High Thermoelectric Performance in PbSe–NaSbSe2 Alloys from Valence Band Convergence and Low Thermal Conductivity

PbSe is an attractive thermoelectric material due to its favorable electronic structure, high melting point, and lower cost compared to PbTe. Herein, the hitherto unexplored alloys of PbSe with NaSbSe2 (NaPbmSbSem+2) are described and the most promising p‐type PbSe‐based thermoelectrics are found among them. Surprisingly, it is observed that below 500 K, NaPbmSbSem+2 exhibits unorthodox semiconducting‐like electrical conductivity, despite possessing degenerate carrier densities of ≈1020 cm−3. It is shown that the peculiar behavior derives from carrier scattering by the grain boundaries. It is further demonstrated that the high solubility of NaSbSe2 in PbSe augments both the thermoelectric properties while maintaining a rock salt structure. Namely, density functional theory calculations and photoemission spectroscopy demonstrate that introduction of NaSbSe2 lowers the energy separation between the L‐ and Σ‐valence bands and enhances the power factors under 700 K. The crystallographic disorder of Na+, Pb2+, and Sb3+ moreover provides exceptionally strong point defect phonon scattering yielding low lattice thermal conductivities of 1–0.55 W m‐1 K‐1 between 400 and 873 K without nanostructures. As a consequence, NaPb10SbSe12 achieves maximum ZT ≈1.4 near 900 K when optimally doped. More importantly, NaPb10SbSe12 maintains high ZT across a broad temperature range, giving an estimated record ZTavg of ≈0.64 between 400 and 873 K, a significant improvement over existing p‐type PbSe thermoelectrics.The high solubility of NaSbSe2 in PbSe is exploited to facilitate convergence of L‐ and Σ‐valence bands and to produce strong point defect phonon scattering. These processes yield enhanced power factors and low lattice thermal conductivity over ≈300–700 K, which together give NaPb10SbSe12 outstanding thermoelectric performance with a maximum ZT ≈ 1.4 at 873 K and ZTavg ≈0.64 over 400–873 K.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151353/1/aenm201901377.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151353/2/aenm201901377-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151353/3/aenm201901377_am.pd

Open X-Embodiment:Robotic learning datasets and RT-X models

Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for many applications. Can such a consolidation happen in robotics? Conventionally, robotic learning methods train a separate model for every application, every robot, and even every environment. Can we instead train "generalist" X-robot policy that can be adapted efficiently to new robots, tasks, and environments? In this paper, we provide datasets in standardized data formats and models to make it possible to explore this possibility in the context of robotic manipulation, alongside experimental results that provide an example of effective X-robot policies. We assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks). We show that a high-capacity model trained on this data, which we call RT-X, exhibits positive transfer and improves the capabilities of multiple robots by leveraging experience from other platforms. The project website is robotics-transformer-x.github.io

Price dynamics and volatility jumps in bitcoin options

Abstract In the FinTech era, we contribute to the literature by studying the pricing of Bitcoin options, which is timely and important given that both Nasdaq and the CME Group have started to launch a variety of Bitcoin derivatives. We find pricing errors in the presence of market smiles in Bitcoin options, especially for short-maturity ones. Long-maturity options display more of a “smirk” than a smile. Additionally, the ARJI-EGARCH model provides a better overall fit for the pricing of Bitcoin options than the other ARJI-GARCH type models. We also demonstrate that the ARJI-GARCH model can provide more precise pricing of Bitcoin and its options than the SVCJ model in term of the goodness-of-fit in forecasting. Allowing for jumps is crucial for modeling Bitcoin options as we find evidence of time-varying jumps. Our empirical results demonstrate that the realized jump variation can describe the volatility behavior and capture the jump risk dynamics in Bitcoin and its options

CpG Oligodeoxynucleotides for Anticancer Monotherapy from Preclinical Stages to Clinical Trials

CpG oligodeoxynucleotides (CpG ODNs), the artificial versions of unmethylated CpG motifs that were originally discovered in bacterial DNA, are demonstrated not only as potent immunoadjuvants but also as anticancer agents by triggering toll-like receptor 9 (TLR9) activation in immune cells. TLR9 activation triggered by CpG ODN has been shown to activate plasmacytoid dendritic cells (pDCs) and cytotoxic T lymphocytes (CTLs), enhancing T cell-mediated antitumor immunity. However, the extent of antitumor immunity carried by TLR agonists has not been optimized individually or in combinations with cancer vaccines, resulting in a decreased preference for TLR agonists as adjuvants in clinical trials. Although various combination therapies involving CpG ODNs have been applied in clinical trials, none of the CpG ODN-based drugs have been approved by the FDA, owing to the short half-life of CpG ODNs in serum that leads to low activation of natural killer cells (NK cells) and CTLs, along with increases of pro-inflammatory cytokine productions. This review summarized the current innovation on CpG ODNs that are under clinical investigation and explored the future direction for CpG ODN-based nanomedicine as an anticancer monotherapy

A Squalene-Based Nanoemulsion for Therapeutic Delivery of Resiquimod

Agonists for toll-like receptors (TLRs) have shown promising activities against cancer. In the present study, a squalene-based nanoemulsion (NE) was loaded with resiquimod, a TLR7/8 agonist for therapeutic delivery. R848 NE was developed and characterized for long-term stability. In vitro and in vivo antitumor immunity of R848 NE were also evaluated in combination with SD-101, a CpG-containing TLR9 agonist. In vitro studies demonstrated strong long-term stability and immune responses to R848 NE. When combined with SD-101, strong antitumor activity was observed in MC38 murine colon carcinoma model with over 80% tumor growth inhibition. The combination treatment showed a 4-fold increase in systemic TNFa production and a 2.6-fold increase in Cd8a expression in tumor tissues, suggesting strong cell-mediated immune responses against the tumor. The treatment not only demonstrated a strong antitumor immunity by TLR7/8 and TLR9 activations but also induced PD-L1 upregulation in tumors, suggesting a potential therapeutic synergy with immune checkpoint inhibitors