MgB 2 ultrathin films fabricated by hybrid physical chemical vapor deposition and ion milling
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An on-chip spectroscopic sensor includes a tunable diode laser. A laser driver for drives the tunable diode laser. An analyte test cavity receives a chemical sample and exposes the received chemical sample to light from the tunable diode laser. An optical detector detects light emerging from the analyte test cavity as a result of the laser exposure. A spectral analyzer determines a spectrum of the emerging light, matches and removes one or more known optical fringe patterns from the determined spectrum, and determines a composition or concentration of the chemical sample from the optical fringe pattern-removed spectrum.
A rapid, scalable methodology for graphene dispersion and concentration with a polymer-organic solvent medium, as can be utilized without centrifugation, to enhance graphene concentration.
A rapid, scalable methodology for graphene dispersion and concentration with a polymer-organic solvent medium, as can be utilized without centrifugation, to enhance graphene concentration.
A tunable diode laser absorption spectroscopy device includes a tunable diode laser. A laser driver is configured to drive the diode laser and ramp it within a particular frequency range. An analyte gas container, a reference gas container, and a fringe generating device are configured to receive the laser therethrough. An optical detector is configured to detect the laser after it has passed through the analyte gas container and/or the reference gas container, and the in-line fringe generating device. An acquisition card is configured to sample an output of the optical detector. A spectral analyzer is configured to receive output data from the acquisition card, determine a spectrum of the output data, decouple the fringe spectrum from the measured spectrum, calibrate the spectrum based on an expected ideal spectrum of both the fringe and reference gas, and determine a composition of the analyte based on the calibrated spectrum.
A rapid, scalable methodology for graphene dispersion and concentration with a polymer-organic solvent medium, as can be utilized without centrifugation, to enhance graphene concentration.
An on-chip spectroscopic sensor includes a tunable diode laser. A laser driver for drives the tunable diode laser. An analyte test cavity receives a chemical sample and exposes the received chemical sample to light from the tunable diode laser. An optical detector detects light emerging from the analyte test cavity as a result of the laser exposure. A spectral analyzer determines a spectrum of the emerging light, matches and removes one or more known optical fringe patterns from the determined spectrum, and determines a composition or concentration of the chemical sample from the optical fringe pattern-removed spectrum.
A method is provided for Fourier domain dynamic correction of optical fringes in a laser spectrometer. The method includes Fourier transforming a background spectrum contaminated with the optical fringes to obtain baseline fringes in a frequency domain. The method includes partitioning the baseline fringes in the frequency domain to obtain partitioned baseline fringes. The method includes reconstructing the partitioned baseline fringes as separate spectra. The method includes constructing a fitting model to approximate the background spectrum by assigning a first and a second free parameter to each of partitioned baseline fringe components to respectively allow for drift and amplitude adjustments during a fitting of the fitting model. The method includes applying the fitting model to a newly acquired spectrum to provide an interpretation of the newly acquired spectrum having a reduced influence of spectral contamination on concentration retrieval.
In one aspect of the invention, a dye sensitized solar cell has a counter-electrode including carbon-titania nanocomposite thin films made by forming a carbon-based ink; forming a titania (TiO 2 ) solution; blade-coating a mechanical mixture of the carbon-based ink and the titania solution onto a substrate; and annealing the blade-coated substrate at a first temperature for a first period of time to obtain the carbon-based titania nanocomposite thin films. In certain embodiments, the carbon-based titania nanocomposite thin films may include solvent-exfoliated graphene titania (SEG-TiO 2 ) nanocomposite thin films, or single walled carbon nanotube titania (SWCNT-TiO 2 ) nanocomposite thin films.
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The present invention is directed at intercalative metal oxide/conductive polymer composites suitable for use as electrode materials for rechargeable batteries. The composites can be prepared by agitation of the metal oxide and the conductive polymer in aqueous media. The present invention is also directed at a sodium rich layered manganese oxide hydrate prepared by annealing manganese (II, III) oxide and sodium hydroxide. The sodium rich manganese (III, IV) oxide so formed indicates an enhanced capacity for Na-ion storage suitable for the use of electrode materials for aqueous energy storage.
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In one aspect of the invention, a dye sensitized solar cell has a counter-electrode including carbon-titania nanocomposite thin films made by forming a carbon-based ink; forming a titania (TiO 2 ) solution; blade-coating a mechanical mixture of the carbon-based ink and the titania solution onto a substrate; and annealing the blade-coated substrate at a first temperature for a first period of time to obtain the carbon-based titania nanocomposite thin films. In certain embodiments, the carbon-based titania nanocomposite thin films may include solvent-exfoliated graphene titania (SEG-TiO 2 ) nanocomposite thin films, or single walled carbon nanotube titania (SWCNT-TiO 2 ) nanocomposite thin films.
Abstract not provided.
Abstract not provided.
Imbalanced learning attracts great attention in various research fields. Existing literature-reported methodologies in imbalanced learning have shown drawbacks including over-generation or noisy/wrong samples generations. This paper presents EE-SMOTE, an oversampling technique based on information entropy, to support the imbalance classifications. Specifically, we propose a metric, Eigen-Entropy (EE), to identify homogenous samples from minority classes for oversampling technique, specifically, SMOTE to reach data balances for classification. Experiments on public dataset and real-world datasets demonstrate the efficacy and effectiveness of the proposed EE-SMOTE in imbalanced learning.