nanocube array, designed to achieve near-perfect absorption through quasi-bound states in the continuum (QBICs). This metasurface supports a stable QBIC mode induced by MO-induced permittivity terms that break the symmetry of the permittivity tensors, corresponding to a longitudinal electric dipole (ED) mode. By integrating graphene to introduce material loss, the absorption reaches 99.6% at a wavelength of 1512.3 nm with a Q factor of 9440, despite monolayer graphene's inherent absorption being only 2.3%. The inherent transverse ED background mode, with high reflection and low Q, helps decrease the radiative loss of the QBIC mode, allowing the structure to surpass the 50% absorption limit. This approach offers a simplified pathway for designing high-Q metasurface perfect absorbers, with potential applications in optical switches and modulators.
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The biogeochemical cycling of phosphorus (P) in river-lake systems presents significant challenges in tracing P sources, highlighting the importance of effective traceability approaches for formulating targeted management measures to mitigate lake eutrophication. In this study, we used the oxygen isotope of phosphate (δ18Op) as a tracer in the river-lake systems, establishing a tracing pathway from potential end-members, through inflow rivers, and eventually to the lake. Taking Dianshan Lake and its main inflow rivers as the study area, we measured δ18Op values of potential end-members, including domestic sewage treatment plant effluents, industrial effluents from phosphorus-related enterprises (printing and dyeing, electroplating, plastics, etc.), and farmland soils. Notably, the industrial effluent signatures ranged from 13.1 to 21.0 with an average of 16.8 ± 3.2 , enriching the δ18Op threshold database. Using the MixSIAR model, it was found that phosphorus in the Jishuigang River primarily originated from agricultural non-point sources and domestic sewage in the dry season, while the Qiandengpu River, with a higher proportion of urban area, had a greater influence from domestic sewage and industrial effluents. Moreover, significant differences were observed between δ18Op values at the lake entrances of the inflow rivers (13.7 ± 1.0 ) and in acid-soluble phosphate of the lake sediments (9.9 ± 1.0 ). Isotopic tracing revealed that phosphorus in the lake originated from both external inputs (80.6 %) and internal release (19.4 %) in the dry season. Alongside pollutant flux calculations based on the hydrological conditions and water quality of the inflow rivers, our findings indicated that phosphorus in Dianshan Lake was mainly attributed to agricultural non-point sources, domestic sewage and sediment release in the dry season. This study provided novel insights into the identification of pollution sources in the river-lake systems, with broad implications for pollution control and environmental protection.
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All-dielectric metasurface perfect absorbers (MPAs) based on quasibound states in the continuum (QBICs) play a crucial role in optical and photonic devices as they can excite high-Q resonances. These structures require adding back reflectors or placing at least two asymmetric elements in each unit to break the absorption limit of 50%, which will increase the design complexity. In this work, we propose a high-Q monolayer MPA (MMPA) composed of a tilted Si nanocube array. By tuning the tilted angle of the nanocube, dual-QBIC modes at two different wavelengths are excited, which corresponds to magnetic quadrupole (MQ) and toroidal dipole (TD) modes, respectively. The high-reflection but low-Q magnetic dipole (MD) background mode excited by such a dual-band structure can decrease the radiative loss of transmission of MQ and TD modes, enabling the structure to break the absorption limit of 50%. The maximum absorption achieves 94% simultaneously at the wavelength of 933 and 961 nm, with the Q factors of 759 and 986, respectively. Our work provides a simple paradigm for designing dual-band high-Q MMPAs, which would greatly expand their range of applications, such as multiplexed optical nanodevices.
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All-dielectric high-Q metasurface absorbers based on quasi-bound states in the continuum (QBICs) are essential for optical and photonic devices. However, achieving perfect absorption requires adding back reflectors at the bottom or placing at least four asymmetric elements in each unit of monolayer metasurfaces, which will increase the design complexity. This work proposes a honeycomb structure with units periodically arranged as a hexagonal lattice. Each unit cell is made of two nanopost elements. By only tuning the radius difference of two elements to break the in-plane symmetry, two orthogonal QBIC modes corresponding to toroidal dipole (TD) and electric dipole (ED) modes are excited, respectively. The maximum absorption reaches 92.3% at 955â nm with a Q factor of 1501, breaking the monolayer limit of 50% by the degenerate critical coupling. Our work may provide a promising route for designing high-Q all-dielectric metasurface absorbers applied in ultrafast optoelectronic devices.
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The wave propagating through the temporal boundary has attracted considerable attention in the past few years because of the potential applications of time-varying systems in the optics community. However, temporal diffraction of light remains to be investigated, because free space is non-dispersive. Here, we theoretically provide the analytical expressions for the temporal diffraction contributions of electron waves across the temporal boundary between the free space and a dispersive medium. With the help of coupled waveguide arrays, temporal diffraction is analogously observed by the optical platform. The optical analogy results confirm the theoretical predictions of the temporal diffraction wave at the temporal boundary. By changing the permittivity of the waveguides, implying the coupling coefficient is modified, the temporal diffraction angle is tuned. Our analysis and observations of temporal diffraction of dispersive media have great potential in time-varying physics, signal processing, and photonics communications.
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BACKGROUND: To investigate the pain and self-management status of patients with cancer and the influencing factors of pain and self-management status during the COVID-19 pandemic. METHODS: A cross-sectional design was used. Eighty-one Chinese patients with cancer were recruited in December 2020. The Brief Pain Inventory, the Pain Management Inventory, and the Pain Self-efficacy Questionnaire were used to evaluate patients' pain and self-management status. Descriptive statistical analysis and multiple linear regression models were conducted for the research aims. RESULTS: Two thirds of the participants experienced moderate to severe pain. Cancer pain had moderate to severe interference on 90.12% of patients' lives. Self-management of pain in these participants was low. The most commonly used methods of pain management included adjusting activity intensity to avoid fatigue, using distraction techniques, and massaging the sore area. The most effective methods to manage pain included taking analgesics prescribed by doctor, taking over-the-counter analgesics, and massaging the sore area. Fifteen patients (18.5%) believed that the COVID-19 pandemic had an impact on pain management and 26 patients (32.1%) needed support. Pain education, pain interference on sleep, chemotherapy, and payment status were significantly associated with cancer patients 'pain self-management. CONCLUSIONS: During the COVID-19 pandemic, patients with cancer had moderate to severe pain intensity with low levels of self-management and self-efficacy towards that pain.
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COVID-19 , Neoplasias , Autogestão , China/epidemiologia , Estudos Transversais , Humanos , Neoplasias/complicações , Neoplasias/terapia , Dor/tratamento farmacológico , Dor/epidemiologia , Pandemias , SARS-CoV-2RESUMO
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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High in-plane anisotropies arise in layered materials with large structural difference along different in-plane directions. We report an extreme case in layered TiS3, which features tightly bonded atomic chains along the b-axis direction, held together by weaker, interchain bonding along the a-axis direction. Experiments show thermal conductivity along the chain twice as high as between the chain, an in-plane anisotropy higher than any other layered materials measured to date. We found that in contrast to most other materials, optical phonons in TiS3 conduct an unusually high portion of heat (up to 66% along the b-axis direction). The large dispersiveness of optical phonons along the chains, contrasted to many fewer dispersive optical phonons perpendicular to the chains, is the primary reason for the observed high anisotropy in thermal conductivity. The finding discovers materials with unusual thermal conduction mechanism, as well as provides new material platforms for potential heat-routing or heat-managing devices.
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Alloying selected layered transitional metal trichalcogenides (TMTCs) with unique chain-like structures offers the opportunities for structural, optical, and electrical engineering thus expands the regime of this class of pseudo-one-dimensional materials. Here, the novel phase transition in anisotropic Nb(1- x ) Tix S3 alloys is demonstrated for the first time. Results show that Nb(1- x ) Tix S3 can be fully alloyed across the entire composition range from triclinic-phase NbS3 to monoclinic-phase TiS3 . Surprisingly, incorporation of a small concentration of Ti (x ≈ 0.05-0.18) into NbS3 host matrix is sufficient to induce triclinic to monoclinic transition. Theoretical studies suggest that Ti atoms effectively introduce hole doping, thus rapidly decreases the total energy of monoclinic phase and induces the phase transition. When alloyed, crystalline and optical anisotropy are largely preserved as evidenced by high resolution transmission electron microscopy and angle-resolved Raman spectroscopy. Further Raman measurements identify Raman modes to determine crystalline anisotropy direction and offer insights into the degree of anisotropy. Overall results introduce Nb(1- x ) Tix S3 as a new and easy phase change material and mark the first phase engineering in anisotropic van der Waals (vdW) trichalcogenide systems for their potential applications in two-dimensional superconductivity, electronics, photonics, and information technologies.
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Recent studies have demonstrated that tellurene is a van der Waals (vdW) two-dimensional material with potential optoelectronic and thermoelectric applications as a result of its pseudo-one-dimensional structure and properties. Here, we report on the pressure induced anomalous phase transition of tellurium nanoribbons. The observation of clean phase transitions was made possible with high quality single crystalline Te nanoribbons that are synthesized by hydrothermal reaction growth. The results show that phase transition has a large pressure hysteresis and multiple competing phases: during compression, the phase transition is sudden and takes place from trigonal to orthorhombic phase at 6.5 GPa. Orthorhombic phase remains stable up to higher pressures (15 GPa). In contrast, phase transition is not sudden during decompression, but orthorhombic and trigonal phases co-exist between 6.9 to 3.4 GPa. Grüneisen parameter calculations further confirm the presence of co-existing phases and suggest hysteretic phase change behavior. Finally, orthorhombic to trigonal phase transition occurs at 3.4 GPa which means overall pressure hysteresis is around 3.1 GPa.
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Low-symmetry layered two-dimensional (2D) materials with strong in-plane optical anisotropy can potentially be applied for polarization photodetection. This is especially true for those 2D materials with a direct band gap, which can efficiently absorb light with specific axial polarization. However, discovering such new anisotropic 2D materials with a direct band structure is still extremely challenging. Here, we fabricate a photodetector using a pseudo-one-dimensional (pseudo-1D) Nb(1- x)Ti xS3 alloy device and demonstrate that it is highly sensitive to the polarized light because of the strong in-plane optical anisotropy and direct band gap of the alloy by combining angle-resolved polarization Raman spectroscopy, azimuth-dependent reflectance difference microscopy, polarization-dependent absorption spectroscopy, and hybrid functional theory calculations. As a consequence, the polarization photodetector of the Nb(1- x)Ti xS3 alloy shows a large photocurrent anisotropic ratio and a high photoresponse. The choice of a low-symmetry layered pseudo-1D Nb(1- x)Ti xS3 alloy in polarization photodetection might open up new functionalities for novel optoelectronic device applications.
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Advanced mathematics, such as multiscale weighted colored subgraph and element specific persistent homology, and machine learning including deep neural networks were integrated to construct mathematical deep learning models for pose and binding affinity prediction and ranking in the last two D3R Grand Challenges in computer-aided drug design and discovery. D3R Grand Challenge 2 focused on the pose prediction, binding affinity ranking and free energy prediction for Farnesoid X receptor ligands. Our models obtained the top place in absolute free energy prediction for free energy set 1 in stage 2. The latest competition, D3R Grand Challenge 3 (GC3), is considered as the most difficult challenge so far. It has five subchallenges involving Cathepsin S and five other kinase targets, namely VEGFR2, JAK2, p38-α, TIE2, and ABL1. There is a total of 26 official competitive tasks for GC3. Our predictions were ranked 1st in 10 out of these 26 tasks.
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Aprendizado Profundo , Simulação de Acoplamento Molecular/métodos , Receptores Citoplasmáticos e Nucleares/química , Sítios de Ligação , Catepsinas/química , Desenho Assistido por Computador , Cristalografia por Raios X , Bases de Dados de Proteínas , Desenho de Fármacos , Ligantes , Ligação Proteica , Conformação Proteica , Proteínas Quinases/química , TermodinâmicaRESUMO
Artificial electromagnetic surfaces, metasurfaces, control light in the desired manner through the introduction of abrupt changes of electromagnetic fields at interfaces. Current modelling of metasurfaces successfully exploits generalised sheet transition conditions (GSTCs), a set of boundary conditions that account for electric and magnetic metasurface-induced optical responses. GSTCs are powerful theoretical tools but they are not readily applicable for arbitrarily shaped metasurfaces. Accurate and computationally efficient algorithms capable of implementing artificial boundary conditions are highly desired for designing free-form photonic devices. To address this challenge, we propose a numerical method based on conformal boundary optics with a modified finite difference time-domain (FDTD) approach which accurately calculates the electromagnetic fields across conformal metasurfaces. Illustrative examples of curved meta-optics are presented, showing results in good agreement with theoretical predictions. This method can become a powerful tool for designing and predicting optical functionalities of conformal metasurfaces for new lightweight, flexible and wearable photonic devices.
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Alloying in semiconductors has enabled many civilian technologies in electronics, optoelectronics, photonics, and others. While the alloying phenomenon is well established in traditional bulk semiconductors owing to a vast array of available ternary phase diagrams, alloying in 2D materials still remains at its seminal stages. This is especially true for transition metal trichalcogenides (TMTCs) such as TiS3 which has been recently predicted to be a direct gap, high carrier mobility, pseudo-1D semiconductor. In this work, we report on an unusual alloying rejection behavior in TiS3(1-x)Se3x vdW crystals. TEM, SEM, EDS, and angle-resolved Raman measurements show that only a miniscule amount (8%) of selenium can be successfully alloyed into a TiS3 host matrix despite vastly different precursor amounts as well as growth temperatures. This unusual behavior contrasts with other vdW systems such as TiS2(1-x)Se2x, MoS2(1-x)Se2x, Mo1-xWxS2, WS2(1-x)Se2x, where continuous alloying can be attained. Angle-resolved Raman and kelvin probe force microscopy measurements offer insights into how selenium alloying influences in-plane structural anisotropy as well as electron affinity values of exfoliated sheets. Our cluster expansion theory calculations show that only the alloys with a small amount of Se can be attained due to energetic instability above/below a certain selenium concentration threshold in the ternary phase diagrams. The overall findings highlight potential challenges in achieving stable Ti based TMTCs alloys.
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In-plane anisotropy of layered materials adds another dimension to their applications, opening up avenues in diverse angle-resolved devices. However, to fulfill a strong inherent in-plane anisotropy in layered materials still poses a significant challenge, as it often requires a low-symmetry nature of layered materials. Here, we report the fabrication of a member of layered semiconducting AIIIBVI compounds, TlSe, that possesses a low-symmetry tetragonal structure and investigate its anisotropic light-matter interactions. We first identify the in-plane Raman intensity anisotropy of thin-layer TlSe, offering unambiguous evidence that the anisotropy is sensitive to crystalline orientation. Further in-situ azimuth-dependent reflectance difference microscopy enables the direct evaluation of in-plane optical anisotropy of layered TlSe, and we demonstrate that the TlSe shows a linear dichroism under polarized absorption spectra arising from an in-plane anisotropic optical property. As a direct result of the linear dichroism, we successfully fabricate TlSe devices for polarization-sensitive photodetection. The discovery of layered TlSe with a strong in-plane anisotropy not only facilitates its applications in linear dichroic photodetection but opens up more possibilities for other functional device applications.
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Akin to the enormous number of discoveries made through traditional semiconductor alloys, alloying selected 2D semiconductors enables engineering of their electronic structure for a wide range of new applications. 2D alloys have been demonstrated when two components crystallized in the same phase, and their bandgaps displayed predictable monotonic variation. By stabilizing previously unobserved compositions and phases of GaSe1-xTe x at nanoscales on GaAs(111), we demonstrate abnormal band bowing effects and phase instability region when components crystallize in different phases. Advanced microscopy and spectroscopy measurements show as tellurium is alloyed into GaSe, nanostructures undergo hexagonal to monoclinic and isotropic to anisotropic transition. There exists an instability region (0.56 < x < 0.67) where both phases compete and coexist, and two different bandgap values can be found at the same composition leading to anomalous band bowing effects. Results highlight unique alloying effects, not existing in single-phase alloys, and phase engineering routes for potential applications in photonic and electronics.
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Aqueous solubility and partition coefficient are important physical properties of small molecules. Accurate theoretical prediction of aqueous solubility and partition coefficient plays an important role in drug design and discovery. The prediction accuracy depends crucially on molecular descriptors which are typically derived from a theoretical understanding of the chemistry and physics of small molecules. This work introduces an algebraic topology-based method, called element-specific persistent homology (ESPH), as a new representation of small molecules that is entirely different from conventional chemical and/or physical representations. ESPH describes molecular properties in terms of multiscale and multicomponent topological invariants. Such topological representation is systematical, comprehensive, and scalable with respect to molecular size and composition variations. However, it cannot be literally translated into a physical interpretation. Fortunately, it is readily suitable for machine learning methods, rendering topological learning algorithms. Due to the inherent correlation between solubility and partition coefficient, a uniform ESPH representation is developed for both properties, which facilitates multi-task deep neural networks for their simultaneous predictions. This strategy leads to a more accurate prediction of relatively small datasets. A total of six datasets is considered in this work to validate the proposed topological and multitask deep learning approaches. It is demonstrated that the proposed approaches achieve some of the most accurate predictions of aqueous solubility and partition coefficient. Our software is available online at http://weilab.math.msu.edu/TopP-S/. © 2018 Wiley Periodicals, Inc.
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Simulação de Dinâmica Molecular , Redes Neurais de Computação , Água/química , Algoritmos , Software , SolubilidadeRESUMO
The understanding of toxicity is of paramount importance to human health and environmental protection. Quantitative toxicity analysis has become a new standard in the field. This work introduces element specific persistent homology (ESPH), an algebraic topology approach, for quantitative toxicity prediction. ESPH retains crucial chemical information during the topological abstraction of geometric complexity and provides a representation of small molecules that cannot be obtained by any other method. To investigate the representability and predictive power of ESPH for small molecules, ancillary descriptors have also been developed based on physical models. Topological and physical descriptors are paired with advanced machine learning algorithms, such as the deep neural network (DNN), random forest (RF), and gradient boosting decision tree (GBDT), to facilitate their applications to quantitative toxicity predictions. A topology based multitask strategy is proposed to take the advantage of the availability of large data sets while dealing with small data sets. Four benchmark toxicity data sets that involve quantitative measurements are used to validate the proposed approaches. Extensive numerical studies indicate that the proposed topological learning methods are able to outperform the state-of-the-art methods in the literature for quantitative toxicity analysis. Our online server for computing element-specific topological descriptors (ESTDs) is available at http://weilab.math.msu.edu/TopTox/ .
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Algoritmos , Testes de Toxicidade , Aprendizado de Máquina , Redes Neurais de ComputaçãoRESUMO
Implicit solvent models divide solvation free energies into polar and nonpolar additive contributions, whereas polar and nonpolar interactions are inseparable and nonadditive. We present a feature functional theory (FFT) framework to break this ad hoc division. The essential ideas of FFT are as follows: (i) representability assumption: there exists a microscopic feature vector that can uniquely characterize and distinguish one molecule from another; (ii) feature-function relationship assumption: the macroscopic features, including solvation free energy, of a molecule is a functional of microscopic feature vectors; and (iii) similarity assumption: molecules with similar microscopic features have similar macroscopic properties, such as solvation free energies. Based on these assumptions, solvation free energy prediction is carried out in the following protocol. First, we construct a molecular microscopic feature vector that is efficient in characterizing the solvation process using quantum mechanics and Poisson-Boltzmann theory. Microscopic feature vectors are combined with macroscopic features, that is, physical observable, to form extended feature vectors. Additionally, we partition a solvation dataset into queries according to molecular compositions. Moreover, for each target molecule, we adopt a machine learning algorithm for its nearest neighbor search, based on the selected microscopic feature vectors. Finally, from the extended feature vectors of obtained nearest neighbors, we construct a functional of solvation free energy, which is employed to predict the solvation free energy of the target molecule. The proposed FFT model has been extensively validated via a large dataset of 668 molecules. The leave-one-out test gives an optimal root-mean-square error (RMSE) of 1.05 kcal/mol. FFT predictions of SAMPL0, SAMPL1, SAMPL2, SAMPL3, and SAMPL4 challenge sets deliver the RMSEs of 0.61, 1.86, 1.64, 0.86, and 1.14 kcal/mol, respectively. Using a test set of 94 molecules and its associated training set, the present approach was carefully compared with a classic solvation model based on weighted solvent accessible surface area. © 2017 Wiley Periodicals, Inc.
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Chemical vapor deposition and growth dynamics of highly anisotropic 2D lateral heterojunctions between pseudo-1D ReS2 and isotropic WS2 monolayers are reported for the first time. Constituent ReS2 and WS2 layers have vastly different atomic structure, crystallizing in anisotropic 1T' and isotropic 2H phases, respectively. Through high-resolution scanning transmission electron microscopy, electron energy loss spectroscopy, and angle-resolved Raman spectroscopy, this study is able to provide the very first atomic look at intimate interfaces between these dissimilar 2D materials. Surprisingly, the results reveal that ReS2 lateral heterojunctions to WS2 produce well-oriented (highly anisotropic) Re-chains perpendicular to WS2 edges. When vertically stacked, Re-chains orient themselves along the WS2 zigzag direction, and consequently, Re-chains exhibit six-fold rotation, resulting in loss of macroscopic scale anisotropy. The degree of anisotropy of ReS2 on WS2 largely depends on the domain size, and decreases for increasing domain size due to randomization of Re-chains and formation of ReS2 subdomains. Present work establishes the growth dynamics of atomic junctions between novel anisotropic/isotropic 2D materials, and overall results mark the very first demonstration of control over anisotropy direction, which is a significant leap forward for large-scale nanomanufacturing of anisotropic systems.