Flow-Through Atmospheric Pressure-Atomic Layer Deposition Reactor for Thin-Film Deposition in Capillary Columns.

We demonstrate the development of a new atmospheric pressure-atomic layer deposition(AP-ALD) system to coat the inner walls of capillary columns for gas chromatography (GC). Unlike traditional ALD, this reactor operates at near-atmospheric pressure and addresses the challenges of depositing thin films inside capillaries, which include long pump down times, deposition in high-aspect-ratio materials, and temperature control. We show ALD of alumina in 5 and 12 m capillaries (0.53 mm ID) via sequential half reactions of trimethylaluminum and water. Our system yields pinhole-free, uniform thin films. It includes small witness chambers for witness silicon shards before and after the capillary. An engineering flow/transport analysis of the device is provided. Our ALD alumina thin films are characterized by spectroscopic ellipsometry (SE), X-ray photoelectron spectroscopy, transmission electron microscopy (TEM), and energy-dispersive X-ray spectroscopy. Alumina film growth achieved is 1.4-1.5 Å/cycle, which is consistent with previously reported results. Film thickness measurements by SE on witness shards of silicon and by TEM at both ends of the capillary are in good agreement. A capillary column coated with alumina is used to separate different gases by GC, although the retention times of gases are essentially the same as with an untreated fused silica capillary. This successful deposition of ALD alumina in long capillaries opens the door for other possible ALD coatings, including hybrid organic-inorganic coatings, using the 450+ ALD precursors available today.

Polyallylamine as an Adhesion Promoter for SU-8 Photoresist.

Resist lithography is an important microfabrication technique in the electronics industry. In this, patterns are transferred by irradiation onto a photosensitive polymer. SU-8 has emerged as a favorite photoresist for High Aspect Ratio (HAR) lithography, showing high chemical and mechanical stability and biocompatibility. Unfortunately, its poor adhesion to substrates is a drawback, with possible solutions being the use of low-viscosity SU-8, surface modification with a low molecular weight adsorbate like hexamethyldisilazane (HMDS), or a commercial adhesion promotion reagent. However, HMDS and the commercial reagent require surface dehydration and/or curing, and a modified form of SU-8 is not always desirable. Here, we demonstrate the use of a water-soluble, amine-containing polymer, polyallylamine (PAAm), which spontaneously adsorbs to silica surfaces, as a simple, easy-to-apply, and reactive adhesion promoter for SU-8. Conditions for the use of PAAm are explored, and the resulting materials are characterized by X-ray photoelectron spectroscopy (XPS), spectroscopic ellipsometry (SE), and wetting.

Targeted Subcutaneous Vibration With Single-Neuron Electrophysiology As a Novel Method for Understanding the Central Effects of Peripheral Vibrational Therapy in a Rodent Model.

Very little is known about the effects of whole body vibration on the supraspinal central nervous system. Though much clinical outcome data and mechanistic data about peripheral neural and musculoskeletal mechanisms have been explored, the lack of central understanding is a barrier to evidence-based, best practice guidelines in the use of vibrational therapy. Disparate methods of administration render study to study comparisons difficult. To address this lack of uniformity, we present the use of targeted subcutaneous vibration combined with simultaneous in vivo electrophysiological recordings as a method of exploring the central effects of peripheral vibration therapy. We used implanted motors driven by both Grass stimulators and programmed microcontrollers to vary frequency and location of stimulation in an anesthetized in vivo rat model while simultaneously recording firing rate from gamma-aminobutyric acid (GABA) neurons in the ventral tegmental area. We show that peripheral vibration can alter GABA neuron firing rate in a location- and frequency-dependent manner. We include detailed schematics and code to aid others in the replication of this technique. This method allows for control of previous weaknesses in the literature including variability in body position, vibrational intensity, node and anti-node interactions with areas of differing mechanoreceptor densities, and prefrontal cortex influence.

Using pattern recognition entropy to select mass chromatograms to prepare total ion current chromatograms from raw liquid chromatography-mass spectrometry data.

The total ion current chromatogram (TICC) obtained by liquid-chromatography-mass spectrometry (LC-MS) is often extremely complex and 'noisy' in appearance, particularly when an electrospray ionization source is used. Accordingly, meaningful qualitative and quantitative information can be obtained in LC-MS by data mining processes. Here, one or more higher-quality mass chromatograms can be identified/extracted/isolated and combined to form a TICC, wherein much of the background mass noise is eliminated, and quantitative data for chromatographic peaks can be obtained. Pattern Recognition Entropy (PRE) is a new application of Shannon's statistical concept of entropy. PRE is both a pattern recognition tool and a summary statistic that can be used to identify information-containing mass chromatograms, where higher quality data (higher signal-to-noise mass chromatograms) usually have lower PRE values. Reduced TICCs are obtained by first calculating the PRE values of the component mass chromatograms. A plot of PRE value vs. m/z for the mass chromatograms is then generated, and the resulting band of PRE values is fit to a piecewise spline polynomial. The distribution of the differences between the individual PRE values and the spline fit is then used to select 'good' mass chromatograms. For the data set considered herein, best results were obtained with a threshold of 0.5 standard deviations below the average value (value of the spline). PRE reduces the number of component mass chromatograms significantly (by an order of magnitude) and at the same time preserves most of the chemical information that is collectively in them. It can also distinguish between mass chromatograms of chemically similar species. PRE is arguably a less computationally intensive alternative to the widely used CODA algorithm for variable reduction. It produces reduced TICCs of comparable if not higher quality, and it requires only a single user input for variable selection. Reduced TICCs generated by PRE can be smoothed to further improve their signal-to-noise ratios.