We prepared undoped and Fe-doped MoS2 layered crystals using a chemical vapor transport method to compare their optical and electrical properties. Optical behaviors of carrier transitions were observed successfully in both undoped and Fe-doped MoS2 samples using reflectance and piezoreflectance. Frequency-dependent photoconductivity (PC) measurements reveal an additional deep Fe doping level for the Fe-doped MoS2 sample. In addition, a longer carrier lifetime was calculated for the Fe-doped MoS2 sample than for the undoped MoS2 sample through PC analysis. Hall measurements were also performed for both samples and indicated that the Fe-doped MoS2 sample exhibited a higher carrier concentration and a lower mobility owing to the effect of Fe dopants. Furthermore, both samples were confirmed to have n-type carriers.

Co-doped and undoped layered MoS 2 crystals were grown by the chemical vapor transport method using iodine as the transport agent. Both reflectance and piezoreflectance measurements reveal two exciton transitions of the direct band edge around 1.86 and 2.06 eV for undoped MoS 2 and 1.84 and 2.03 eV for Co-doped MoS 2 . Hall effect measurements show that the Co-doped MoS 2 sample has a lower carrier concentration and mobility than the undoped sample. These differences between undoped and Co-doped MoS 2 were attributed to the effect of cobalt atoms causing a small lattice distortion, lattice imperfections and/or impurity states that form trap states between the conduction band and valence band. Furthermore, photoconductivity (PC) and persistent PC results show that Co-doped MoS 2 has a longer time constant and better responsivity than undoped MoS 2 . This work discusses the advantages of Co-doped MoS 2 for photodetector applications.

Abstract:In this paper, MoS 2 and Ni-MoS 2 crystal layers were fabricated by the chemical vapor transport method with iodine as the transport agent. Two direct band edge transitions of excitons at 1.9 and 2.1 eV were observed successfully for both MoS 2 and Ni-MoS 2 samples using temperature-dependent optical reflectance (R) measurement. Hall effect measurements were carried out to analyze the transport behavior of carriers in MoS 2 and Ni-MoS 2 , which indicate that the Ni-MoS 2 sample is n-type and has a higher resistance and lower mobility than the MoS 2 sample has. A photoconductivity spectrum was performed which shows an additional Ni doping level existing at 1.2 eV and a higher photocurrent generating only for Ni-MoS 2 . The differences between MoS 2 and Ni-MoS 2 could be attributed to the effect of Ni atoms causing small lattice imperfections to form trap states around 1.2 eV. The temperature-dependent conductivity shows the presence of two shallow levels with activation energies (84 and 6.7 meV in MoS 2 ; 57 and 6.5 meV in Ni-MoS 2 ). Therefore, the Ni doping level leads to high resistance, low mobility and small activation energies. A series of experimental results could provide useful guidance for the fabrication of optoelectronic devices using MoS 2 structures.

Motivation Cross-sample comparisons or large-scale meta-analyses based on the next generation sequencing (NGS) involve replicable and universal data preprocessing, including removing adapter fragments in contaminated reads (i.e., adapter trimming). While modern adapter trimmers require users to provide candidate adapter sequences for each sample, which are sometimes unavailable or falsely documented in the repositories (such as GEO or SRA), large-scale meta-analyses are therefore jeopardized by suboptimal adapter trimming. Results Here we introduce a set of fast and accurate adapter detection and trimming algorithms that entail no a priori adapter sequences. These algorithms were implemented in modern C ++ with SIMD and multithreading to accelerate its speed. Our experiments and benchmarks show that the implementation (i.e., EARRINGS), without being given any hint of adapter sequences, can reach comparable accuracy and higher throughput than that of existing adapter trimmers. EARRRINGS is particularly useful in meta-analyses of a large batch of datasets and can be incorporated in any sequence analysis pipelines in all scales. Availability and implementation EARRINGS is open-source software and is available at https://github.com/jhhung/EARRINGS. Supplementary information Supplementary data are available at Bioinformatics online.