Ultrathin In2O3thin-film transistors deposited from trimethylindium and ozone.

Indium oxide (In2O3) is a promising channel material for thin-film transistors (TFTs). In this work, we develop an atomic layer deposition (ALD) process of using trimethylindium and ozone (O3) to deposit In2O3films and fabricate ultrathin In2O3TFTs. The In2O3TFTs with 4 nm channel thickness show generally good switching characteristics with a highIon/Ioffof 108, a high mobility (µFE) of 16.2cm2V-1s-1and a positive threshold voltage (Vth) of 0.48 V. Although the 4 nm In2O3TFTs exhibit short channel effect, it can be improved by adding an ALD Ga2O3capping layer to afford the bilayer In2O3/Ga2O3channel structure. The afforded In2O3/Ga2O3TFTs exhibit improved immunity to the short channel effect, with good TFT characteristics ofIon/Ioffof 107,µFEof 9.3cm2V-1s-1, and positiveVthof 2.23 V. Overall, the thermal budget of the entire process is only 400 °C, which is suitable for the display and CMOS back-end-of-line-compatible applications.

Metatranscriptomic characterization of six types of forensic samples and its potential application to body fluid/tissue identification: A pilot study.

Microorganisms are potential markers for identifying body fluids (venous and menstrual blood, semen, saliva, and vaginal secretion) and skin tissue in forensic genetics. Existing published studies have mainly focused on investigating microbial DNA by 16 S rRNA gene sequencing or metagenome shotgun sequencing. We rarely find microbial RNA level investigations on common forensic body fluid/tissue. Therefore, the use of metatranscriptomics to characterize common forensic body fluids/tissue has not been explored in detail, and the potential application of metatranscriptomics in forensic science remains unknown. Here, we performed 30 metatranscriptome analyses on six types of common forensic sample from healthy volunteers by massively parallel sequencing. After quality control and host RNA filtering, a total of 345,300 unigenes were assembled from clean reads. Four kingdoms, 137 phyla, 267 classes, 488 orders, 985 families, 2052 genera, and 4690 species were annotated across all samples. Alpha- and beta-diversity and differential analysis were also performed. As a result, the saliva and skin groups demonstrated high alpha diversity (Simpson index), while the venous blood group exhibited the lowest diversity despite a high Chao1 index. Specifically, we discussed potential microorganism contamination and the "core microbiome," which may be of special interest to forensic researchers. In addition, we implemented and evaluated artificial neural network (ANN), random forest (RF), and support vector machine (SVM) models for forensic body fluid/tissue identification (BFID) using genus- and species-level metatranscriptome profiles. The ANN and RF prediction models discriminated six forensic body fluids/tissue, demonstrating that the microbial RNA-based method could be applied to BFID. Unlike metagenomic research, metatranscriptomic analysis can provide information about active microbial communities; thus, it may have greater potential to become a powerful tool in forensic science for microbial-based individual identification. This study represents the first attempt to explore the application potential of metatranscriptome profiles in forensic science. Our findings help deepen our understanding of the microorganism community structure at the RNA level and are beneficial for other forensic applications of metatranscriptomics.