Dual-Criteria Decision Analysis by Multiphotonic Effects in Nanostructured ZnO.

Simultaneous interrogation of pump and probe beams interacting in ZnO nanostructures of a two-wave mixing is proposed for dual-path data processing of optical signals by nonlinear optical effects. An enhancement in third-order nonlinear optical properties was exhibited by Al-doped ZnO thin films. Multiphoton absorption and nonlinear refraction were explored by the z-scan technique at 532 nm with nanosecond pulses. The evolution of the optical Kerr effect in the ZnO thin films was analyzed as a function of the incorporation of Al in the sample by a vectorial two-wave mixing method. Electrical and photoconductive effects were evaluated to further characterize the influence of Al in the ZnO solid samples. Potential applications of nonlinear optical parameters for encoding and encrypting information in light can be envisioned.

Multiphotonic Ablation and Electro-Capacitive Effects Exhibited by Candida albicans Biofilms.

This work reports the modification in the homogeneity of ablation effects with the assistance of nonlinear optical phenomena exhibited by C. albicans ATCC 10231, forming a biofilm. Equivalent optical energies with different levels of intensity were irradiated in comparative samples, and significant changes were observed. Nanosecond pulses provided by an Nd:YAG laser system at a 532 nm wavelength in a single-beam experiment were employed to explore the photodamage and the nonlinear optical transmittance. A nonlinear optical absorption coefficient -2 × 10-6 cm/W was measured in the samples studied. It is reported that multiphotonic interactions can promote more symmetric optical damage derived by faster changes in the evolution of fractional photoenergy transference. The electrochemical response of the sample was studied to further investigate the electronic dynamics dependent on electrical frequency, and an electro-capacitive behavior in the sample was identified. Fractional differential calculations were proposed to describe the thermal transport induced by nanosecond pulses in the fungi media. These results highlight the nonlinear optical effects to be considered as a base for developing photothermally activated phototechnology and high-precision photodamage in biological systems.

A Framework for Biosensors Assisted by Multiphoton Effects and Machine Learning.

The ability to interpret information through automatic sensors is one of the most important pillars of modern technology. In particular, the potential of biosensors has been used to evaluate biological information of living organisms, and to detect danger or predict urgent situations in a battlefield, as in the invasion of SARS-CoV-2 in this era. This work is devoted to describing a panoramic overview of optical biosensors that can be improved by the assistance of nonlinear optics and machine learning methods. Optical biosensors have demonstrated their effectiveness in detecting a diverse range of viruses. Specifically, the SARS-CoV-2 virus has generated disturbance all over the world, and biosensors have emerged as a key for providing an analysis based on physical and chemical phenomena. In this perspective, we highlight how multiphoton interactions can be responsible for an enhancement in sensibility exhibited by biosensors. The nonlinear optical effects open up a series of options to expand the applications of optical biosensors. Nonlinearities together with computer tools are suitable for the identification of complex low-dimensional agents. Machine learning methods can approximate functions to reveal patterns in the detection of dynamic objects in the human body and determine viruses, harmful entities, or strange kinetics in cells.