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Bismuth telluride-based materials have been widely used in commercial thermoelectric applications due to their excellent thermoelectric performance in the near-room-temperature range, yet further improvement of their thermoelectric properties is still necessary. Moreover, the narrow band gap of these materials results in a bipolar effect at elevated temperatures, which causes severe degradation of the thermoelectric performance. In this work, the commercial Bi0.4Sb1.6Te3was alloyed with AgSbTe2by using high-energy ball milling method combined with spark plasma sintering. It was found that ball milling can effectively reduce the lattice thermal conductivity of the samples. The alloying of AgSbTe2leads to a gradual increase in hole carrier concentration, resulting in an enhanced electrical conductivity and optimized power factor. Additionally, the bipolar effect is also weakened due to the increased hole carrier concentration. Furthermore, the substitution of Ag in the Bi/Sb sublattice causes further reduction in the lattice thermal conductivity. Ultimately, the sample alloyed with 0.15 wt % AgSbTe2demonstrates its best thermoelectric performance with a maximum zTof 1.35 at 393 K, showing a 20.5% improvement compared to the commercial sample. Besides, its average zTreaches a high value of 1.25 between 303 and 483 K, with a 27.6% improvement compared to that of the commercial sample.

In this work, a series of Cu2Se/xwt % porous carbon (PC) (x= 0, 0.2, 0.4, 0.6, 0.8, 1) composite materials were synthesized by ball milling and spark plasma sintering (SPS). The highly ordered porous carbon was synthesized by a hydrothermal method using mesoporous silica (SBA-15) as the template. X-ray diffraction results show that the incorporation of porous carbon induces a phase transition of Cu2Se from the β phase to the α phase. Meanwhile, the addition of porous carbon reduces the carrier concentration from 2.7 × 1021to 2.45 × 1020cm–3by 1 order of magnitude. The decrease of the carrier concentration leads to the reduction of electrical conductivity and the increase of the Seebeck coefficient, which results in the enhancement of the power factor. On the other hand, the incorporation of porous carbon into Cu2Se increases the porosity of the composites and also introduces more interfaces between the two materials, which is evidenced by positron annihilation lifetime measurements. Both pores and interfaces greatly enhance phonon scattering, leading to extremely low lattice thermal conductivity. In addition, the decrease of electrical conductivity also causes a sufficient reduction in electronic thermal conductivity. Due to the above synergistic effects, the thermoelectric performance of the Cu2Se/PC composite is significantly enhanced with a maximum ZTvalue of 0.92 at 403 K in the Cu2Se/1 wt % PC composite, which is close to that of the Bi2Te3-based materials. Our work shows that α-Cu2Se has great potential for near-room-temperature thermoelectric materials.

Background: Identification of genomic markers using NGS (next-generation sequencing) technology would be valuable for guiding precision medicine treatments for pancreatic cancers. Traditional somatic mutation methods require both tumor and matched non-tumor samples. However, only tumor samples are available mostly, especially in retrospective studies. In this study, we tried to analyze the associations between clinical features and oncogenic somatic mutations in genome-wide tumor-only samples. Methods: Fifty-four tumor-only samples derived from pancreatic cancer patients were used for whole-exome sequencing. An approach involving SNP filtering of variants included in the Catalogue of Somatic Mutations in Cancer (COSMIC) database was used to identify oncogenic somatic mutations. The relationships between oncogenic mutations and clinical features were analyzed and simultaneously compared with those from the TCGA database. Results: By analyzing the mutations from tumor only samples, divergent mutation profiles were observed in different locations (head vs. body/tail) of pancreatic tumors. The divergences between pancreatic head and body/tail cancers were also confirmed by the TCGA data. Furthermore, mutations of several genes were found to be significantly associated with clinical features, such as pathological stage and the degree of tumor differentiation. Conclusion: The results confirmed the efficiency of our approach in identifying oncogenic somatic mutations from tumor only samples and revealed the associations between somatic mutations and clinical features in pancreatic cancer.