Towards a Fully Automated Scanning Probe Microscope for Biomedical Applications

The increase in capabilities of Scanning Probe Microscopy (SPM) has resulted in a parallel increase in complexity that limits the use of this technique outside of specialised research laboratories. SPM automation could substantially expand its application domain, improve reproducibility and increase throughput. Here, we present a bottom-up design in which the combination of positioning stages, orientation, and detection of the probe produces an SPM design compatible with full automation. The resulting probe microscope achieves sub-femtonewton force sensitivity whilst preserving low mechanical drift (2.0±0.2 nm/min in-plane and 1.0±0.1 nm/min vertically). The additional integration of total internal reflection microscopy, and the straightforward operations in liquid, make this instrument configuration particularly attractive to future biomedical applications.

Developments and Recent Progresses in Microwave Impedance Microscope

Microwave impedance microscope (MIM) is a near-field microwave technology which has low emission energy and can detect samples without any damages. It has numerous advantages, which can appreciably suppress the common-mode signal as the sensing probe separates from the excitation electrode, and it is an effective device to represent electrical properties with high spatial resolution. This article reviews the major theories of MIM in detail which involve basic principles and instrument configuration. Besides, this paper summarizes the improvement of MIM properties, and its cutting-edge applications in quantitative measurements of nanoscale permittivity and conductivity, capacitance variation, and electronic inhomogeneity. The relevant implementations in recent literature and prospects of MIM based on the current requirements are discussed. Limitations and advantages of MIM are also highlighted and surveyed to raise awareness for more research into the existing near-field microwave microscopy. This review on the ongoing progress and future perspectives of MIM technology aims to provide a reference for the electronic and microwave measurement community.

Instrumental Configuration of Electromagnetic Thermography and Optical Thermography

Electromagnetic thermography and optical thermography are both important non-destructive testing (NDT) methods that have been widely used in the fields of modern aerospace, renewable energy, nuclear industry, etc. The excitation modes are crucial whose performances have a decisive effect on the detection results. Previous studies mainly focused on the physics mechanism, applications, and signal processing algorithms. However, the instrument configuration is rarely presented. This paper is to introduces the recently designed excitation sources of electromagnetic thermography and optical thermography detection systems, respectively. These instruments involved L-shaped and Shuttle-shaped sensor structures for electromagnetic thermography and multi-modes excitation for optical thermography. Besides, the topologies and operating principles are shown in detail. Experimental results are carried out to verify the practicability and reliability of the proposed systems.

Deep Learning Methods On Neutron Scattering Data

Recently, by using deep learning methods, a computer is able to surpass or come close to matching human performance on image analysis and recognition. This advanced methods could also help extracting features from neutron scattering experimental data. Those data contain rich scientific information about structure and dynamics of materials under investigation. Deep learning could help researchers better understand the link between experimental data and materials properties. Moreover,it could also help to optimize neutron scattering experiment by predicting the best possible instrument configuration. Among all possible experimental methods, we begin our study on the small-angle neutron scattering (SANS) data and by predicting the structure geometry of the sample material at an early stage. This step is a keystone to predict the experimental parameters to properly setup the instrument as well as the best measurement strategy. In this paper, we propose to use transfer learning to retrain a convolutional neural networks (CNNs) based pre rained model to adapt the scattering images classification, which could predict the structure of the materials at an early stage in the SANS experiment. This deep neural network is trained and validated on simulated database, and tested on real scattering images.

Transformation of aqueous protein attenuated total reflectance infra-red absorbance spectroscopy to transmission

Infrared (IR) spectroscopy is increasingly being used to probe the secondary structure of proteins, especially for high-concentration samples and biopharmaceuticals in complex formulation vehicles. However, the small path lengths required for aqueous protein transmission experiments, due to high water absorbance in the amide I region of the spectrum, means that the path length is not accurately known, so only the shape of the band is ever considered. This throws away a dimension of information. Attenuated total reflectance (ATR) IR spectroscopy is much easier to implement than transmission IR spectroscopy and, for a given instrument and sample, gives reproducible spectra. However, the ATR-absorbance spectrum varies with sample concentration and instrument configuration, and its wavenumber dependence differs significantly from that observed in transmission spectroscopy. In this paper, we determine, for the first time, how to transform water and aqueous protein ATR spectra into the corresponding transmission spectra with appropriate spectral shapes and intensities. The approach is illustrated by application to water, concanavalin A, haemoglobin and lysozyme. The transformation is only as good as the available water refractive index data. A hybrid of literature data provides the best results. The transformation also allows the angle of incidence of an ATR crystal to be determined. This opens the way to using both spectral shape and spectra intensity for protein structure fitting.

Polarimetric imaging mode of VLT/SPHERE/IRDIS

Context. Polarimetric imaging is one of the most effective techniques for high-contrast imaging and for the characterization of protoplanetary disks, and it has the potential of becoming instrumental in the characterization of exoplanets. The Spectro-Polarimetric High-contrast Exoplanet REsearch (SPHERE) instrument installed on the Very Large Telescope (VLT) contains the InfraRed Dual-band Imager and Spectrograph (IRDIS) with a dual-beam polarimetric imaging (DPI) mode, which offers the capability of obtaining linear polarization images at high contrast and resolution. Aims. We aim to provide an overview of the polarimetric imaging mode of VLT/SPHERE/IRDIS and study its optical design to improve observing strategies and data reduction. Methods. For H-band observations of TW Hydrae, we compared two data reduction methods that correct for instrumental polarization effects in different ways: a minimization of the “noise” image (Uϕ), and a correction method based on a polarimetric model that we have developed, as presented in Paper II of this study. Results. We use observations of TW Hydrae to illustrate the data reduction. In the images of the protoplanetary disk around this star, we detect variability in the polarized intensity and angle of linear polarization that depend on the pointing-dependent instrument configuration. We explain these variations as instrumental polarization effects and correct for these effects using our model-based correction method. Conclusions. The polarimetric imaging mode of IRDIS has proven to be a very successful and productive high-contrast polarimetric imaging system. However, the instrument performance is strongly dependent on the specific instrument configuration. We suggest adjustments to future observing strategies to optimize polarimetric efficiency in field-tracking mode by avoiding unfavorable derotator angles. We recommend reducing on-sky data with the pipeline called IRDAP, which includes the model-based correction method (described in Paper II) to optimally account for the remaining telescope and instrumental polarization effects and to retrieve the true polarization state of the incident light.