Μm Standard Deviation Research Articles

Spectrofluorimetric determination of acetone in water samples with solid-phase extraction and a new benzaldehyde derivative

A new method is described for acetone (C(CH3)2O) determination in water samples. The method is based on the reaction with 4-(dimethylamino)benzaldehyde (DMAB) in dimethyl sulfoxide (DMSO) in slightly basic medium, resulting in a highly fluorescent compound with fluorescent wavelengths undisturbed by other common fluorescent compounds. Experimental conditions were optimized (reagents concentrations, reaction time) to reach optimal sensitivity. For the analysis of aqueous samples, a preconcentration step of acetone by solid-phase extraction (SPE) followed by an elution step in DMSO was optimized using Isolute ENV + columns. A highly satisfactory low detection limit of 0.014 μM (0.8 μg L−1) was achieved by combining these two steps, with a linear range from 0.048 to 5 μM and relative standard deviations between 5.7 % and 6.9 %. The protocol was validated on complex real water samples such as river water and wastewater, and our fluorimetric method with DMAB was in good agreement with the reference LC-UV method with DNPH.

Horizontal homing laser for high repetitive inertial fusion

For a commercial laser inertial fusion energy reactor, a highly repetitive operation in which many fuel pellets must be illuminated by laser spots. One of the most efficient ways to achieve this is to control the laser pointing by following fluctuations of the target position. The paper shows the precise control of laser pointing in the horizontal direction with a repetition rate of 10 Hz. Free-falling test pellets of 1 mm in diameter have been illuminated by a laser of 1.6 mm in diameter with cancellation of horizontal fluctuation over 4 mm. The difference in centroids between the laser spot and the illuminated test pellets is 86 μm (standard deviation). This corresponds to a 92% engagement within a 0.15 mm difference, which is a condition for successful nuclear fusions at the Hamamatsu facility. This is the proof-of-principle demonstration of the target-supply tracking and homing laser at a repetition rate of 10 Hz for the actualization of a commercial reactor.

Evaluation of the Marginal Fit of Virgilite Based Lithium Disilicate Ceramic Crowns: An In-Vitro Comparative Study.

Achieving optimal marginal fit is essential for the success of Virgilite Based Lithium Disilicate Ceramic crowns. In this in-vitro study, we compared the marginal fit of Virgilite Based Lithium Disilicate Ceramic crowns using two different CAD/CAM scanners, powder free (System A, Omnicam) and powder based (System B, Blue cam). The mean marginal gap for System A was found to be 63.5 μm (standard deviation ± 10.2 μm), while for System B, it was 57.8 μm (standard deviation ± 9.8 μm). System B demonstrated a slightly superior marginal fit compared to System A, with a difference of 5.7 μm. Within the limitations of this study, it can be concluded that both Omnicam and Blue cam produced clinically acceptable marginal fit of Virgilite Based Lithium Disilicate Ceramic crowns. However, Blue cam exhibited a slightly better marginal fit compared to Omnicam. Further clinical studies are warranted to validate these findings.

Spatial and temporal variability of martian water-ice cloud effective radius in EMIRS thermal infrared observations

New analyses of thermal infrared spectra obtained from the Emirates Mars Infrared Spectrometer (EMIRS) allow for retrieval of water-ice cloud effective radius, reff,ice, in the lower atmosphere of Mars across spatial, seasonal, and daytime diurnal scales. Using a one Martian-year observational dataset the mean retrieved reff,ice is 3.1 μm (standard deviation, σ = 1.5 μm) for an assumed effective variance, νeff,ice = 0.1, and with most individual values between 1 and 10 μm. Sensitivity analyses show the uncertainty associated with reff,ice is largely inversely proportional to water-ice cloud optical depth, τice. As a result, our retrieval is generally applicable to water-ice clouds with τice of at least ∼0.02 to 0.08 at 825 cm−1. Seasonal results show mean reff,ice values of 4.3 μm (σ = 1.9 μm) during aphelion season (Ls = 40°–140°), associated with larger particle sizes in the aphelion cloud belt (ACB), and 2.5 μm (σ = 0.8 μm) during perihelion season (Ls = 225°–360°). Diurnal analyses between roughly 06:00 and 20:00 local true solar time indicate the largest variability occurs in ACB clouds, with effective radii tending to be smaller during midday (zonal-mean reff,ice of 4–5 μm) as compared to the mornings and afternoons (zonal-mean reff,ice of 6–7 μm). Relatively large spatial gradients in reff,ice within the ACB are observed, including a seasonal mean reff,ice of ∼8 μm in the Tharsis region and regions in the southern mid-latitudes with seasonal mean reff,ice of ∼2 μm. Spatial variability in reff,ice tends to be smaller throughout the rest of the year, though with some similar patterns. This includes several time periods between regional dust storms when a low-latitude band of water-ice clouds formed in the afternoons near Tharsis, which grew in both optical depth and effective radius to maxima in the early evenings. Lastly, changes in reff,ice are found to be generally positively correlated with changes in τice and negatively correlated with estimated cloud height, though reff,ice distributions also show this to be a more complex relationship than simple averages might suggest.

Facile Layer Diffusion Technique for Synthesis of Terbium-Based Metal Organic Framework for Fluorometric Sensing of Hydroquinone.

A photoluminescent terbium (III)-based Metal Organic Framework (MOF) was synthesized at room temperature by layer diffusion method utilizing mixed carboxylate linkers (4,4'-oxybis(benzoic acid) and benzene-1,3,5 tricarboxylic acid). Synthesized MOF has crystalline nature and rod-shaped morphology and is thermally stable up to 455°C. The fluorescence emission spectra and theoretical results revealed that carboxylate linkers functioned as sensitizers for Tb(III) photoluminescence which resulted in four distinct emission peaks at 495, 547, 584, and 621nm corresponding to the transitions 5D4 → 7F6, 5D4 → 7F5, 5D4 → 7F4, and 5D4 → 7F3. Using synthesized MOF as fluorescent probe, hydroquinone was detected in aqueous medium with a detection limit of 0.048μM, remarkable recovery (95.6-101.1%), and relative standard deviation less than 2.25%. The quenching phenomenon may be ascribed to electron transfer from synthesized probe to oxidized hydroquinone via carboxylic groups on thesurface of MOF, which is further supported by photo-induced electron transfer mechanism. This study introduces a cheaper, faster, and more accurate method for hydroquinone detection.

Facile immobilization of cholesterol oxidase on Pt,Ru-C nanocomposite and ionic liquid-modified carbon paste electrode for an efficient amperometric free cholesterol biosensing.

In present work, the enzyme cholesterol oxidase (ChOx) was immobilized by Nafion® (Naf) on Pt,Ru-C nanocomposite and an ionic liquid (IL)-modified carbon paste electrode (CPE) in order to create cholesterol biosensor (Naf/ChOx/Pt,Ru-C/IL-CPE). The prepared working electrodes were characterized using scanning electron microscopy-energy-dispersive spectrometry, while their electrochemical performance was evaluated using electrochemical impedance spectroscopic, cyclic voltammetric, and amperometric techniques. Excellent synergism between IL 1-allyl-3-methylimidazolium dicyanamide ([AMIM][DCA]), Pt,Ru-C, and ChOx, as modifiers of CPE, offers the most pronounced analytical performance for improved cholesterol amperometric determination in phosphate buffer solution pH 7.50 at a working potential of 0.60V. Under optimized experimental conditions, a linear relationship between oxidation current and cholesterol concentration was found for the range from 0.31 to 2.46µM, with an estimated detection limit of 0.13µM and relative standard deviation (RSD) below 5.5%. The optimized amperometric method in combination with the developed Naf/ChOx/Pt,Ru-C/IL-CPE biosensor showed good repeatability and high selectivity towards cholesterol biosensing. The proposed biosensor was successfully applied to determine free cholesterol in a human blood serum sample via its enzymatic reaction product hydrogen peroxide despite the presence of possible interferences. The percentage recovery ranged from 99.08 to 102.81%, while RSD was below 2.0% for the unspiked as well as the spiked human blood serum sample. The obtained results indicated excellent accuracy and precision of the method, concluding that the developed biosensor can be a promising alternative to existing commercial cholesterol tests used in medical practice.

Parameterization of polydisperse aerosol optical properties during hygroscopic growth

Aerosol water uptake and the related influence on its optical properties owing to the hygroscopic growth of polydisperse aerosols have a significant effect on air quality and climate. This study develops an analytical parameterization for a single hygroscopic optical parameter and the scattering enhancement factor for polydisperse aerosol sizes. Polydisperse lognormal size distributions for geometric mean diameters of 0.05–1 μm and geometric standard deviations of 1.3–2.5 are considered with real refractive indices between 1.35-1.6. The analytical expression obtained for the optical parameter is compared to Mie theory and reasonable agreements within the size range investigated in this study are observed. Further, our results show that the analytical expression could express polydispersed aerosol optical properties as a function of geometric mean diameter and geometric standard deviation of a lognormal distribution and the refractive index. The obtained analytical expression can be efficiently used for 3D models with a reduced computational burden.

FocusNET: An autofocusing learning‐based model for digital lensless holographic microscopy

This paper reports on a convolutional neural network (CNN) – based regression model, called FocusNET, to predict the accurate reconstruction distance of raw holograms in Digital Lensless Holographic Microscopy (DLHM). This proposal provides a physical-mathematical formulation to extend its use to different DLHM setups than the optical and geometrical conditions utilized for recording the training dataset; this unique feature is tested by applying the proposal to holograms of diverse samples recorded with different DLHM setups. Additionally, a comparison between FocusNET and conventional autofocusing methods in terms of processing times and accuracy is provided. Although the proposed method predicts reconstruction distances with approximately 54 µm standard deviation, accurate information about the samples in the validation dataset is still retrieved. When compared to a method that utilizes a stack of reconstructions to find the best focal plane, FocusNET performs 600 times faster, as no hologram reconstruction is needed. When implemented in batches, the network can achieve up to a 1200-fold reduction in processing time, depending on the number of holograms to be processed. The training and validation datasets, and the code implementations, are hosted on a public GitHub repository that can be freely accessed.

20 dB improvement utilizing custom-designed 3D-printed terahertz horn coupler.

Terahertz band is envisaged to provide substantially higher capacity and much lower latency for wireless communications in contrast to microwave frequencies. Moving to higher frequencies comes with its own unique challenges to be addressed, such as poor coupling efficiency from free space into and out of planar air-core waveguides. Here, we propose a framework for rapid design and low-cost fabrication of terahertz horn couplers. The horn couplers are first designed by maximizing the field overlap integral on apex and aperture interfaces, then fabricated exploiting 3D printing technique, and finally sputtered with a thin layer of gold. A 28~μm standard deviation of the surface roughness height of the 3D printed horn couplers is calculated. Experimental demonstrations show that the proposed horn coupler improves the transmittance of a hybrid photonic crystal waveguide by 20 dB in comparison with the previous pinhole-based coupling configuration. This work provides a fast, convenient and economical approach for design and fabrication of customized couplers for any waveguide size, with a cost of only 5% of commercially available counterparts, and could be integrated in 3D-printed terahertz devices during fabrication.

Demarcation Line Depth in Epithelium-Off Corneal Cross-Linking Performed at the Slit Lamp.

We aimed to evaluate the depth of the demarcation line following accelerated epithelium-off corneal cross-linking (A-CXL) performed at the slit lamp with the patient sitting in an upright position. Twenty-three eyes from twenty patients, undergoing epi-off A-CXL (9 mW/cm2 for 10 min) using a CXL device at the slit lamp in the upright position. Demarcation line depth was assessed at 1 month after the procedure using anterior segment optical coherence tomography (AS-OCT) and specialized software. Surgery was uneventful in all cases. The average postoperative demarcation line depth achieved was 189.4 µm (standard deviation: 58.67 µm). The demarcation line depth achieved with patients sitting upright, receiving CXL at the slit lamp, is similar to published data on CXL performed in the supine position, suggesting that demarcation line depth is not dependent on patient orientation during CXL.

Sub-millimetre light detection and ranging using perovskites

Light detection and ranging (LiDAR) technology is an active remote-sensing system used in autonomous vehicles, machine vision and augmented reality. Improvements in the speed and signal-to-noise ratio of photodetectors are needed to meet these demanding ranging applications. Silicon electronics have been the principal option for LiDAR photodetectors in the range of 850–950 nm. However, its indirect bandgap leads to a low absorption coefficient in the near-infrared region, as well as a consequent trade-off between speed and efficiency. Here we report solution-processed lead–tin binary perovskite photodetectors that have an external quantum efficiency of 85% at 850 nm, dark current below 10–8 A cm–2 and response time faster than 100 ps. The devices are fabricated using self-limiting and self-reduced tin precursors that enable perovskite crystallization at the desired stoichiometry and prevent the formation of interfacial defects with the hole transport layer. The approach removes oxygen from the solution, converts Sn4+ to Sn2+ through comproportionation, and leaves neither metallic tin nor SnOx residues. To illustrate the potential of these solution-processed perovskite photodetectors in LiDAR, we show that they can resolve sub-millimetre distances with a typical 50 µm standard deviation.

Experimental investigation and characterization of NiTinol shape memory alloy during wire electrochemical machining

NiTinol-based microstructures have piqued interest in a variety of industrial applications. Nonetheless, due to material features and characteristics, micromachining of NiTinol shape memory alloy (SMA) offers a significant problem due to a detrimental combination of shape memory effect and super-elasticity. In this paper, an investigation into the wire electrochemical machining (WECM) of NiTinol SMA at a low concentration of 0.1 M H2SO4 aqueous acidic electrolyte with effect of small amplitude at low-frequency PZT vibration-assisted axial nozzle jet flushing is presented. During the machining process, initially, the effect of most influencing WECM process parameters i.e. electrolyte flow rate, tool PZT amplitude and frequency, electrolyte temperature during micromachining of NiTinol SMA was studied on machining characteristics for microslit fabrication. Additionally, the effect of pulse voltage, pulse frequency, pulse width and, the wire feed rate was also investigated during machining on micro slit width to understand the benefit of WECM on NiTinol SMA machining in sequential order. Furthermore, after several experiments for controlled machining conditions, finally, NiTinol SMA - based homogeneous minimum slit width of 110 μm with 0.57 μm standard deviation were obtained with 120 μm thick NiTinol sheet at a 100 μm initial inter-electrode gap. The characteristics of NiTinol SMA were analyzed before and after machining using scanning electron microscopy (SEM), and energy-dispersive X-ray (EDX), X-ray diffraction (XRD) tests. Also, dissolution behavior of NiTinol SMA in 0.1 M H2SO4 aqueous acidic electrolyte was studied. The surface roughness Ra was observed as 0.108 μm on the machined surface confirming a uniform dissolution during WECM.

The incorporation of environmentally derived 87Sr/86Sr and Sr/Ca in early otolith formation of Chinook salmon

AbstractEffective species management often requires understanding patterns of movement and habitat use. A common approach in identifying where individuals reside relies upon chemical tracers from the environment that are incorporated into an individual's tissues. For fish, isotopes in their otoliths, specifically the portion of their otolith formed during their larval stage, have been used to identify the natal origin. Complicating this work, however, is the fact that during this life stage, there is a shift in the source of isotopes deposited onto the growing otolith from maternally to environmentally derived. The objective of this study was to identify the portion of the otolith representing this transition to environmentally derived isotopes so as to accurately investigate questions of natal origin for a threatened population of fall Chinook salmon (Oncorhynchus tshawytscha). We exposed developing larvae to four treatments that differed in terms of their water strontium isotope ratio (87Sr/86Sr) and used change‐point analysis of otolith 87Sr/86Sr and strontium to calcium ratio (Sr/Ca) to identify the otolith radius corresponding to the transition to environmentally derived isotopes. Our results indicated this transition occurred, on average, at 132 μm (87Sr/86Sr; ±50 μm standard deviation) and 127 μm (Sr/Ca; ±29 μm) from the otolith core, which corresponded to the developmental time between hatching and exogenous feeding. A substantial proportion of our otoliths (i.e., 61%) did not show convergence between otolith and water 87Sr/86Sr by the end of the 113‐day experiment, which was likely due to the dietary contribution of marine‐based feed. Therefore, we were unable to recommend an otolith radius to target for the purposes of reconstructing natal origin apart from being beyond approximately 130 μm.

Using machine learning to predict dimensions and qualify diverse part designs across multiple additive machines and materials

One of the most critical decisions in a factory is whether to accept or reject manufactured parts, where the acceptance criteria usually includes part geometry and the presence of defects. Additive manufacturing (AM) produces parts having geometric defects that depend upon the part size and shape as well as manufacturing process parameters. There is a need to develop methods that can effectively predict these defects and aid the part qualification process. This study addresses two problems: first, the prediction of part geometry; and second, the use of these predictions to qualify parts. To mimic an AM production scheme, we produced 405 parts across nine builds, using two machines, three polymer materials, and two different arrangements of part designs within a build. For each of three part designs, we identified and measured five critical features per part for a total of 2025 feature measurements. We developed a data model that describes design information and manufacturing process information using both continuous and categorical variables and used this data to train a support vector regression (SVR) machine learning (ML) model to predict part geometry. The models are trained on a random selection of the 405 parts and predict the geometry of unsampled parts with high accuracy. The SVR models predict feature geometry to within 53 µm, which is close to the manufacturer reported process repeatability and much smaller than the 180 µm standard deviation of the data. An exploration of the data model shows that categorical information about the part design significantly improves the model prediction compared to models that do not capture this information. In the second part of the study, we leverage the same data model to develop a part qualification tool and explore three strategies for accepting or rejecting parts based on ML predictions. The strategies are based on: SVR feature geometry predictions and tunable acceptance thresholds, direct feature classifications with a part acceptance threshold, and direct part classifications. In all cases, the only model inputs are the manufacturing parameters and feature descriptors. The SVR-based part qualification strategy achieves the highest accuracy at 81% and is more data efficient than the other approaches. The research demonstrates the utility of ML in predicting AM part geometry and accurately classifying parts, and provides opportunities to better understand geometry variability in production AM.

Industrially microfabricated ion trap with 1 eV trap depth

Scaling trapped-ion quantum computing will require robust trapping of at least hundreds of ions over long periods, while increasing the complexity and functionality of the trap itself. Symmetric three-dimensional (3D) structures enable high trap depth, but microfabrication techniques are generally better suited to planar structures that produce less ideal conditions for trapping. We present an ion trap fabricated on stacked eight-inch wafers in a large-scale micro-electro-mechanical system microfabrication process that provides reproducible traps at a large volume. Electrodes are patterned on the surfaces of two opposing wafers bonded to a spacer, forming a 3D structure with 2.5 μm standard deviation in alignment across the stack. We implement a design achieving a trap depth of 1 eV for a 40Ca+ ion held at 200 μm from either electrode plane. We characterize traps, achieving measurement agreement with simulations to within ±5% for mode frequencies spanning 0.6–3.8 MHz, and evaluate stray electric field across multiple trapping sites. We measure motional heating rates over an extensive range of trap frequencies, and temperatures, observing 40 phonons/s at 1 MHz and 185 K. This fabrication method provides a highly scalable approach for producing a new generation of 3D ion traps.

No optical coherence tomography changes in premanifest Huntington's disease mutation carriers far from disease onset

BackgroundSpectral‐domain optical coherence tomography (OCT) may detect retinal changes as a biomarker in neurodegenerative diseases like manifest Huntington's disease (HD). We investigate macular retinal layer thicknesses in a premanifest HD (pre‐HD) cohort and healthy controls (HC).MethodsPre‐HD mutation carriers underwent standardized ratings and a preset macular OCT scan. Thickness values were determined for each sector of all macular retinal layers, the mean of all sectors and the mean of the inner ring (IR, 3 mm) after segmentation (Heyex segmentation batch). HC were retrospectively included from an existing database. The IR thickness of the ganglion cell layer (GCL), retinal nerve fiber layer (RNFL), GCL + inner plexiform layer (GCIPL), and total retina were included in the exploratory correlation analyses with paraclinical ratings and compared to HC.ResultsThe analyses comprised n = 24 pre‐HD participants (n = 10 male, n = 14 female) and n = 38 HC (n = 14 male, n = 24 female). Retinal layer parameters did not correlate with paraclinical ratings. Expected correlations between established HD biomarkers were robust. The IR thicknesses of the GCL, GCIPL, and total retina did not differ between pre‐HD and HC. The IR thickness of the RNFL was significantly higher in pre‐HD participants (pre‐HD: 23.22 μm (standard deviation 2.91), HC: 21.26 μm (1.90), p = .002).DiscussionIn this cross‐sectional cohort of genetically determined pre‐HD participants, neurodegenerative features were not detected with retinal layer segmentation. Since our pre‐HD collective was more than 16 years before disease onset, OCT may not be sensitive enough to detect early changes.

Improving the dimensional accuracy of 3D x-ray microscopy data

X-ray microscopy instruments have the unique ability to achieve nondestructive imaging with higher spatial resolutions than traditional x-ray computed tomography (CT) systems. This unique ability is of interest to industrial quality control entities, as they deal with small features in precision manufactured parts (with tolerances in the order of ±25 µm or better). Since many of today’s technology and manufacturing companies demand increasingly higher levels of precision, accuracy, and reliability for dimensional measurements on feature sizes that are much smaller than 5 mm, it would be ideal to further expand the imaging capabilities of x-ray microscopy to the field of precision metrology. To address such demand, this paper describes the development of a measurement workflow, through a package consisting of hardware and software, to improve the accuracy of dimensional data obtained with 3D x-ray microscopes (XRMs)—also known as sub-micrometer CT systems. The measurement workflow, called Metrology Extension (MTX), was designed to adjust and configure the XRM instrument work-zone to perform dimensional measurement tasks. The main adjustments of an XRM instrument through the MTX workflow, which must be implemented before scanning parts of interest for dimensional evaluation, include applying a distortion map correction on the image projections produced by the x-ray detector and a voxel scale correction. The main purpose of this article is to present, evaluate, and analyze the experimental results of various measurement tests to verify the metrological performance of several XRM systems operating with the MTX workflow. The main results show that these systems can produce repeatable and reproducible measurements, with repeatability standard deviations of the order of 0.1 μm and reproducibility standard deviations of less than 0.5 μm. In addition, coordinate-based 3D XRM measurements produce dimensional accuracies comparable to those offered by high-precision tactile coordinate measurement machines (with deviations within the range of ±0.95 µm). Therefore, once the MTX workflow is executed, XRM instruments can be used to measure small volumes, in the order of (5 mm)3 or less, with improved dimensional accuracy.

Radiological safety during sodium diuranate dissolution process

The article presents an overview of the occupational radiation protection aspects of experimental sodium diuranate transferring and handling processes required for refining utilization. The health physics aspects and associated monitoring programs necessary to adequately measure and control radiological exposures to workers during the process is described here. A particle size distribution study was also carried out and estimated the activity median aerodynamic diameter (AMAD) for the process. The AMAD varied from 4.6 to 7.7 μm and geometric standard deviation ranged from 1.9 to 2.8. Obtained data serve the purpose of comparison for formulating a detailed radiological safety protocol during regular operation.

Influence of process parameters on particle characteristics using a combined pressure-swirl-gas atomizer

Abstract This paper summarizes the latest results in the development of a combined pressure-swirl-gas atomizer. The main goals of this investigation are to characterize the generated metal powders in terms of spray pattern and particle size distribution. With the combined pressure-swirl-gas atomizer it is possible to create 150 kg h – 1 of tin powder with mass medians between 30 and 110 μm (tin alloys) and geometric standard deviations below 1.9 with a nitrogen consumption of 100 kg h – 1. Gas flow and melt mass flow can be varied independently of each other, while their characteristic ratio of mass flows can be held below 0.7, which opens new potential for low gas consumption in gas atomization. The experiments were conducted with water and tin melts as model fluids. The comparison of the dimensionless numbers shows that the model experiments are comparable and basically extendable to other melts as long as the material characteristics allow this.

L-cysteine capped silver nanoparticles as chiral recognition sensor for ketoprofen enantiomers.

A simple, inexpensive but effective approach for visual chiral recognition of ketoprofen enantiomers was developed using L-cysteine capped silver nanoparticles (L-Cys-AgNPs) as a colorimetric sensor. Upon the addition of R-ketoprofen to L-Cys-AgNPs, rapid aggregation occurred, and the solution changed color from yellow to green. However, the presence of S-ketoprofen did not induce any color change. The results were characterized using UV-Vis, FESEM, FT-IR, SERS, and zeta potential measurements. The chiral assay described in this work is easily distinguished with the naked eyes or using a UV-Vis spectrometer. The sensor revealed a good linear response to ketoprofen enantiomers in the concentration range of 8.33-33.3μM with a detection limit of 4.52 μM and relative standard deviation of 3.73%. The proposed method was utilized for the determination of ketoprofen racemic mixtures in water samples and commercial tablets. The method excels by its simplicity, low cost, and good availability of materials.