Photoacoustic spectroscopy is a powerful optical biopsy technique that enables rapid tumor diagnosis in situ. It has also been reported that photoacoustic spectroscopy can be used to diagnose pre-malignant tissue based on the chemical differences between healthy and pre-malignant tissues. Since the acoustic signals obtained from tissues in these analyses suffer from minimum damping, photoacoustic spectroscopy can be highly sensitive. This paper focuses on the characterization of a novel multiphoton excited photoacoustic methodology for margining of malignant and premalignant tissues.The two-photon excitation process in tissues using nanosecond laser pulses produces ultrasonic signals that transmit through tissue with minimal attenuation. Additionally, the two-photon excitation process is highly localized since only ballistic photons contribute to the excitation process; thereby eliminating potential absorption events in tissue not of interest (i.e., along the beam path) and increasing the spatial resolution of the diagnostic technique to that achievable via optics. This work characterizes the two-photon excitation process for photoacoustic signal measurements on a model dye. Using gelatin phantoms to mimic real tissues, tissue penetration studies were performed, revealing chemical species as deep as 1.3 cm in the tissue can easily be detected using this methodology. Furthermore, the resolution of this multiphoton excitation process was determined to be as great as 50 µm (near cellular level resolution).

The development and demonstration of a multiphoton photoacoustic imaging technique capable of providing high spatial resolution chemical images of subsurface tissue components as deep as 1.4 cm below the tissue surface is described. By combining multiphoton excitation in the diagnostic window (650 to 1100 nm), with ultrasonic detection of nonradiative relaxation events, it is possible to rapidly reconstruct three-dimensional, chemical specific, images of samples underneath overlying structures as well as chemical species of the same material. Demonstration of this technique for subsurface tissue differentiation is shown, with the ability to distinguish between grade III astrocytoma tissue and adjacent healthy tissue in blind studies. By employing photoacoustic signal detection, the high nonradiative relaxation rates of most biological tissue components (>90% >90% ) and the minimal signal attenuation of the resulting ultrasound compensate for excitation efficiency losses associated with two-photon absorption. Furthermore, the two-photon absorption process results in a highly localized excitation volume (ca., 60  μm 60  μm ). Characterization of the probing depth, spatial resolution, and ability to image through overlying structures is also demonstrated in this paper using tissue phantoms with well-characterized optical scattering properties, mimicking those of tissues.

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The efficiency of renewable energy technologies, such as solar and wind power, has drastically increased over the last decade, whereas the cost of owning these technologies has decreased significantly. As a result, these changes have created a huge demand for energy storage devices, including batteries. Of particular interest is the development and improvement of portable lithium-ion (Li-ion) batteries because of their advantages over traditional battery technologies, including having higher energy density compared to other existing rechargeable batteries and faster charging. Researchers are constantly investigating ways to make Li-ion batteries more efficient and safer. Currently, the Li-ion battery technology is far from perfect and there have been several high-profile reports of failures, including explosions and fires caused during charging, use, and storage. In this regard, Raman spectroscopy has proven to be a powerful tool for research and quality control of Li-ion batteries. In this paper, we present Raman as a technique of choice for quality control of manufacturing processes of Li-ion batteries. We highlight two cases of bulk analysis of lithium compounds using Raman spectroscopy during the quality control procedure of raw materials, and one case of analysis for better manufacturing using Raman imaging microscopy.