Terahertz scanning near-field optical microscopy for biomedical detection: Recent advances, challenges, and future perspectives.

Terahertz (THz) radiation is widely recognized as a non-destructive, label-free, and highly- sensitive tool for biomedical detections. Nevertheless, its application in precision biomedical fields faces challenges due to poor spatial resolution caused by intrinsically long wavelength characteristics. THz scanning near-field optical microscopy (THz-SNOM), which surpasses the Rayleigh criterion, offers micrometer and nanometer-scale spatial resolution, making it possible to perform precise bioinspection with THz imaging.

Switchable Pancharatnam-Berry Phases in Heterogeneously Integrated THz Metasurfaces.

The Pancharatnam-Berry (PB) phase has revolutionized the design of metasurfaces, offering a straightforward and robust method for controlling wavefronts of electromagnetic waves. However, traditional metasurfaces have fixed PB phases determined by the orientation of their individual elements. In this study, an innovative structural design and integration scheme is proposed that utilizes vanadium dioxide, a phase-change material, to achieve thermally controlled dynamic PB phase control within the metasurface.

Heterogeneous-Gradient Supercell Metasurfaces for Independent Complex Amplitude Control over Multiple Diffraction Channels.

The ability to achieve independent complex amplitude control across multiple channels can significantly increase the information capacity of photonic devices. Diffraction inherently holds numerous channels, which are good candidates for dense light manipulation in angular space. However, no convenient method is currently available for attaining this.

Thermo-optical tweezers based on photothermal waveguides.

Field-controlled micromanipulation represents a pivotal technique for handling microparticles, yet conventional methods often risk physical damage to targets. Here, we discovered a completely new mechanism for true noncontact manipulation through photothermal effects, called thermal-optical tweezers. We employ a laser self-assembly photothermal waveguide (PTW) for dynamic microparticle manipulation.

The supramolecular synthon behavior within cocrystals of pyrazinamide and alkyl dicarboxylic acids: A perspective from terahertz spectroscopy and quantum chemical calculation.

Pyrazinamide (PZA) is a widely-used anti-tuberculosis pharmaceutical, but its poor solubility prompts us to optimize pharmaceutical performance. Cocrystallization is a promising technique to improve physiochemical properties of active pharmaceutical ingredient (API) by connecting it with cocrystal former (CCF) via intermolecular interactions. Even though a series of alkyl dicarboxylic acids are employed to form cocrystal structures, systematic understanding on the role of intermolecular interactions is still missing.

Highly Responsive and Self-Powered Photodetector Based on PtSe/MoS Heterostructure.

In recent years, 2D materials and their heterostructures have started to offer an ideal platform for high-performance photodetection devices. In this work, a highly responsive, self-powered photodetector based on PtSe/MoS van der Waals heterostructure is demonstrated. The device achieves a noteworthy wide band spectral response from visible (405 nm) range to the near infrared region (980 nm).

Computationally-efficient linear scheme for overlap time-gating spatial frequency domain diffuse optical tomography using an analytical diffusion model.

Time-domain (TD) spatial frequency domain (SFD) diffuse optical tomography (DOT) potentially enables laminar tomography of both the absorption and scattering coefficients. Its full time-resolved-data scheme is expected to enhance performances of the image reconstruction but poses heavy computational costs and also susceptible signal-to-noise ratio (SNR) limits, as compared to the featured-data one. We herein propose a computationally-efficient linear scheme of TD-SFD-DOT, where an analytical solution to the TD phasor diffusion equation for semi-infinite geometry is derived and used to formulate the Jacobian matrices with regard to overlap time-gating data of the time-resolved measurement for improved SNR and reduced redundancy.

In-line imaging and recognition of flip chip fabrication defects by real-time photoacoustic remote sensing system.

Microscopic defects in flip chips, originating from manufacturing, significantly affect performance and longevity. Post-fabrication sampling methods ensure product functionality but lack in-line defect monitoring to enhance chip yield and lifespan in real-time. This study introduces a photoacoustic remote sensing (PARS) system for in-line imaging and defect recognition during flip-chip fabrication.

Performance enhancement of diffuse fluorescence tomography based on an extended Kalman filtering-long short term memory neural network correction model.

To alleviate the ill-posedness of diffuse fluorescence tomography (DFT) reconstruction and improve imaging quality and speed, a model-derived deep-learning method is proposed by combining extended Kalman filtering (EKF) with a long short term memory (LSTM) neural network, where the iterative process parameters acquired by implementing semi-iteration EKF (SEKF) served as inputs to the LSTM neural network correction model for predicting the optimal fluorescence distributions. To verify the effectiveness of the SEKF-LSTM algorithm, a series of numerical simulations, phantom and in vivo experiments are conducted, and the experimental results are quantitatively evaluated and compared with the traditional EKF algorithm. The simulation experimental results show that the proposed new algorithm can effectively improve the reconstructed image quality and reconstruction speed.

Deep-learning approach to stratified reconstructions of tissue absorption and scattering in time-domain spatial frequency domain imaging.

Significance: The conventional optical properties (OPs) reconstruction in spatial frequency domain (SFD) imaging, like the lookup table (LUT) method, causes OPs aliasing and yields only average OPs without depth resolution. Integrating SFD imaging with time-resolved (TR) measurements enhances space-TR information, enabling improved reconstruction of absorption () and reduced scattering () coefficients at various depths.

Aim: To achieve the stratified reconstruction of OPs and the separation between and , using deep learning workflow based on the temporal and spatial information provided by time-domain SFD imaging technique, while enhancing the reconstruction accuracy.

Convolutional Neural Network-Driven Impedance Flow Cytometry for Accurate Bacterial Differentiation.

Impedance flow cytometry (IFC) has been demonstrated to be an efficient tool for label-free bacterial investigation to obtain the electrical properties in real time. However, the accurate differentiation of different species of bacteria by IFC technology remains a challenge owing to the insignificant differences in data. Here, we developed a convolutional neural networks (ConvNet) deep learning approach to enhance the accuracy and efficiency of the IFC toward distinguishing various species of bacteria.

A Microflow Cytometer Enabled by Monolithic Integration of a Microreflector with an Acoustic Resonator.

Current microflow cytometers suffer from complicated fluidic integration and low fluorescence collection efficiency, resulting in reduced portability and sensitivity. Herein, we demonstrated a new flow cell design based on an on-chip monolithically integrated microreflector with a bulk acoustic wave resonator (MBAW). It enables simultaneous 3D particle focusing and fluorescence enhancement without using shear flow.

IR780-based diffuse fluorescence tomography for cancer detection.

IR780 iodide is a commercially available targeted near-infrared contrast agent for in vivo imaging and cancer photodynamic or photothermal therapy, whereas the accumulation, dynamics, and retention of IR780 in biological tissue, especially in tumor is still under-explored. Diffuse fluorescence tomography (DFT) can be used for localization and quantification of the three-dimensional distribution of NIR fluorophores. Herein, a homemade DFT imaging system combined with tumor-targeted IR780 was utilized for cancer imaging and pharmacokinetic evaluation.

Advanced Terahertz Refractive Sensing And Fingerprint Recognition Through Metasurface-Excited Surface Waves.

High-sensitive metasurface-based sensors are essential for effective substance detection and insightful bio-interaction studies, which compress light in subwavelength volumes to enhance light-matter interactions. However, current methods to improve sensing performance always focus on optimizing near-field response of individual meta-atom, and fingerprint recognition for bio-substances necessitates several pixelated metasurfaces to establish a quasi-continuous spectrum. Here, a novel sensing strategy is proposed to achieve Terahertz (THz) refractive sensing, and fingerprint recognition based on surface waves (SWs).

The Label-Free Detection and Identification of SARS-CoV-2 Using Surface-Enhanced Raman Spectroscopy and Principal Component Analysis.

The World Health Organization (WHO) declared in a May 2023 announcement that the COVID-19 illness is no longer categorized as a Public Health Emergency of International Concern (PHEIC); nevertheless, it is still considered an actual threat to world health, social welfare and economic stability. Consequently, the development of a convenient, reliable and affordable approach for detecting and identifying SARS-CoV-2 and its emerging new variants is crucial. The fingerprint and signal amplification characteristics of surface-enhanced Raman spectroscopy (SERS) could serve as an assay scheme for SARS-CoV-2.

An all-silicon design of a high-efficiency broadband transmissive terahertz polarization convertor.

Polarization, a fundamental behavior of electromagnetic waves, holds immense potential across diverse domains such as environmental monitoring, biomedicine, and ocean exploration. However, achieving efficient modulation of terahertz waves with wide operational bandwidth poses significant challenges. Here, we introduce an all-silicon polarization converter designed specifically to operate in the terahertz range of the electromagnetic spectrum.

Subcycle surface electron emission driven by strong-field terahertz waveforms.

The advent of intense terahertz (THz) sources opened a new era when the demonstration of the acceleration and manipulation of free electrons by THz pulses became within reach. THz-field-driven electron emission was predicted to be confined to a single burst due to the single-cycle waveform. Here we demonstrate the confinement of single-cycle THz-waveform-driven electron emission to one of the two half cycles from a solid surface emitter.

Terahertz label-free detection of nicotine-induced neural cell changes and the underlying mechanisms.

Nicotine exposure can lead to neurological impairments and brain tumors, and a label-free and nondestructive detection technique is urgently required by the scientific community to assess the effects of nicotine on neural cells. Herein, a terahertz (THz) time-domain attenuated total reflection (TD-ATR) spectroscopy approach is reported, by which the effects of nicotine on normal and cancerous neural cells, i.e.

Insights into the Semiconductor SERS Activity: The Impact of the Defect-Induced Energy Band Offset and Electron Lifetime Change.

The significant boost in surface-enhanced Raman scattering (SERS) by the chemical enhancement of semiconducting oxides is a pivotal finding. It offers a prospective path toward high uniformity and low-cost SERS substrates. However, a detailed understanding of factors that influence the charge transfer process is still insufficient.

2D shape reconstruction of submillimetric irregular rough particles from speckle pattern in interferometric particle imaging measurement.

Particle shape is a significant feature of irregular particles. The interferometric particle imaging (IPI) technique has been introduced to retrieve submillimetric irregular rough particle shapes, while inevitable experimental noises hinder the convergence of two-dimensional (2D) particle shapes from single speckle patterns. In this work, a hybrid input-output algorithm with shrink-wrap support and oversampling smoothness constraints is utilized to suppress the Poisson noise in IPI measurement and recover accurate 2D shapes of particles.

CGAN-rIRN: a data-augmented deep learning approach to accurate classification of mental tasks for a fNIRS-based brain-computer interface.

Functional near-infrared spectroscopy (fNIRS) is increasingly used to investigate different mental tasks for brain-computer interface (BCI) control due to its excellent environmental and motion robustness. Feature extraction and classification strategy for fNIRS signal are essential to enhance the classification accuracy of voluntarily controlled BCI systems. The limitation of traditional machine learning classifiers (MLCs) lies in manual feature engineering, which is considered as one of the drawbacks that reduce accuracy.