Electron beam pumped semiconductor laser

Electron-beam-pumped semiconductor ultra-violet optical sources (ESUVOSs) are disclosed that use ballistic electron pumped wide bandgap semiconductor materials. The sources may produce incoherent radiation and take the form of electron-beam-pumped light emitting triodes (ELETs). The sources may produce coherent radiation and take the form of electron-beam-pumped laser triodes (ELTs). The ELTs may take the form of electron-beam-pumped vertical cavity surface emitting lasers (EVCSEL) or edge emitting electron-beam-pumped lasers (EEELs). The semiconductor medium may take the form of an aluminum gallium nitride alloy that has a mole fraction of aluminum selected to give a desired emission wavelength, diamond, or diamond-like carbon (DLC). The sources may be produced from discrete components that are assembled after their individual formation or they may be produced using batch MEMS-type or semiconductor-type processing techniques to build them up in a whole or partial monolithic manner, or combination thereof

Spectroscopic chemical analysis methods and apparatus

Spectroscopic chemical analysis methods and apparatus are disclosed which employ deep ultraviolet (e.g. in the 200 nm to 300 nm spectral range) electron beam pumped wide bandgap semiconductor lasers, incoherent wide bandgap semiconductor light emitting devices, and hollow cathode metal ion lasers to perform non-contact, non-invasive detection of unknown chemical analytes. These deep ultraviolet sources enable dramatic size, weight and power consumption reductions of chemical analysis instruments. Chemical analysis instruments employed in some embodiments include capillary and gel plane electrophoresis, capillary electrochromatography, high performance liquid chromatography, flow cytometry, flow cells for liquids and aerosols, and surface detection instruments. In some embodiments, Raman spectroscopic detection methods and apparatus use ultra-narrow-band angle tuning filters, acousto-optic tuning filters, and temperature tuned filters to enable ultra-miniature analyzers for chemical identification. In some embodiments Raman analysis is conducted simultaneously with native fluorescence spectroscopy to provide high levels of sensitivity and specificity in the same instrument

Local spectroscopy and atomic imaging of tunneling current, forces and dissipation on graphite

Theory predicts that the currents in scanning tunneling microscopy (STM) and the attractive forces measured in atomic force microscopy (AFM) are directly related. Atomic images obtained in an attractive AFM mode should therefore be redundant because they should be \emph{similar} to STM. Here, we show that while the distance dependence of current and force is similar for graphite, constant-height AFM- and STM images differ substantially depending on distance and bias voltage. We perform spectroscopy of the tunneling current, the frequency shift and the damping signal at high-symmetry lattice sites of the graphite (0001) surface. The dissipation signal is about twice as sensitive to distance as the frequency shift, explained by the Prandtl-Tomlinson model of atomic friction.Comment: 4 pages, 4 figures, accepted at Physical Review Letter

Spectroscopic Chemical Analysis Methods and Apparatus

This invention relates to non-contact spectroscopic methods and apparatus for performing chemical analysis and the ideal wavelengths and sources needed for this analysis. It employs deep ultraviolet (200- to 300-nm spectral range) electron-beam-pumped wide bandgap semiconductor lasers, incoherent wide bandgap semiconductor lightemitting devices, and hollow cathode metal ion lasers. Three achieved goals for this innovation are to reduce the size (under 20 L), reduce the weight [under 100 lb (.45 kg)], and reduce the power consumption (under 100 W). This method can be used in microscope or macroscope to provide measurement of Raman and/or native fluorescence emission spectra either by point-by-point measurement, or by global imaging of emissions within specific ultraviolet spectral bands. In other embodiments, the method can be used in analytical instruments such as capillary electrophoresis, capillary electro-chromatography, high-performance liquid chromatography, flow cytometry, and related instruments for detection and identification of unknown analytes using a combination of native fluorescence and/or Raman spectroscopic methods. This design provides an electron-beampumped semiconductor radiation-producing method, or source, that can emit at a wavelength (or wavelengths) below 300 nm, e.g. in the deep ultraviolet between about 200 and 300 nm, and more preferably less than 260 nm. In some variations, the method is to produce incoherent radiation, while in other implementations it produces laser radiation. In some variations, this object is achieved by using an AlGaN emission medium, while in other implementations a diamond emission medium may be used. This instrument irradiates a sample with deep UV radiation, and then uses an improved filter for separating wavelengths to be detected. This provides a multi-stage analysis of the sample. To avoid the difficulties related to producing deep UV semiconductor sources, a pumping approach has been developed that uses ballistic electron beam injection directly into the active region of a wide bandgap semiconductor material

Optimized Local Control for Active Distribution Grids using Machine Learning Techniques

Modern distribution system operators are facing a changing scenery due to the increasing penetration of distributed energy resources, introducing new challenges to system operation. In order to ensure secure system operation at a low cost, centralized and decentralized operational schemes are used to optimally dispatch these units. This paper proposes a decentralized, real-time, operation scheme for the optimal dispatch of distributed energy resources in the absence of extensive monitoring and communication infrastructure. This scheme uses an offline, centralized, optimal operation algorithm, with historical information, to generate a training dataset consisting of various operating conditions and corresponding distributed energy resources optimal decisions. Then, this dataset is used to design the individual local controllers for each unit with the use of machine learning techniques. The performance of the proposed method is tested on a low-voltage distribution network and is compared against centralized and existing decentralized methods

A hybrid approach for planning and operating active distribution grids

This paper investigates the planning and operational processes of modern distribution networks (DNs) hosting Distributed Energy Resources (DERs). While in the past the two aspects have been distinct, a methodology is proposed in this paper to co-optimize the two phases by considering the operational flexibility offered by DERs already in the planning phase. By employing AC Optimal Power Flow (OPF) to analyse the worst-case forecasts for the load and distributed generator (DG) injection, the optimal set-points for the DERs are determined such that the network's security is ensured. From these results, the optimized individual characteristic curves are then extracted for each DER which are used in the operational phase for the local control of the devices. The optimized controls use only local measurements to address system-wide issues and emulate the OPF solution without any communication. Finally, the proposed methodology is tested on the Cigre LV benchmark grid confirming that it is successful in mitigating with acceptable violations over- and under-voltage problems, as well as congestion issues. Its performance is compared against the OPF-based approach and currently employed local control schemes

Spectroscopic chemical analysis methods and apparatus

Spectroscopic chemical analysis methods and apparatus are disclosed which employ deep ultraviolet (e.g. in the 200 nm to 300 nm spectral range) electron beam pumped wide bandgap semiconductor lasers, incoherent wide bandgap semiconductor light emitting devices, and hollow cathode metal ion lasers to perform non-contact, non-invasive detection of unknown chemical analytes. These deep ultraviolet sources enable dramatic size, weight and power consumption reductions of chemical analysis instruments. Chemical analysis instruments employed in some embodiments include capillary and gel plane electrophoresis, capillary electrochromatography, high performance liquid chromatography, flow cytometry, flow cells for liquids and aerosols, and surface detection instruments. In some embodiments, Raman spectroscopic detection methods and apparatus use ultra-narrow-band angle tuning filters, acousto-optic tuning filters, and temperature tuned filters to enable ultra-miniature analyzers for chemical identification. In some embodiments Raman analysis is conducted along with photoluminescence spectroscopy (i.e. fluorescence and/or phosphorescence spectroscopy) to provide high levels of sensitivity and specificity in the same instrument

Identification and characterization of novel factors that act in the nonsense-mediated mRNA decay pathway in nematodes, flies and mammals

Nonsense-mediated mRNA decay (NMD) is a surveillance mechanism that degrades mRNAs harboring premature termination codons (PTCs). We have conducted a genome-wide RNAi screen in Caenorhabditis elegans that resulted in the identification of five novel NMD genes that are conserved throughout evolution. Two of their human homologs, GNL2 (ngp-1) and SEC13 (npp-20), are also required for NMD in human cells. We also show that the C. elegans gene noah-2, which is present in Drosophila melanogaster but absent in humans, is an NMD factor in fruit flies. Altogether, these data identify novel NMD factors that are conserved throughout evolution, highlighting the complexity of the NMD pathway and suggesting that yet uncovered novel factors may act to regulate this process

Classical Many-particle Clusters in Two Dimensions

We report on a study of a classical, finite system of confined particles in two dimensions with a two-body repulsive interaction. We first develop a simple analytical method to obtain equilibrium configurations and energies for few particles. When the confinement is harmonic, we prove that the first transition from a single shell occurs when the number of particles changes from five to six. The shell structure in the case of an arbitrary number of particles is shown to be independent of the strength of the interaction but dependent only on its functional form. It is also independent of the magnetic field strength when included. We further study the effect of the functional form of the confinement potential on the shell structure. Finally we report some interesting results when a three-body interaction is included, albeit in a particular model.Comment: Minor corrections, a few references added. To appear in J. Phys: Condensed Matte

Microbial contributions to coupled arsenic and sulfur cycling in the acid-sulfide hot spring Champagne Pool, New Zealand

Acid-sulfide hot springs are analogs of early Earth geothermal systems where microbial metal(loid) resistance likely first evolved. Arsenic is a metalloid enriched in the acid-sulfide hot spring Champagne Pool (Waiotapu, New Zealand). Arsenic speciation in Champagne Pool follows reaction paths not yet fully understood with respect to biotic contributions and coupling to biogeochemical sulfur cycling. Here we present quantitative arsenic speciation from Champagne Pool, finding arsenite dominant in the pool, rim and outflow channel (55-75% total arsenic), and dithio- and trithioarsenates ubiquitously present as 18-25% total arsenic. In the outflow channel, dimethylmonothioarsenate comprised ≤9% total arsenic, while on the outflow terrace thioarsenates were present at 55% total arsenic. We also quantified sulfide, thiosulfate, sulfate and elemental sulfur, finding sulfide and sulfate as major species in the pool and outflow terrace, respectively. Elemental sulfur concentration reached a maximum at the terrace. Phylogenetic analysis of 16S rRNA genes from metagenomic sequencing revealed the dominance of Sulfurihydrogenibium at all sites and an increased archaeal population at the rim and outflow channel. Several phylotypes were found closely related to known sulfur- and sulfide-oxidizers, as well as sulfur- and sulfate-reducers. Bioinformatic analysis revealed genes underpinning sulfur redox transformations, consistent with sulfur speciation data, and illustrating a microbial role in sulfur-dependent transformation of arsenite to thioarsenate. Metagenomic analysis also revealed genes encoding for arsenate reductase at all sites, reflecting the ubiquity of thioarsenate and a need for microbial arsenate resistance despite anoxic conditions. Absence of the arsenite oxidase gene, aio, at all sites suggests prioritization of arsenite detoxification over coupling to energy conservation. Finally, detection of methyl arsenic in the outflow channel, in conjunction with increased sequences from Aquificaceae, supports a role for methyltransferase in thermophilic arsenic resistance. Our study highlights microbial contributions to coupled arsenic and sulfur cycling at Champagne Pool, with implications for understanding the evolution of microbial arsenic resistance in sulfidic geothermal systems