Carbon nanotube reinforced nanocomposites for energy conversion and storage

CNT-reinforced foams comprised of three-dimensional (3D) interconnected macropores with uniform mesoporous walls were developed as multifunctional nanocomposites and tested for electrochemical energy conversion and storage. Multi-walled CNTs grown on the wall surface of the interconnected scaffold structure of carbon foams were found to improve the surface area and electrochemical properties of the nanocomposites. The lightweight CNT-reinforced nanocomposites not only exhibit high structural flexibility, but also possess enhanced electrocatalytic performance for HER at current density of 10 mA cm−2 with overpotentials of 240 mV. In addition, these nanocomposites can be used as flexible, electric double layer capacitor electrodes, and have achieved a specific capacitance of 776 F g−1, with excellent durability and stability after 1000 cycles

GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimation

The inherent ambiguity in ground-truth annotations of 3D bounding boxes caused by occlusions, signal missing, or manual annotation errors can confuse deep 3D object detectors during training, thus deteriorating the detection accuracy. However, existing methods overlook such issues to some extent and treat the labels as deterministic. In this paper, we formulate the label uncertainty problem as the diversity of potentially plausible bounding boxes of objects, then propose GLENet, a generative framework adapted from conditional variational autoencoders, to model the one-to-many relationship between a typical 3D object and its potential ground-truth bounding boxes with latent variables. The label uncertainty generated by GLENet is a plug-and-play module and can be conveniently integrated into existing deep 3D detectors to build probabilistic detectors and supervise the learning of the localization uncertainty. Besides, we propose an uncertainty-aware quality estimator architecture in probabilistic detectors to guide the training of IoU-branch with predicted localization uncertainty. We incorporate the proposed methods into various popular base 3D detectors and demonstrate significant and consistent performance gains on both KITTI and Waymo benchmark datasets. Especially, the proposed GLENet-VR outperforms all published LiDAR-based approaches by a large margin and ranks $1^{st}$ among single-modal methods on the challenging KITTI test set. We will make the source code and pre-trained models publicly available

Ultralight three-dimensional, carbon-based nanocomposites for thermal energy storage

Polymer based nanocomposites consisting of elastic three-dimensional (3D) carbon foam (CF), paraffin wax and graphene nanoplatelets (GNPs) have been created and evaluated for thermal energy storage. The ultralight, highly porous (∼98.6% porosity), and flexible CFs with densities of 2.84–5.26 mg/cm3 have been used as the backbone skeleton to accommodate phase change wax and nanoscale thermal conductive enhancer, GNP. Low level of defects and the ordered sp2 configuration allow the resulting CFs to exhibit excellent cyclic compressive behavior at strains up to 95%, while retaining part of their elastic properties even after 100 cycles of testing. By dispersing the highly conductive GNP nanofillers in paraffin wax and infiltrating them into the flexible CFs, the resultant nanocomposites were observed to possess enhanced overall thermal conductivity up to 0.76 W/(m K), representing an impressive improvement of 226%, which is highly desirable for thermal engineering

Monitoring of Fiber-Reinforced Composite Single-Lap Joint with Electromechanical Impedance of Piezoelectric Transducer.

The single-lap joint of fiber-reinforced composites is a common structure in the field of structure repair, which has excellent mechanical properties. To study and monitor its quasi-static response behavior under external load, two methodologies called effective structural mechanical impedance (ESMI) and reduced-ESMI (R-ESMI) are presented in this article. A two-dimensional electromechanical impedance (EMI) model for a surface-bonded square piezoelectric transducer (PZT) is adopted to extract more sensitive signatures from the measured raw signatures. There are two major advantages of the monitoring scheme based on ESMI and R-ESMI signatures: (1) excellent monitoring results with less signatures to process, (2) the ability to monitor the quasi-static behavior of a single-lap joint with previously ignored susceptance signatures. Combining the extracted ESMI signatures with the index of root-mean-square deviation, the quasi-static behavior of single-lap joints can be effectively quantified. To test the effectiveness of ESMI methodology, verifying experiments were conducted. The experimental results convincingly demonstrated that the presented ESMI and R-ESMI methodologies have good feasibility in monitoring the quasi-static behavior of a fiber-reinforced composite single-lap joint. The proposed method has potential application in the field of structural health monitoring (SHM)

Metal Sulfide Nanoparticles Anchored N, S Co-doped Porous Carbon Nanofibers as Highly Efficient Bifunctional Electrocatalysts for Oxygen Reduction/Evolution Reactions

Developing multi-functional electrocatalysts is a key for new energy techniques,such as fuel cells, metal-air batteries, and water splitting. In this paper, a bifunctional (ORR/OER) electrocatalysts, metal sulfide nanoparticles anchored N, S co-doped porous carbon nanofibers were successfully synthesized by a simultaneous carbonization and sulfurization of ZIFs/PAN electrospun composite nanofibers. The as-prepared material Zn/Co-ZIFs/PAN-CS-800 catalyst exhibited an excellent electrocatalytic performance in both ORR and OER. Such excellent ORR and OER performance comes from the activemetal sulfide species, N, S co-doping effect, porous structure, and good conductivity. Our method can be used to produce other metal sulfide nanoparticles combined with N, S co-doped porous carbon materials with potential applications in the field of energy storage and conversion

Carbon encapsulated WS2 nanocomposites derived from ZIF- 67@WS2 Core-Shell Nanoparticles and their electrocatalytic applications

In this work, Co9S8 and N,S co-dopped carbon encapsulated WS2nanocomposites (Co9S8-N,S-C@WS2) has been successfully prepared through a high-temperature carbonization of the precursor ZIF-67@WS2nanoparticles. The obtained Co9S8-N,S-C@WS2nanoparticles were confirmed to have a core-shell structure and uniform element distribution by TEM and element mapping. Its crystal structure was characterized by XRD, and the high specific surface areas with porous structure was characterized by BET tests. The as-prepared Co9S8-N,S-C@WS2nanoparticles exhibited a better ORR/OER/HER performance than single component. In this work,a novel idea for the preparation of functional nanocomposite materials could be provide

Preparation and Characterization of Multi-Doped PorousCarbon Nanofibers from Carbonization in Different Atmospheres and Their Oxygen Electrocatalytic Properties Research

Recently, electrocatalysts for oxygen reduction reaction (ORR) as well as oxygen evolution reaction (OER) hinged on electrospun nanofiber composites have attracted wide research attention. Transition metal elements and heteroatomic doping are important methods used to enhance their catalytic performances. Lately, the construction of electrocatalysts based on metal-organic framework (MOF) electrospun nanofibers has become a research hotspot. In this work, nickel-cobalt zeolitic imidazolate frameworks with different molar ratios (NixCoy-ZIFs) were synthesized in an aqueous solution, followed by NixCoy-ZIFs/polyacrylonitrile (PAN) electrospun nanofiber precursors, which were prepared by a simple electrospinning method. Bimetal (Ni-Co) porous carbon nanofiber catalysts doped with nitrogen, oxygen, and sulfur elements were obtained at high-temperature carbonization treatment in different atmospheres (argon (Ar), Air, and hydrogen sulfide (H2S)), respectively. The morphological properties, structures, and composition were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), selected area electron diffraction (SAED), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). Moreover, the specific surface area of materials and their pore size distribution was characterized by Brunauer-Emmett-Teller (BET). Linear sweep voltammetry curves investigated catalyst performances towards oxygen reduction and evolution reactions. Importantly, Ni1Co2-ZIFs/PAN-Ar yielded the best ORR activity, whereas Ni1Co1-ZIFs/PAN-Air exhibited the best OER performance. This work provides significant guidance for the preparation and characterization of multi-doped porous carbon nanofibers carbonized in different atmospheres

Abundance of SSR Motifs and Development of Candidate Polymorphic SSR Markers (BARCSOYSSR_1.0) in Soybean

Simple sequence repeat (SSR) genetic markers, also referred to as microsatellites, function in map-based cloning and for marker-assisted selection in plant breeding. The objectives of this study were to determine the abundance of SSRs in the soybean genome and to develop and test soybean SSR markers to create a database of locus-specific markers with a high likelihood of polymorphism. A total of 210,990 SSRs with di-, tri-, and tetranucleotide repeats of five or more were identified in the soybean whole genome sequence (WGS) which included 61,458 SSRs consisting of repeat units of di- (≥10), tri- (≥8), and tetranucleotide (≥7). Among the 61,458 SSRs, (AT)n, (ATT)n and (AAAT)n were the most abundant motifs among di-, tri-, and tetranucleotide SSRs, respectively. After screening for a number of factors including locus-specificity using e-PCR, a soybean SSR database (BARCSOYSSR_1.0) with the genome position and primer sequences for 33,065 SSRs was created. To examine the likelihood that primers in the database would function to amplify locus-specific polymorphic products, 1034 primer sets were evaluated by amplifying DNAs of seven diverse Glycine max (L.) Merr. and one wild soybean (Glycine soja Siebold & Zucc.) genotypes. A total of 978 (94.6%) of the primer sets amplified a single polymerase chain reaction (PCR) product and 798 (77.2%) amplified polymorphic amplicons as determined by 4.5% agarose gel electrophoresis. The BARCSOYSSR1.0 SSR markers can be found in Soy- Base (http://soybase.org; verified 21 June 2010) the USDA-ARS Soybean Genome Database

A High Density Integrated Genetic Linkage Map of Soybean and the Development of a 1536 Universal Soy Linkage Panel for Quantitative Trait Locus Mapping

Single nucleotide polymorphisms (SNPs) are the marker of choice for many researchers due to their abundance and the high-throughput methods available for their multiplex analysis. Only recently have SNP markers been available to researchers in soybean [Glycine max (L.) Merr.] with the release of the third version of the consensus genetic linkage map that added 1141 SNP markers to the map. Our objectives were to add 2500 additional SNP markers to the soybean integrated map and select a set of 1536 SNPs to create a universal linkage panel for high-throughput soybean quantitative trait locus (QTL) mapping. The GoldenGate assay is one high-throughput analysis method capable of genotyping 1536 SNPs in 192 DNA samples over a 3-d period. We designed GoldenGate assays for 3456 SNPs (2956 new plus 500 previously mapped) which were used to screen three recombinant inbred line populations and diverse germplasm. A total of 3000 workable assays were obtained which added about 2500 new SNP markers to create a fourth version of the soybean integrated linkage map. To create a “Universal Soy Linkage Panel” (USLP 1.0) of 1536 SNP loci, SNPs were selected based on even distribution throughout each of the 20 consensus linkage groups and to have a broad range of allele frequencies in diverse germplasm. The 1536 USLP 1.0 will be able to quickly create a comprehensive genetic map in most QTL mapping populations and thus will serve as a useful tool for high-throughput QTL mapping