Application of the Photoacoustic Approach in the Characterization of Nanostructured Materials

Size dependent properties of Gd3+-free versus Gd3+-doped carbon dots for bioimaging application

Gd3+- free carbon dots (CDs) were synthesized by one-step solvothermal method using urea, citric acid and 3-(trifluoromethyl)aniline as precursors. Additionally, Gd3+-doped CDs were prepared by incorporating gadolinium chloride (Gd3+ ions) into the synthesis. Size selection of the purified CDs was achieved through filter membranes ranging from 3 kDa to 100 kDa. The chemical composition and optical properties of the obtained samples were characterized by Energy dispersive X-ray (EDX), Fourier-transform infrared spectroscopy (FTIR), Dynamic Light Scattering (DLS), proton relaxation time measurements, Ultraviolet-visible (UV-vis) and fluorescence spectroscopies. A comparative analysis revealed a strong size-dependent behavior in the optical properties of both Gd3+-doped and Gd3+-free CDs. Furthermore, in vitro tests confirmed the non-cytotoxicity of Gd3+-doped CDs, indicating their potential applicability in biomedicine for magnetic resonance imaging (MRI) and red fluorescence-based cell and tissue imaging.

Innovative methods for microplastic characterization and detection: Deep learning supported by photoacoustic imaging and automated pre-processing data

Plastic products' widespread applications and their non-biodegradable nature have resulted in the continuous accumulation of microplastic waste, emerging as a significant component of ecological environmental issues. In the field of microplastic detection, the intricate morphology poses challenges in achieving rapid visual characterization of microplastics. In this study, photoacoustic imaging technology is initially employed to capture high-resolution images of diverse microplastic samples. To address the limited dataset issue, an automated data processing pipeline is designed to obtain sample masks while effectively expanding the dataset size. Additionally, we propose Vqdp2, a generative deep learning model with multiple proxy tasks, for predicting six forms of microplastics data. By simultaneously constraining model parameters through two training modes, outstanding morphological category representations are achieved. The results demonstrate Vqdp2's excellent performance in classification accuracy and feature extraction by leveraging the advantages of multi-task training. This research is expected to be attractive for the detection classification and visual characterization of microplastics.

Frequency-Resolved High-Frequency Broadband Measurement of Acoustic Longitudinal Waves by Laser-Based Excitation and Detection

Optoacoustics is a metrology widely used for material characterisation. In this study, a measurement setup for the selective determination of the frequency-resolved phase velocities and attenuations of longitudinal waves over a wide frequency range (3-55 MHz) is presented. The ultrasonic waves in this setup were excited by a pulsed laser within an absorption layer in the thermoelastic regime and directed through a layer of water onto a sample. The acoustic waves were detected using a self-built adaptive interferometer with a photorefractive crystal. The instrument transmits compression waves only, is low-contact, non-destructive, and has a sample-independent excitation. The limitations of the approach were studied both by simulation and experiments to determine how the frequency range and precision can be improved. It was shown that measurements are possible for all investigated materials (silicon, silicone, aluminium, and water) and that the relative error for the phase velocity is less than 0.2%.

Advances in photoacoustic imaging aided by nano contrast agents: special focus on role of lymphatic system imaging for cancer theranostics

Photoacoustic imaging (PAI) is a successful clinical imaging platform for management of cancer and other health conditions that has seen significant progress in the past decade. However, clinical translation of PAI based methods are still under scrutiny as the imaging quality and clinical information derived from PA images are not on par with other imaging methods. Hence, to improve PAI, exogenous contrast agents, in the form of nanomaterials, are being used to achieve better image with less side effects, lower accumulation, and improved target specificity. Nanomedicine has become inevitable in cancer management, as it contributes at every stage from diagnosis to therapy, surgery, and even in the postoperative care and surveillance for recurrence. Nanocontrast agents for PAI have been developed and are being explored for early and improved cancer diagnosis. The systemic stability and target specificity of the nanomaterials to render its theranostic property depends on various influencing factors such as the administration route and physico-chemical responsiveness. The recent focus in PAI is on targeting the lymphatic system and nodes for cancer diagnosis, as they play a vital role in cancer progression and metastasis. This review aims to discuss the clinical advancements of PAI using nanoparticles as exogenous contrast agents for cancer theranostics with emphasis on PAI of lymphatic system for diagnosis, cancer progression, metastasis, PAI guided tumor resection, and finally PAI guided drug delivery.

Thermal transport properties of porous silicon filled by ionic liquid nanocomposite system

This paper investigates thermal transport in a nanocomposite system consisting of a porous silicon matrix filled with ionic liquid. Firstly, the thermal conductivity and heat capacity of two imidazolium and one ammonium ionic liquids were evaluated using the photoacoustic approach in piezoelectric configuration and differential scanning calorimetry, respectively. Then, the thermal transport properties of the composite system "ionic liquid confined inside porous silicon matrix" were investigated with the photoacoustic approach in gas-microphone configuration. The results demonstrated a significant enhancement of the thermal conductivity of the composite system when compared to the individual components, i.e. (i) more than two times for pristine porous silicon and (ii) more than eight times for ionic liquids. These results provide new paths for innovative solutions in the field of thermal management, particularly in the development of highly efficient energy storage devices.