Advances in optoplasmonic sensors – combining optical nano/microcavities and photonic crystals with plasmonic nanostructures and nanoparticles

AbstractNanophotonic device building blocks, such as optical nano/microcavities and plasmonic nanostructures, lie at the forefront of sensing and spectrometry of trace biological and chemical substances. A new class of nanophotonic architecture has emerged by combining optically resonant dielectric nano/microcavities with plasmonically resonant metal nanostructures to enable detection at the nanoscale with extraordinary sensitivity. Initial demonstrations include single-molecule detection and even single-ion sensing. The coupled photonic-plasmonic resonator system promises a leap forward in the nanoscale analysis of physical, chemical, and biological entities. These optoplasmonic sensor structures could be the centrepiece of miniaturised analytical laboratories, on a chip, with detection capabilities that are beyond the current state of the art. In this paper, we review this burgeoning field of optoplasmonic biosensors. We first focus on the state of the art in nanoplasmonic sensor structures, high quality factor optical microcavities, and photonic crystals separately before proceeding to an outline of the most recent advances in hybrid sensor systems. We discuss the physics of this modality in brief and each of its underlying parts, then the prospects as well as challenges when integrating dielectric nano/microcavities with metal nanostructures. In Section 5, we hint to possible future applications of optoplasmonic sensing platforms which offer many degrees of freedom towards biomedical diagnostics at the level of single molecules.

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Mechanically-Tunable Quantum Interference in Ferrocene-Based Single-Molecule Junctions

10.26434/chemrxiv.12252059 ◽

2020 ◽

Author(s):

María Camarasa-Gómez ◽

Daniel Hernangómez-Pérez ◽

Michael S. Inkpen ◽

Giacomo Lovat ◽

E-Dean Fung ◽

...

Keyword(s):

Single Molecule ◽

Quantum Interference ◽

Degrees Of Freedom ◽

Building Blocks ◽

Ferrocene Derivative ◽

Single Molecule Junctions ◽

Molecule Junction ◽

Single Molecule Junction ◽

The Impact ◽

D Orbitals

Ferrocenes are ubiquitous organometallic building blocks that comprise a Fe atom sandwiched between two cyclopentadienyl (Cp) rings that rotate freely at room temperature. Of widespread interest in fundamental studies and real-world applications, they have also attracted some interest as functional elements of molecular-scale devices. Here we investigate the impact of the configurational degrees of freedom of a ferrocene derivative on its single-molecule junction conductance. Measurements indicate that the conductance of the ferrocene derivative, which is suppressed by two orders of magnitude as compared to a fully conjugated analog, can be modulated by altering the junction configuration. Ab initio transport calculations show that the low conductance is a consequence of destructive quantum interference effects that arise from the hybridization of metal-based d-orbitals and the ligand-based π-system. By rotating the Cp rings, the hybridization, and thus the quantum interference, can be mechanically controlled, resulting in a conductance modulation that is seen experimentally.

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Self-assembled plasmonic metamaterials

Nanophotonics ◽

10.1515/nanoph-2012-0036 ◽

2013 ◽

Vol 2 (3) ◽

pp. 211-240 ◽

Cited By ~ 36

Author(s):

Stefan Mühlig ◽

Alastair Cunningham ◽

José Dintinger ◽

Toralf Scharf ◽

Thomas Bürgi ◽

...

Keyword(s):

Self Assembly ◽

Degrees Of Freedom ◽

Building Blocks ◽

Spatial Arrangement ◽

Plasmonic Nanostructures ◽

Bottom Up ◽

Unit Cells ◽

Amorphous Structures ◽

Self Assembled ◽

Novel Applications

AbstractNowadays for the sake of convenience most plasmonic nanostructures are fabricated by top-down nanofabrication technologies. This offers great degrees of freedom to tailor the geometry with unprecedented precision. However, it often causes disadvantages as well. The structures available are usually planar and periodically arranged. Therefore, bulk plasmonic structures are difficult to fabricate and the periodic arrangement causes undesired effects, e.g., strong spatial dispersion is observed in metamaterials. These limitations can be mitigated by relying on bottom-up nanofabrication technologies. There, self-assembly methods and techniques from the field of colloidal nanochemistry are used to build complex functional unit cells in solution from an ensemble of simple building blocks, i.e., in most cases plasmonic nanoparticles. Achievable structures are characterized by a high degree of nominal order only on a short-range scale. The precise spatial arrangement across larger dimensions is not possible in most cases; leading essentially to amorphous structures. Such self-assembled nanostructures require novel analytical means to describe their properties, innovative designs of functional elements that possess a desired near- and far-field response, and entail genuine nanofabrication and characterization techniques. Eventually, novel applications have to be perceived that are adapted to the specifics of the self-assembled nanostructures. This review shall document recent progress in this field of research. Emphasis is put on bottom-up amorphous metamaterials. We document the state-of-the-art but also critically assess the problems that have to be overcome.

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Plasmonic gas and chemical sensing

Nanophotonics ◽

10.1515/nanoph-2014-0002 ◽

2014 ◽

Vol 3 (3) ◽

pp. 157-180 ◽

Cited By ~ 55

Author(s):

Andreas Tittl ◽

Harald Giessen ◽

Na Liu

Keyword(s):

Single Molecule ◽

Local Environment ◽

Building Blocks ◽

Industrial Applications ◽

Noble Metal Nanoparticles ◽

Sensor Technology ◽

Plasmonic Nanostructures ◽

Robust Detection ◽

Single Molecule Level ◽

Plasmonic Particles

AbstractSensitive and robust detection of gases and chemical reactions constitutes a cornerstone of scientific research and key industrial applications. In an effort to reach progressively smaller reagent concentrations and sensing volumes, optical sensor technology has experienced a paradigm shift from extended thin-film systems towards engineered nanoscale devices. In this size regime, plasmonic particles and nanostructures provide an ideal toolkit for the realization of novel sensing concepts. This is due to their unique ability to simultaneously focus light into subwavelength hotspots of the electromagnetic field and to transmit minute changes of the local environment back into the farfield as a modulation of their optical response. Since the basic building blocks of a plasmonic system are commonly noble metal nanoparticles or nanostructures, plasmonics can easily be integrated with a plethora of chemically or catalytically active materials and compounds to investigate processes ranging from hydrogen absorption in palladium to the detection of trinitrotoluene (TNT). In this review, we will discuss a multitude of plasmonic sensing strategies, spanning the technological scale from simple plasmonic particles embedded in extended thin films to highly engineered complex plasmonic nanostructures. Due to their flexibility and excellent sensing performance, plasmonic structures may open an exciting pathway towards the detection of chemical and catalytic events down to the single molecule level.

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ENGINEERING PLASMONIC COLORS IN METAL NANOSTRUCTURES

Journal of Molecular and Engineering Materials ◽

10.1142/s2251237314400115 ◽

2014 ◽

Vol 02 (02) ◽

pp. 1440011 ◽

Cited By ~ 6

Author(s):

SHAWN J. TAN ◽

XIAO MING GOH ◽

YING MIN WANG ◽

JOEL K. W. YANG ◽

JINGHUA TENG

Keyword(s):

Structural Design ◽

State Of The Art ◽

Visible Spectrum ◽

Metal Nanostructures ◽

Plasmonic Nanostructures ◽

Length Scale ◽

Biological Sensing ◽

Color Printing ◽

The Rich ◽

Immense Potential

Plasmonic nanostructures hold immense potential for structure-based color engineering at the subwavelength length scale. In this paper, we will review representative works that demonstrate promising strategies to exploit the rich mechanisms of surface plasmons for color engineering across the visible spectrum. By varying the structural design and material composition of plasmonic nanostructures through chemical synthesis or lithography, these approaches can achieve highly controllable and tunable colors for a wide variety of applications. We will also critically discuss the applications of these state-of-the-art technologies in color filtering, color printing and color-based chemical and biological sensing.

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Mechanically-Tunable Quantum Interference in Ferrocene-Based Single-Molecule Junctions

10.26434/chemrxiv.12252059.v1 ◽

2020 ◽

Author(s):

María Camarasa-Gómez ◽

Daniel Hernangómez-Pérez ◽

Michael S. Inkpen ◽

Giacomo Lovat ◽

E-Dean Fung ◽

...

Keyword(s):

Single Molecule ◽

Quantum Interference ◽

Degrees Of Freedom ◽

Building Blocks ◽

Ferrocene Derivative ◽

Single Molecule Junctions ◽

Molecule Junction ◽

Single Molecule Junction ◽

The Impact ◽

D Orbitals

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Design of True Random Number Circuit with Controllable Frequency

Electronics ◽

10.3390/electronics10131517 ◽

2021 ◽

Vol 10 (13) ◽

pp. 1517

Author(s):

Xinsheng Wang ◽

Xiyue Wang

Keyword(s):

Random Number ◽

Noise Source ◽

State Of The Art ◽

Building Blocks ◽

Encryption Algorithm ◽

Random Numbers ◽

Random Number Generators ◽

Random Telegraph Noise ◽

Telegraph Noise ◽

Novel Method

True random number generators (TRNGs) have been a research hotspot due to secure encryption algorithm requirements. Therefore, such circuits are necessary building blocks in state-of-the-art security controllers. In this paper, a TRNG based on random telegraph noise (RTN) with a controllable rate is proposed. A novel method of noise array circuits is presented, which consists of digital decoder circuits and RTN noise circuits. The frequency of generating random numbers is controlled by the speed of selecting different gating signals. The results of simulation show that the array circuits consist of 64 noise source circuits that can generate random numbers by a frequency from 1 kHz to 16 kHz.

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Dimerization and oligomerization of DNA-assembled building blocks for controlled multi-motion in high-order architectures

Nature Communications ◽

10.1038/s41467-021-23532-y ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Ling Xin ◽

Xiaoyang Duan ◽

Na Liu

Keyword(s):

Building Block ◽

Degrees Of Freedom ◽

Building Blocks ◽

Single Type ◽

Hierarchical Assembly ◽

Optical Responses ◽

Self Association ◽

Living Organisms ◽

Order Structures ◽

Chiral System

AbstractIn living organisms, proteins are organized prevalently through a self-association mechanism to form dimers and oligomers, which often confer new functions at the intermolecular interfaces. Despite the progress on DNA-assembled artificial systems, endeavors have been largely paid to achieve monomeric nanostructures that mimic motor proteins for a single type of motion. Here, we demonstrate a DNA-assembled building block with rotary and walking modules, which can introduce new motion through dimerization and oligomerization. The building block is a chiral system, comprising two interacting gold nanorods to perform rotation and walking, respectively. Through dimerization, two building blocks can form a dimer to yield coordinated sliding. Further oligomerization leads to higher-order structures, containing alternating rotation and sliding dimer interfaces to impose structural twisting. Our hierarchical assembly scheme offers a design blueprint to construct DNA-assembled advanced architectures with high degrees of freedom to tailor the optical responses and regulate multi-motion on the nanoscale.

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Optimal Relabeling of Water Molecules and Single-Molecule Entropy Estimation

Biophysica ◽

10.3390/biophysica1030021 ◽

2021 ◽

Vol 1 (3) ◽

pp. 279-296

Author(s):

Federico Fogolari ◽

Gennaro Esposito

Keyword(s):

Single Molecule ◽

Degrees Of Freedom ◽

Water Molecules ◽

Maximum Information ◽

Nearest Neighbours ◽

Biomolecular Simulations ◽

Solvent Molecules ◽

Solvation Entropy ◽

Dynamics Simulations ◽

Internal Degrees Of Freedom

Estimation of solvent entropy from equilibrium molecular dynamics simulations is a long-standing problem in statistical mechanics. In recent years, methods that estimate entropy using k-th nearest neighbours (kNN) have been applied to internal degrees of freedom in biomolecular simulations, and for the rigorous computation of positional-orientational entropy of one and two molecules. The mutual information expansion (MIE) and the maximum information spanning tree (MIST) methods were proposed and used to deal with a large number of non-independent degrees of freedom, providing estimates or bounds on the global entropy, thus complementing the kNN method. The application of the combination of such methods to solvent molecules appears problematic because of the indistinguishability of molecules and of their symmetric parts. All indistiguishable molecules span the same global conformational volume, making application of MIE and MIST methods difficult. Here, we address the problem of indistinguishability by relabeling water molecules in such a way that each water molecule spans only a local region throughout the simulation. Then, we work out approximations and show how to compute the single-molecule entropy for the system of relabeled molecules. The results suggest that relabeling water molecules is promising for computation of solvation entropy.

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An experimental study on feature-based SLAM for multi-legged robots with RGB-D sensors

Industrial Robot the international journal of robotics research and application ◽

10.1108/ir-11-2016-0340 ◽

2017 ◽

Vol 44 (4) ◽

pp. 428-441 ◽

Cited By ~ 11

Author(s):

Michał R. Nowicki ◽

Dominik Belter ◽

Aleksander Kostusiak ◽

Petr Cížek ◽

Jan Faigl ◽

...

Keyword(s):

Performance Metrics ◽

State Of The Art ◽

Building Blocks ◽

Bundle Adjustment ◽

The State ◽

Legged Robots ◽

Evaluation Methodology ◽

Walking Robots ◽

Content Type ◽

Feature Based

Purpose This paper aims to evaluate four different simultaneous localization and mapping (SLAM) systems in the context of localization of multi-legged walking robots equipped with compact RGB-D sensors. This paper identifies problems related to in-motion data acquisition in a legged robot and evaluates the particular building blocks and concepts applied in contemporary SLAM systems against these problems. The SLAM systems are evaluated on two independent experimental set-ups, applying a well-established methodology and performance metrics. Design/methodology/approach Four feature-based SLAM architectures are evaluated with respect to their suitability for localization of multi-legged walking robots. The evaluation methodology is based on the computation of the absolute trajectory error (ATE) and relative pose error (RPE), which are performance metrics well-established in the robotics community. Four sequences of RGB-D frames acquired in two independent experiments using two different six-legged walking robots are used in the evaluation process. Findings The experiments revealed that the predominant problem characteristics of the legged robots as platforms for SLAM are the abrupt and unpredictable sensor motions, as well as oscillations and vibrations, which corrupt the images captured in-motion. The tested adaptive gait allowed the evaluated SLAM systems to reconstruct proper trajectories. The bundle adjustment-based SLAM systems produced best results, thanks to the use of a map, which enables to establish a large number of constraints for the estimated trajectory. Research limitations/implications The evaluation was performed using indoor mockups of terrain. Experiments in more natural and challenging environments are envisioned as part of future research. Practical implications The lack of accurate self-localization methods is considered as one of the most important limitations of walking robots. Thus, the evaluation of the state-of-the-art SLAM methods on legged platforms may be useful for all researchers working on walking robots’ autonomy and their use in various applications, such as search, security, agriculture and mining. Originality/value The main contribution lies in the integration of the state-of-the-art SLAM methods on walking robots and their thorough experimental evaluation using a well-established methodology. Moreover, a SLAM system designed especially for RGB-D sensors and real-world applications is presented in details.

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Deep Learning for Brain Tumor Segmentation: A Survey of State-of-the-Art

Journal of Imaging ◽

10.3390/jimaging7020019 ◽

2021 ◽

Vol 7 (2) ◽

pp. 19

Author(s):

Tirivangani Magadza ◽

Serestina Viriri

Keyword(s):

Image Analysis ◽

Deep Learning ◽

Brain Tumor ◽

Quantitative Analysis ◽

Medical Image ◽

State Of The Art ◽

Medical Image Analysis ◽

Building Blocks ◽

Tumor Segmentation ◽

Brain Tumor Segmentation

Quantitative analysis of the brain tumors provides valuable information for understanding the tumor characteristics and treatment planning better. The accurate segmentation of lesions requires more than one image modalities with varying contrasts. As a result, manual segmentation, which is arguably the most accurate segmentation method, would be impractical for more extensive studies. Deep learning has recently emerged as a solution for quantitative analysis due to its record-shattering performance. However, medical image analysis has its unique challenges. This paper presents a review of state-of-the-art deep learning methods for brain tumor segmentation, clearly highlighting their building blocks and various strategies. We end with a critical discussion of open challenges in medical image analysis.

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