Super-resolution Spectroscopy Research Articles

Super-resolution spectroscopy via spectrum slicing with a Fabry–Perot cavity

Spectroscopy is one of the most powerful technical tools that are widely used in the study of natural sciences and the development of high technologies. To improve the performance of a traditional dispersive spectrometer, there is a competition between its spectral resolution and the geometric volume; a higher resolution is usually accompanied by a higher cost as well. However, a growing body of evidence suggests an urgent demand for miniaturized spectrometers with high spectral resolution and low costs. In this paper, we propose and study super-resolution spectroscopy via spectrum slicing by use of a Fabry–Perot (FP) cavity combined with a traditional spectrometer. The cavity functions as a spectral filter to slice into discrete pieces the continuous spectrum of the input light. For each given cavity length, the cavity outputs a set of sliced spectral pieces that are then analyzed and recorded by the subsequent spectrometer. By scanning the cavity length, one will have multiple sets of sliced spectral pieces that are then finally fused to recover a resolution-enhanced copy of the input spectrum. A theoretical analysis for the super-resolution spectroscopy is provided to prove the feasibility of the proposal, as further confirmed by MATLAB numerical simulation. The studied spectral analysis technique will benefit the research fields in need of high resolution spectrometers with moderate device volumes and low costs.

Perspectives and recent advances in super-resolution spectroscopy: Stochastic and disordered-based approaches

Spectroscopic applications are characterized by the constant effort to combine high spectral resolution with large bandwidth. A trade-off typically exists between these two aspects, but the recent development of super-resolved spectroscopy techniques is bringing new opportunities into this field. This is particularly relevant for all applications where compact and cost-effective instruments are needed such as in sensing, quality control, environmental monitoring, or biometric authentication, to name a few. These unconventional approaches exploit several strategies for spectral investigation, taking advantage of concepts such as sparse sampling, artificial intelligence, or post-processing reconstruction algorithms. In this Perspective, we discuss the main strengths and weaknesses of these methods, tracing promising future directions for their further development and widespread adoption.

Harnessing disorder for photonic device applications

For photonic devices, structural disorder and light scattering have long been considered annoying and detrimental features that were best avoided or minimized. This review shows that disorder and complexity can be harnessed for photonic device applications. Compared to ordered systems, disordered systems provide much more possibilities and diverse optical responses. They have been used to create physical unclonable functions for secret key generation, and more recently for random projection, high-dimensional matrix multiplication, and reservoir computing. Incorporating structural disorder enables novel devices with unique functionalities as well as multi-functionality. A random system can function as an optical lens, a spectrometer, a polarimeter, and a radio frequency receiver. It is also employed for optical pulse measurement and full-field recovery. Multi-functional disordered photonic devices have been developed for hyperspectral imaging, spatial, and spectral polarimetry. In addition to passive devices, structural disorder has been incorporated to active devices. One prominent example is the random laser, which enables speckle-free imaging, super-resolution spectroscopy, broad tunability of high-power fiber laser, and suppression of lasing instabilities. Disordered devices have low fabrication costs, and their combination with advanced computational techniques may lead to a paradigm shift in photonics and optical engineering.

Broadband Super-Resolution Terahertz Time-Domain Spectroscopy Applied to Gas Analysis

Commercially available Terahertz (THz) Time domain spectroscopy (THz-TDS) apparatus are used in multiple application fields from material science to biology, and even in industry to measure the thickness of a paint layers. Its broad spectral coverage is of interest for air quality monitoring and atmospheric composition analysis. However, gas spectroscopy needs high resolution that the usual approach in THz-TDS is unable to provide. In this letter, we introduce the concept of constraint reconstruction for super-resolution spectroscopy based on the modeling of the spectroscopic rotational lines in a sparse spectrum. It is demonstrated for low-molecular weight molecules in gas phase that typically have spectra containing a small number of narrow lines over a broad spectrum. This alternative approach directly reconstructing the spectra achieved a resolution improvement factor of 10 compared to the best available resolution by the standard THz-TDS data treatment.

Machine learning method puts the “super” in super-resolution spectroscopy

Deep learning network improves feature resolution of infrared imaging method twofold.

Mechanistic Insights into Pore Formation by an α-Pore Forming Toxin: Protein and Lipid Bilayer Interactions of Cytolysin A.

Pore forming toxins (PFTs) are the largest class of bacterial toxins playing a central role in bacterial pathogenesis. They are proteins specifically designed to form nanochannels in the membranes of target cells, ultimately resulting in cell death and establishing infection. PFTs are broadly classified as α- and β-PFTs, depending on secondary structures that form the transmembrane channel. A unique feature about this class of proteins is the drastic conformational changes and complex oligomerization pathways that occur upon exposure to the plasma membrane. A molecular understanding of pore formation has implications in designing novel intervention strategies to combat rising antimicrobial resistance, targeted-cancer therapy, as well as designing nanopores for specialized technologies. Central to unraveling the pore formation pathway is the availability of high resolution crystal structures. In this regard, β-toxins are better understood, when compared with α-toxins whose pore forming mechanisms are complicated by an incomplete knowledge of the driving forces for amphiphatic membrane-inserted helices to organize into functional pores. With the publication of the first crystal structure for an α-toxin, cytolysin A (ClyA), in 2009 we embarked on an extensive multiscale study to unravel its pore forming mechanism. This Account represents the collective mechanistic knowledge gained in our laboratories using a variety of experimental and theoretical techniques which include large scale molecular dynamics (MD) simulations, kinetic modeling studies, single-molecule fluorescence imaging, and super-resolution spectroscopy. We reported MD simulations of the ClyA protomer, oligomeric intermediates, and full pore complex in a lipid bilayer and mapped the conformational transitions that accompany membrane binding. Using single-molecule fluorescence imaging, the conformational transition was experimentally verified by analysis of various diffusion states of membrane bound ClyA. Importantly, we have uncovered a hitherto unknown putative cholesterol binding motif in the membrane-inserted helix of ClyA. Distinct binding pockets for cholesterol formed by adjacent membrane-inserted helices are revealed in MD simulations. Cholesterol appears to play a dual role by stabilizing both the membrane-inserted protomer as well as oligomeric intermediates. Molecular dynamics simulations and kinetic modeling studies suggest that the membrane-inserted arcs oligomerize reversibly to form the predominant transmembrane oligomeric intermediates during pore formation. We posit that this mechanistic understanding of the complex action of α-PFTs has implications in unraveling pore assembly across the wider family of bacterial toxins. With emerging antimicrobial resistance, alternate therapies may rely on disrupting pore functionality or oligomerization of these pathogenic determinants utilized by bacteria, and our study includes assessing the potential for dendrimers as pore blockers.

Efficient generation of relativistic near-single-cycle mid-infrared pulses in plasmas

Ultrashort intense optical pulses in the mid-infrared (mid-IR) region are very important for broad applications ranging from super-resolution spectroscopy to attosecond X-ray pulse generation and particle acceleration. However, currently, it is still difficult to produce few-cycle mid-IR pulses of relativistic intensities using standard optical techniques. Here, we propose and numerically demonstrate a novel scheme to produce these mid-IR pulses based on laser-driven plasma optical modulation. In this scheme, a plasma wake is first excited by an intense drive laser pulse in an underdense plasma, and a signal laser pulse initially at the same wavelength (1 micron) as that of the drive laser is subsequently injected into the plasma wake. The signal pulse is converted to a relativistic multi-millijoule near-single-cycle mid-IR pulse with a central wavelength of ~5 microns via frequency-downshifting, where the energy conversion efficiency is as high as approximately 30% when the drive and signal laser pulses are both at a few tens of millijoules at the beginning. Our scheme can be realized with terawatt-class kHz laser systems, which may bring new opportunities in high-field physics and ultrafast science.

Spectral super-resolution spectroscopy using a random laser

Super-resolution microscopy refers to a powerful set of imaging techniques that overcome the diffraction limit. Some of these techniques, the importance of which was recognized by the 2014 Nobel Prize for chemistry, are based on the concept of image reconstruction by spatially sparse sampling. Here, we introduce the concept of super-resolution spectroscopy based on sparse sampling in the frequency domain, and show that this can be naturally achieved using a random laser source. In its chaotic regime, the emission spectrum of a random laser features sharp spikes at uncorrelated frequencies that are sparsely distributed over the emission bandwidth. These narrow lasing modes probe stochastically the spectral response of a sample, allowing it to be reconstructed with a resolution exceeding that of the spectrometer. We envision that the proposed technique will inspire a new generation of simple, cheap, high-resolution spectroscopy tools with a reduced footprint. Spectral super-resolution spectroscopy is realized by exploiting a random laser that chaotically produces sharply spiked spectral lines, representing a new generation of simple, compact and cost-effective spectroscopy tools.

Revisit of energy transfer upconversion luminescence dynamics—the role of energy migration

Upconversion is a process in which one photon is emitted upon absorption of several photons of lower energy. Potential applications include super resolution spectroscopy, high density data storage, anti-counterfeiting and biological imaging and photo-induced therapy. Upconversion luminescence dynamics has long been believed to be determined solely by the emitting ions and their interactions with neighboring sensitizing ions. Recent research shows that this does not hold for nanostructures. The luminescence time behavior in the nanomaterials is confirmed seriously affected by the migration process of the excitation energy. This new fundamental insight is significant for the design of functional upconversion nanostructures. In this paper we review relevant theoretical and spectroscopic results and demonstrate how to tune the rise and decay profile of upconversion luminescence based on energy migration path modulation.

Precisely Tailoring Upconversion Dynamics via Energy Migration in Core-Shell Nanostructures.

Upconversion emission dynamics have long been believed to be determined by the activator and its interaction with neighboring sensitizers. Herein this assumption is, however, shown to be invalid for nanostructures. We demonstrate that excitation energy migration greatly affects upconversion emission dynamics. “Dopant ions’ spatial separation” nanostructures are designed as model systems and the intimate link between the random nature of energy migration and upconversion emission time behavior is unraveled by theoretical modelling and confirmed spectroscopically. Based on this new fundamental insight, we have successfully realized fine control of upconversion emission time behavior (either rise or decay process) by tuning the energy migration paths in various specifically designed nanostructures. This result is significant for applications of this type of materials in super resolution spectroscopy, high‐density data storage, anti‐counterfeiting, and biological imaging.

Precisely Tailoring Upconversion Dynamics via Energy Migration in Core–Shell Nanostructures

AbstractUpconversion emission dynamics have long been believed to be determined by the activator and its interaction with neighboring sensitizers. Herein this assumption is, however, shown to be invalid for nanostructures. We demonstrate that excitation energy migration greatly affects upconversion emission dynamics. “Dopant ions’ spatial separation” nanostructures are designed as model systems and the intimate link between the random nature of energy migration and upconversion emission time behavior is unraveled by theoretical modelling and confirmed spectroscopically. Based on this new fundamental insight, we have successfully realized fine control of upconversion emission time behavior (either rise or decay process) by tuning the energy migration paths in various specifically designed nanostructures. This result is significant for applications of this type of materials in super resolution spectroscopy, high‐density data storage, anti‐counterfeiting, and biological imaging.

Operating organic light-emitting diodes imaged by super-resolution spectroscopy.

Super-resolution stimulated emission depletion (STED) microscopy is adapted here for materials characterization that would not otherwise be possible. With the example of organic light-emitting diodes (OLEDs), spectral imaging with pixel-by-pixel wavelength discrimination allows us to resolve local-chain environment encoded in the spectral response of the semiconducting polymer, and correlate chain packing with local electroluminescence by using externally applied current as the excitation source. We observe nanoscopic defects that would be unresolvable by traditional microscopy. They are revealed in electroluminescence maps in operating OLEDs with 50 nm spatial resolution. We find that brightest emission comes from regions with more densely packed chains. Conventional microscopy of an operating OLED would lack the resolution needed to discriminate these features, while traditional methods to resolve nanoscale features generally cannot be performed when the device is operating. This points the way towards real-time analysis of materials design principles in devices as they actually operate.