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We present a fully differentiable framework for seamlessly integrating wave optical components with geometrical lenses, offering an approach to enhance the performance of large-scale end-to-end optical systems. In this study, we focus on the integration of a metalens, a geometrical lens, and image data. Through the use of gradient-based optimization techniques, we demonstrate the design of nonparaxial imaging systems and the correction of aberrations inherent in geometrical optics. Our framework enables efficient and effective optimization of the entire optical system, leading to improved overall performance.
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The presence of the van der Waals gap in layered materials creates a wealth of intriguing phenomena different to their counterparts in conventional materials. For example, pressurization can generate a large anisotropic lattice shrinkage along the stacking orientation and/or a significant interlayer sliding, and many of the exotic pressure-dependent properties derive from these mechanisms. Here we report a giant piezoresistivity in pressurized ß'-In2Se3. Upon compression, a six-orders-of-magnitude drop of electrical resistivity is obtained below 1.2 GPa in ß'-In2Se3 flakes, yielding a giant piezoresistive gauge πp of -5.33 GPa-1. Simultaneously, the sample undergoes a semiconductor-to-semimetal transition without a structural phase transition. Surprisingly, linear dichroism study and theoretical first principles modelling show that these phenomena arise not due to shrinkage or sliding at the van der Waals gap, but rather are dominated by the layer-dependent atomic motions inside the quintuple layer, mainly from the shifting of middle Se atoms to their high-symmetric location. The atomic motions link to both the band structure modulation and the in-plane ferroelectric dipoles. Our work not only provides a prominent piezoresistive material but also points out the importance of intralayer atomic motions beyond van der Waals gap.
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Photocathodes-materials that convert photons into electrons through a phenomenon known as the photoelectric effect-are important for many modern technologies that rely on light detection or electron-beam generation1-3. However, current photocathodes are based on conventional metals and semiconductors that were mostly discovered six decades ago with sound theoretical underpinnings4,5. Progress in this field has been limited to refinements in photocathode performance based on sophisticated materials engineering1,6. Here we report unusual photoemission properties of the reconstructed surface of single crystals of the perovskite oxide SrTiO3(100), which were prepared by simple vacuum annealing. These properties are different from the existing theoretical descriptions4,7-10. In contrast to other photocathodes with a positive electron affinity, our SrTiO3 surface produces, at room temperature, discrete secondary photoemission spectra, which are characteristic of efficient photocathode materials with a negative electron affinity11,12. At low temperatures, the photoemission peak intensity is enhanced substantially and the electron beam obtained from non-threshold excitations shows longitudinal and transverse coherence that differs from previous results by at least an order of magnitude6,13,14. The observed emergence of coherence in secondary photoemission points to the development of a previously undescribed underlying process in addition to those of the current theoretical photoemission framework. SrTiO3 is an example of a fundamentally new class of photocathode quantum materials that could be used for applications that require intense coherent electron beams, without the need for monochromatic excitations.
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Semianalytical methods, such as rigorous coupled wave analysis, have been pivotal in the numerical analysis of photonic structures. In comparison to other numerical methods, they have a much lower computational cost, especially for structures with constant cross-sectional shapes (such as metasurface units). However, when the cross-sectional shape varies even mildly (such as a taper), existing semianalytical methods suffer from high computational costs. We show that the existing methods can be viewed as a zeroth-order approximation with respect to the structure's cross-sectional variation. We derive a high-order perturbative expansion with respect to the cross-sectional variation. Based on this expansion, we propose a new semianalytical method that is fast to compute even in the presence of large cross-sectional shape variation. Furthermore, we design an algorithm that automatically discretizes the structure in a way that achieves a user-specified accuracy level while at the same time reducing the computational cost.
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Two-dimensional (2D) materials exhibit remarkable mechanical properties, enabling their applications as flexible and stretchable ultrathin devices. As the origin of several extraordinary mechanical behaviors, ferroelasticity has also been predicted theoretically in 2D materials, but so far lacks experimental validation and investigation. Here, we present the experimental demonstration of 2D ferroelasticity in both exfoliated and chemical-vapor-deposited ß'-In2Se3 down to few-layer thickness. We identify quantitatively 2D spontaneous strain originating from in-plane antiferroelectric distortion, using both atomic-resolution electron microscopy and in situ X-ray diffraction. The symmetry-equivalent strain orientations give rise to three domain variants separated by 60° and 120° domain walls (DWs). Mechanical switching between these ferroelastic domains is achieved under ≤0.5% external strain, demonstrating the feasibility to tailor the antiferroelectric polar structure as well as DW patterns through mechanical stimuli. The detailed domain switching mechanism through both DW propagation and domain nucleation is unraveled, and the effects of 3D stacking on such 2D ferroelasticity are also discussed. The observed 2D ferroelasticity here should be widely available in 2D materials with anisotropic lattice distortion, including the 1T' transition metal dichalcogenides with Peierls distortion and 2D ferroelectrics such as the SnTe family, rendering tantalizing potential to tune 2D functionalities through strain or DW engineering.
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Micro-appearance models have brought unprecedented fidelity and details to cloth rendering. Yet, these models neglect fabric mechanics: when a piece of cloth interacts with the environment, its yarn and fiber arrangement usually changes in response to external contact and tension forces. Since subtle changes of a fabric's microstructures can greatly affect its macroscopic appearance, mechanics-driven appearance variation of fabrics has been a phenomenon that remains to be captured. We introduce a mechanics-aware model that adapts the microstructures of cloth yarns in a physics-based manner. Our technique works on two distinct physical scales: using physics-based simulations of individual yarns, we capture the rearrangement of yarn-level structures in response to external forces. These yarn structures are further enriched to obtain appearance-driving fiber-level details. The cross-scale enrichment is made practical through a new parameter fitting algorithm for simulation, an augmented procedural yarn model coupled with a custom-design regression neural network. We train the network using a dataset generated by joint simulations at both the yarn and the fiber levels. Through several examples, we demonstrate that our model is capable of synthesizing photorealistic cloth appearance in a mechanically plausible way.
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The scattering matrix, which quantifies the optical reflection and transmission of a photonic structure, is pivotal for understanding the performance of the structure. In many photonic design tasks, it is also desired to know how the structure's optical performance changes with respect to design parameters, that is, the scattering matrix's derivatives (or gradient). Here we address this need. We present a new algorithm for computing scattering matrix derivatives accurately and robustly. In particular, we focus on the computation in semi-analytical methods (such as rigorous coupled-wave analysis). To compute the scattering matrix of a structure, these methods must solve an eigen-decomposition problem. However, when it comes to computing scattering matrix derivatives, differentiating the eigen-decomposition poses significant numerical difficulties. We show that the differentiation of the eigen-decomposition problem can be completely sidestepped, and thereby propose a robust algorithm. To demonstrate its efficacy, we use our algorithm to optimize metasurface structures and reach various optical design goals.
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Spin Polarized Low Energy Electron Microscopy (SPLEEM) is a powerful tool to reveal the magnetic structure of ferromagnetic surfaces on the atomic depth scale level[1-3]. With aberration corrected LEEM and a high brightness spin polarized electron gun, high spatial resolution will provide more details for ultra-thin ferromagnetic film studies. This study reports the first realization of aberration corrected SPLEEM (AC-SPLEEM). The performance of the setup was tested on ferromagnetic Fe nanoscale islands on a W(110) single crystal, with spatial resolution of 3.3 nm in spin asymmetry images.
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Unravelling the three-dimensional structures and compositions of biological macromolecules sheds light on their functions and also contributes to the design of future biochemical compounds and processes. Atom probe tomography (APT) is demonstrated in this research as a new and effective approach to explore the structure and chemical composition of a single protein in the hydrated state. By introducing graphene encapsulation, proteins in solution can be immobilized on a metal specimen tip, with an end radius in the range of 50 nm to allow field ionization and evaporation. Using a ferritin particle as an example, analysis of the mass spectrum and reconstructed 3D chemical maps at near-atomic resolution acquired from APT reveals the core consisting of iron and iron oxides, the peptide shell containing amino acids, and the interior interface between the iron core and the peptide shell. The quantitative distribution and proportion of iron isotopes from a single ferritin core have been determined for the first time, as well as identification of the possible sites of amino acids inside the protein shell. The complete experimental protocol is straightforward and lays a foundation for future exploration of various macromolecules in a controlled environment.
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Ferritinas/análisis , Tomografía Computarizada por Rayos X , Animales , Grafito/química , Caballos , Bazo/químicaRESUMEN
Metasurfaces are optically thin metamaterials that promise complete control of the wavefront of light but are primarily used to control only the phase of light. Here, we present an approach, simple in concept and in practice, that uses meta-atoms with a varying degree of form birefringence and rotation angles to create high-efficiency dielectric metasurfaces that control both the optical amplitude and phase at one or two frequencies. This opens up applications in computer-generated holography, allowing faithful reproduction of both the phase and amplitude of a target holographic scene without the iterative algorithms required in phase-only holography. We demonstrate all-dielectric metasurface holograms with independent and complete control of the amplitude and phase at up to two optical frequencies simultaneously to generate two- and three-dimensional holographic objects. We show that phase-amplitude metasurfaces enable a few features not attainable in phase-only holography; these include creating artifact-free two-dimensional holographic images, encoding phase and amplitude profiles separately at the object plane, encoding intensity profiles at the metasurface and object planes separately, and controlling the surface textures of three-dimensional holographic objects.
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Van der Waals (vdW) assembly of layered materials is a promising paradigm for creating electronic and optoelectronic devices with novel properties. Ferroelectricity in vdW layered materials could enable nonvolatile memory and low-power electronic and optoelectronic switches, but to date, few vdW ferroelectrics have been reported, and few in-plane vdW ferroelectrics are known. We report the discovery of in-plane ferroelectricity in a widely investigated vdW layered material, ß'-In2Se3. The in-plane ferroelectricity is strongly tied to the formation of one-dimensional superstructures aligning along one of the threefold rotational symmetric directions of the hexagonal lattice in the c plane. Surprisingly, the superstructures and ferroelectricity are stable to 200°C in both bulk and thin exfoliated layers of In2Se3. Because of the in-plane nature of ferroelectricity, the domains exhibit a strong linear dichroism, enabling novel polarization-dependent optical properties.
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High-resolution single-cell imaging in their native or near-native state has received considerable interest for decades. In this research, we present an innovative approach that can be employed to study both morphological and nano-mechanical properties of hydrated single bacterial cells. The proposed strategy is to encapsulate wet cells with monolayer graphene with a newly developed water membrane approach, followed by imaging with both electron microscopy (EM) and atomic force microscopy (AFM). A computational framework was developed to provide additional insights, with the detailed nanoindentation process on graphene modelled based on the finite element method. The model was first validated by calibration with polymer materials of known properties, and the contribution of graphene was then studied and corrected to determine the actual moduli of the encapsulated hydrated sample. Application of the proposed approach was performed on hydrated bacterial cells (Klebsiella pneumoniae) to correlate the structural and mechanical information. EM and energy-dispersive x-ray spectroscopy imaging confirmed that the cells in their near-native stage can be studied inside the miniaturised environment enabled with graphene encapsulation. The actual moduli of the encapsulated hydrated cells were determined based on the developed computational model in parallel, with results comparable with those acquired with wet AFM. It is expected that the successful establishment of controlled graphene encapsulation offers a new route for probing liquid/live cells with scanning probe microscopy, as well as correlative imaging of hydrated samples for both biological and material sciences.
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Grafito/química , Klebsiella pneumoniae/citología , Nanopartículas/química , Simulación por Computador , Análisis de Elementos Finitos , Klebsiella pneumoniae/ultraestructura , Microscopía de Fuerza Atómica , Nanopartículas/ultraestructuraRESUMEN
A semiconductor p-n junction typically has a doping-induced carrier depletion region, where the doping level positively correlates with the built-in potential and negatively correlates with the depletion layer width. In conventional bulk and atomically thin junctions, this correlation challenges the synergy of the internal field and its spatial extent in carrier generation/transport. Organic-inorganic hybrid perovskites, a class of crystalline ionic semiconductors, are promising alternatives because of their direct badgap, long diffusion length, and large dielectric constant. Here, strong depletion in a lateral p-n junction induced by local electronic doping at the surface of individual CH3 NH3 PbI3 perovskite nanosheets is reported. Unlike conventional surface doping with a weak van der Waals adsorption, covalent bonding and hydrogen bonding between a MoO3 dopant and the perovskite are theoretically predicted and experimentally verified. The strong hybridization-induced electronic coupling leads to an enhanced built-in electric field. The large electric permittivity arising from the ionic polarizability further contributes to the formation of an unusually broad depletion region up to 10 µm in the junction. Under visible optical excitation without electrical bias, the lateral diode demonstrates unprecedented photovoltaic conversion with an external quantum efficiency of 3.93% and a photodetection responsivity of 1.42 A W-1 .
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The inverse diffusion curve problem focuses on automatic creation of diffusion curve images that resemble user provided color fields. This problem is challenging since the 1D curves have a nonlinear and global impact on resulting color fields via a partial differential equation (PDE). We introduce a new approach complementary to previous methods by optimizing curve geometry. In particular, we propose a novel iterative algorithm based on the theory of shape derivatives. The resulting diffusion curves are clean and well-shaped, and the final image closely approximates the input. Our method provides a user-controlled parameter to regularize curve complexity, and generalizes to handle input color fields represented in a variety of formats.
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Lateral transition-metal dichalcogenide and their heterostructures have attracted substantial attention, but there lacks a simple approach to produce large-scaled optoelectronic devices with graded composition. In particular, the incorporation of substitution and doping into heterostructure formation is rarely reported. Here, we demonstrate growth of a composition graded doped lateral WSe2/WS2 heterostructure by ambient pressure chemical vapor deposition in a single heat cycle. Through Raman and photoluminescence spectroscopy, we demonstrate that the monolayer heterostructure exhibits a clear interface between two domains and a graded composition distribution in each domain. The coexistence of two distinct doping modes, i.e., interstitial and substitutional doping, was verified experimentally. A distinct three-stage growth mechanism consisting of nucleation, epitaxial growth, and substitution was proposed. Electrical transport measurements reveal that this lateral heterostructure has representative characteristics of a photodiodes. The optoelectronic device based on the lateral WSe2/WS2 heterostructure shows improved photodetection performance in terms of a reasonable responsivity and a large photoactive area.
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Non-equilibrium molecular dynamics was used to simulate the dynamics of atoms at the atom probe surface and five objective functions were used to quantify errors. The results suggested that before ionization, thermal vibration and collision caused the atoms to displace up to 1Å and 25Å respectively. The average atom displacements were found to vary between 0.2 and 0.5Å. About 9 to 17% of the atoms were affected by collision. Due to the effects of collision and ion-ion repulsion, the back-calculated positions were on average 0.3-0.5Å different from the pre-ionized positions of the atoms when the number of ions generated per pulse was minimal. This difference could increase up to 8-10Å when 1.5ion/nm2 were evaporated per pulse. On the basis of the results, surface ion density was considered an important factor that needed to be controlled to minimize error in the evaporation process.
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Large-area two-dimensional (2D) heterojunctions are promising building blocks of 2D circuits. Understanding their intriguing electrostatics is pivotal but largely hindered by the lack of direct observations. Here graphene-WS2 heterojunctions are prepared over large areas using a seedless ambient-pressure chemical vapor deposition technique. Kelvin probe force microscopy, photoluminescence spectroscopy, and scanning tunneling microscopy characterize the doping in graphene-WS2 heterojunctions as-grown on sapphire and transferred to SiO2 with and without thermal annealing. Both p-n and n-n junctions are observed, and a flat-band condition (zero Schottky barrier height) is found for lightly n-doped WS2, promising low-resistance ohmic contacts. This indicates a more favorable band alignment for graphene-WS2 than has been predicted, likely explaining the low barriers observed in transport experiments on similar heterojunctions. Electrostatic modeling demonstrates that the large depletion width of the graphene-WS2 junction reflects the electrostatics of the one-dimensional junction between two-dimensional materials.
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Reduced hair models have proven successful for interactively simulating a full head of hair strands, building upon a fundamental assumption that only a small set of guide hairs are needed for explicit simulation, and the rest of the hair move coherently and thus can be interpolated using guide hairs. Unfortunately, hair-solid interactions is a pathological case for traditional reduced hair models, as the motion coherence between hair strands can be arbitrarily broken by interacting with solids. In this paper, we propose an adaptive hair skinning method for interactive hair simulation with hair-solid collisions. We precompute many eligible sets of guide hairs and the corresponding interpolation relationships that are represented using a compact strand-based hair skinning model. At runtime, we simulate only guide hairs; for interpolating every other hair, we adaptively choose its guide hairs, taking into account motion coherence and potential hair-solid collisions. Further, we introduce a two-way collision correction algorithm to allow sparsely sampled guide hairs to resolve collisions with solids that can have small geometric features. Our method enables interactive simulation of more than 150 K hair strands interacting with complex solid objects, using 400 guide hairs. We demonstrate the efficiency and robustness of the method with various hairstyles and user-controlled arbitrary hair-solid interactions.
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Gráficos por Computador , Simulación por Computador , Cabello/fisiología , Procesamiento de Imagen Asistido por Computador/métodos , Algoritmos , Humanos , Movimiento/fisiologíaRESUMEN
Stress analysis is a crucial tool for designing structurally sound shapes. However, the expensive computational cost has hampered its use in interactive shape editing tasks. We augment the existing example-based shape editing tools, and propose a fast subspace stress analysis method to enable stress-aware shape editing. In particular, we construct a reduced stress basis from a small set of shape exemplars and possible external forces. This stress basis is automatically adapted to the current user edited shape on the fly, and thereby offers reliable stress estimation. We then introduce a new finite element discretization scheme to use the reduced basis for fast stress analysis. Our method runs up to two orders of magnitude faster than the full-space finite element analysis, with average L2 estimation errors less than 2 percent and maximum L2 errors less than 6 percent. Furthermore, we build an interactive stress-aware shape editing tool to demonstrate its performance in practice.
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Ion migration in hybrid organic-inorganic perovskites has been suggested to be an important factor for many unusual behaviors in perovskite-based optoelectronics, such as current-voltage hysteresis, low-frequency giant dielectric response, and the switchable photovoltaic effect. However, the role played by ion migration in the photoelectric conversion process of perovskites is still unclear. In this work, we provide microscale insights into the influence of ion migration on the microstructure, stability, and light-matter interaction in perovskite micro/nanowires by using spatially resolved optical characterization techniques. We observed that ion migration, especially the migration of MA(+) ions, will induce a reversible structural swell-shrink in perovskites and recoverably affect the reflective index, quantum efficiency, light-harvesting, and photoelectric properties. The maximum ion migration quantity in perovskites was as high as approximately 30%, resulting in lattice swell or shrink of approximately 4.4%. Meanwhile, the evidence shows that ion migration in perovskites could gradually accelerate the aging of perovskites because of lattice distortion in the reversible structural swell-shrink process. Knowledge regarding reversible structural swell-shrink and recoverable optical properties may shed light on the development of optoelectronic and converse piezoelectric devices based on perovskites.