High density periodic metal nanopyramids for surface enhanced raman spectroscopy

The work presented in this thesis is focused on two areas. First, a new type of nanotextured noble-metal surface has been developed. The new nanotextured surface is expected to enhance Raman scattering, called surface enhanced Raman scattering (SERS), from molecules absorbed on the surface due to large electromagnetic fields created in nanoscale gaps on the nanotextured metal surfaces by a laser excitation source. By collecting and analyzing the enhanced Raman (inelastically) scattered photons, the molecular bond information can be identified using methods from conventional Raman spectroscopy. Raman spectroscopy is very powerful analytical method in chemistry, biology and other scientific areas, since it provides molecular vibrational information, which is considered as fingerprint the molecule and material.\ud However, Raman spectroscopy is less commonly used compared to infrared (IR)\ud spectroscopy, for example, due to its extremely weak signal (approximately 1 in 107 photons is inelastically scattered). Over the past few decades, there has been a dramatic increase in Raman spectroscopy based on SERS since it can provide huge Raman scattered intensity enhancements commonly reaching million-fold levels and even billion-fold increases. A good SERS substrate should provide both large Raman enhancements (~106-108) over large areas (~mm2) in order to be used as an analytical measurement technique. Four important aspects should be considered when developing a new SERS substrate: i. the first and most important is that the nanoscale gaps should be a made from a noble metal (e.g. Ag and Au), when using laser sources in the visible spectrum, with gap distances less than 5nm ii. the substrate should contain a high density of nanogaps (nanogap/cm2) with homogeneous spatial distribution, iii. the geometric alignment of the nanogaps to the excitation laser polarization should be well-controlled in order to maximize the generation of the local surface plasmon, and iv. The nanogap should be easily accessible for molecular diffusion into the nanogap region.\ud Based on the description above we have developed a general technique to manufacture high density nanopyramid (NPy) and nanogroove (NG) array templates from (100) silicon and subsequently coated with thin layers of polycrystalline gold. Small pitch NPy arrays form spontaneously using anisotropic wet etching silicon following lithographic patterning of an etching mask. A sharp nanocrevice gap is created between two adjacent pyramids and is used to couple laser excitation into a local surface plasmon. The size and density of these nanocrevices are determined by the nanolithography dimensions and etching time. We have studied the behavior of the gold NPy surfaces using a combination of the numerical modeling, reflection spectroscopy and Raman spectroscopy. Reflection spectroscopy provides information about the coupling of the optical laser excitation into a local surface plasmon resonance that includes resonant coupling energy, metal interband transition effects, dielectric interface dependent resonant energy, and polarization alignment effects. Raman spectroscopy allows us to probe the enhancement properties of the gold NPy surface and extensive studies of the enhancement behavior of the NPy surfaces using surface adsorbed rhodamine-6G in water and monolayers of chemisorbed benzenethiol have been performed

Particle Deposition in Microfluidic Devices at Elevated Temperatures

In microchannels, interaction and transport of micro-/nanoparticles and biomolecules are crucial phenomena for many microfluidic applications, such as nanomedicine, portable food processing devices, microchannel heat exchangers, etc. The phenomenon that particles suspended in liquid are captured by a solid surface (e.g., microchannel wall) is referred to as particle deposition. Particle deposition is of importance in numerous practical applications and is also of fundamental interest to the field of colloid science. This chapter presents researches on fouling and particle deposition in microchannels, especially the effects of temperature and temperature gradient, which have been frequently ‘ignored’ but are important factors for thermal-driven particle deposition and fouling processes at elevated temperatures

Keeping speed and distance for aligned motion

The cohesive collective motion (flocking, swarming) of autonomous agents is ubiquitously observed and exploited in both natural and man-made settings, thus, minimal models for its description are essential. In a model with continuous space and time we find that if two particles arrive symmetrically in a plane at a large angle, then (i) radial repulsion and (ii) linear self-propelling toward a fixed preferred speed are sufficient for them to depart at a smaller angle. For this local gain of momentum explicit velocity alignment is not necessary, nor are adhesion/attraction, inelasticity or anisotropy of the particles, or nonlinear drag. With many particles obeying these microscopic rules of motion we find that their spatial confinement to a square with periodic boundaries (which is an indirect form of attraction) leads to stable macroscopic ordering. As a function of the strength of added noise we see – at finite system sizes – a critical slowing down close to the order-disorder boundary and a discontinuous transition. After varying the density of particles at constant system size and varying the size of the system with constant particle density we predict that in the infinite system size (or density) limit the hysteresis loop disappears and the transition becomes continuous. We note that animals, humans, drones, etc. tend to move asynchronously and are often more responsive to motion than positions. Thus, for them velocity-based continuous models can provide higher precision than coordinate-based models. An additional characteristic and realistic feature of the model is that convergence to the ordered state is fastest at a finite density, which is in contrast to models applying (discontinuous) explicit velocity alignments and discretized time. In summary, we find that the investigated model can provide a minimal description of flocking

Edge-Mediated Skyrmion Chain and Its Collective Dynamics in a Confined Geometry

The emergence of a topologically nontrivial vortex-like magnetic structure, the magnetic skyrmion, has launched new concepts for memory devices. There, extensive studies have theoretically demonstrated the ability to encode information bits by using a chain of skyrmions in one-dimensional nanostripes. Here, we report the first experimental observation of the skyrmion chain in FeGe nanostripes by using high resolution Lorentz transmission electron microscopy. Under an applied field normal to the nanostripes plane, we observe that the helical ground states with distorted edge spins would evolves into individual skyrmions, which assemble in the form of chain at low field and move collectively into the center of nanostripes at elevated field. Such skyrmion chain survives even as the width of nanostripe is much larger than the single skyrmion size. These discovery demonstrates new way of skyrmion formation through the edge effect, and might, in the long term, shed light on the applications.Comment: 7 pages, 3 figure

OSIC: A New One-Stage Image Captioner Coined

Mainstream image caption models are usually two-stage captioners, i.e., calculating object features by pre-trained detector, and feeding them into a language model to generate text descriptions. However, such an operation will cause a task-based information gap to decrease the performance, since the object features in detection task are suboptimal representation and cannot provide all necessary information for subsequent text generation. Besides, object features are usually represented by the last layer features that lose the local details of input images. In this paper, we propose a novel One-Stage Image Captioner (OSIC) with dynamic multi-sight learning, which directly transforms input image into descriptive sentences in one stage. As a result, the task-based information gap can be greatly reduced. To obtain rich features, we use the Swin Transformer to calculate multi-level features, and then feed them into a novel dynamic multi-sight embedding module to exploit both global structure and local texture of input images. To enhance the global modeling of encoder for caption, we propose a new dual-dimensional refining module to non-locally model the interaction of the embedded features. Finally, OSIC can obtain rich and useful information to improve the image caption task. Extensive comparisons on benchmark MS-COCO dataset verified the superior performance of our method

Electrical Probing of Field-Driven Cascading Quantized Transitions of Skyrmion Cluster States in MnSi Nanowires

Magnetic skyrmions are topologically stable whirlpool-like spin textures that offer great promise as information carriers for future ultra-dense memory and logic devices1-4. To enable such applications, particular attention has been focused on the skyrmions properties in highly confined geometry such as one dimensional nanowires5-8. Hitherto it is still experimentally unclear what happens when the width of the nanowire is comparable to that of a single skyrmion. Here we report the experimental demonstration of such scheme, where magnetic field-driven skyrmion cluster (SC) states with small numbers of skyrmions were demonstrated to exist on the cross-sections of ultra-narrow single-crystal MnSi nanowires (NWs) with diameters, comparable to the skyrmion lattice constant (18 nm). In contrast to the skyrmion lattice in bulk MnSi samples, the skyrmion clusters lead to anomalous magnetoresistance (MR) behavior measured under magnetic field parallel to the NW long axis, where quantized jumps in MR are observed and directly associated with the change of the skyrmion number in the cluster, which is supported by Monte Carlo simulations. These jumps show the key difference between the clustering and crystalline states of skyrmions, and lay a solid foundation to realize skyrmion-based memory devices that the number of skyrmions can be counted via conventional electrical measurements

NoiSER: Noise is All You Need for Low-Light Image Enhancement

In this paper, we present an embarrassingly simple yet effective solution to a seemingly impossible mission, low-light image enhancement (LLIE) without access to any task-related data. The proposed solution, Noise SElf-Regression (NoiSER), simply learns a convolutional neural network equipped with a instance-normalization layer by taking a random noise image, $\mathcal{N}(0,\sigma^2)$ for each pixel, as both input and output for each training pair, and then the low-light image is fed to the learned network for predicting the normal-light image. Technically, an intuitive explanation for its effectiveness is as follows: 1) the self-regression reconstructs the contrast between adjacent pixels of the input image, 2) the instance-normalization layers may naturally remediate the overall magnitude/lighting of the input image, and 3) the $\mathcal{N}(0,\sigma^2)$ assumption for each pixel enforces the output image to follow the well-known gray-world hypothesis \cite{Gary-world_Hypothesis} when the image size is big enough, namely, the averages of three RGB components of an image converge to the same value. Compared to existing SOTA LLIE methods with access to different task-related data, NoiSER is surprisingly highly competitive in enhancement quality, yet with a much smaller model size, and much lower training and inference cost. With only $\sim$ 1K parameters, NoiSER realizes about 1 minute for training and 1.2 ms for inference with 600x400 resolution on RTX 2080 Ti. As a bonus, NoiSER possesses automated over-exposure suppression ability and shows excellent performance on over-exposed photos

Large area metal nanowire arrays with submicron pitch and tunable sub-20 nm nanogaps

We present a new top-down nanofabrication technology to realize large area metal nanowire (m-NW) arrays with tunable sub-20 nm separation nanogaps without the use of chemical etching or milling of the metal layer. The nanofabrication technology is based on a self-regulating metal deposition process that is facilitated by closely spaced and isolated heterogeneous template surfaces that confines the metal deposition into two dimensions. Electrically isolated parallel arrays of m-NW can be realized with uniform and controllable nanogaps. Au-NW arrays are presented with high-density ~105 NWs cm-1, variable NW diameters down to 50 nm, variable nanogaps down to 5 nm, and very large nanogap length density ~1 km cm-2. A spatially averaged surface enhanced Raman scattering (SERS) analytical enhancement factor of (1.5±0.2)×107 is demonstrated from a benzenethiol monolayer chemisorbed on a Au-NW array substrat