Photochromic materials via sol-gel process

Powders and thin films of photochromic glasses containing AgBr or AgCl microcrystals were synthesized via sol-gel process. Up to 10 wt%, of Ag⁺, bonded with suitable complexing agents, were introduced into the matrix system consisting of xSiO₂-(1 - x)Al₂O₃ (x = 0.7... 1). After drying and heat treatment the AgX microcrystals (X = Cl, Br) were characterized by X-ray diffraction and high-resolution TEM. The photochromic properties were measured using a diode array UV-VIS spectrometer

Sol-gel derived coatings with completely reversible photochromism

Besides the photochromic glasses based on silver halides especially the cuprous halide containing materials are of practical importance. Due to their high absorption coefficient the cuprous halides are particularly suited for the preparation of thin photochromic films. Using the sol-gel technique silicon alkoxide based coating solutions with continuously distributed photoactive components were prepared. From these sols single or multilayer coatings were produced by dipping. The precipitation of the cuprous halide microcrystals as carriers of the photochromic properties of the coatings proceeded during a subsequent heat treatment (temperature range of 100 to 800 °C). Thus it was possible for the first time to produee photochromic coatings with a pronounced darkening and with complete reversibility of the photochromic reactions at room temperature

Optimization Techniques for Semi-Automated 3D Rigid Registration in Multimodal Image-Guided Deep Brain Stimulation

Multimodal image registration is vital in Deep Brain Stimulation (DBS) surgery. DBS treats movement disorders by implanting a neurostimulator device in the brain to deliver electrical impulses. Image registration between computed tomography (CT) and cone beam computed tomography (CBCT) involves fusing images with a specific field of view (FOV) to visualize individual electrode contacts. This contains important information about the location of segmented contacts that can reduce the time required for electrode programming. We performed a semi-automated multimodal image registration with different FOV between CT and CBCT images due to the tiny structures of segmented electrode contacts that necessitate high accuracy in the registration. In this work, we present an optimization workflow for multi-modal image registration using a combination of different similarity metrics, interpolators, and optimizers. Optimization-based rigid image registration (RIR) is a common method for registering images. The selection of appropriate interpolators and similarity metrics is crucial for the success of this optimization-based image registration process.We rely on quantitative measures to compare their performance. Registration was performed on CT and CBCT images for DBS datasets with an image registration algorithm written in Python using the Insight Segmentation and Registration Toolkit (ITK). Several combinations of similarity metrics and interpolators were used, including mean square difference (MSD), mutual information (MI), correlation and nearest neighbors (NN), linear (LI), and B-Spline (SPI), respectively. The combination of a correlation as similarity metric, B-Spline interpolation, and GD optimizer performs the best in optimizing the 3D RIR algorithm, enhancing the visualization of segmented electrode contacts. Patients undergoing DBS therapy may ultimately benefit from this