Role of Chain Morphology and Stiffness in Thermal Conductivity of Amorphous Polymers

Designing thermally conductive polymer is of scientific interest and practical importance for applications like thermal interface materials, electronics packing, and plastic heat exchangers. In this work, we study the fundamental relationship between the molecular morphology and thermal conductivity in bulk amorphous polymers. We use polyethylene as a model system and performed systematic parametric study in molecular dynamics simulations. We find that the thermal conductivity is a strong function of the radius of gyration of the molecular chains, which is further correlated to persistence length, an intrinsic property of the molecule that characterizes molecular stiffness. Larger persistence length can lead to more extended chain morphology and thus higher thermal conductivity. Further thermal conductivity decomposition analysis shows that thermal transport through covalent bonds dominates the effective thermal conductivity over other contributions from nonbonded interactions (van der Waals) and translation of molecules disregarding the morphology. As a result, the more extended chains due to larger persistence length provide longer spatial paths for heat to transfer efficiently and thus lead to higher thermal conductivity. In addition, rigid rod-like polymers with very large persistence length tend to spontaneously crystallize and form orientated chains, leading to a thermal conductivity increase by more than 1 order of magnitude. Our results will provide important insights into the design of thermally conductive amorphous polymers

High-Contrast, Reversible Thermal Conductivity Regulation Utilizing the Phase Transition of Polyethylene Nanofibers

Reversible thermal conductivity regulation at the nanoscale is of great interest to a wide range of applications such as thermal management, phononics, sensors, and energy devices. Through a series of large-scale molecular dynamics simulations, we demonstrate a thermal conductivity regulation utilizing the phase transition of polyethylene nanofibers, enabling a thermal conductivity tuning factor of as high as 12, exceeding all previously reported values. The thermal conductivity change roots from the segmental rotations along the polymer chains, which introduce along-chain morphology disorder that significantly interrupts phonon transport along the molecular chains. This phase transition, which can be regulated by temperature, strain, or their combinations, is found to be fully reversible in the polyethylene nanofibers and can happen at a narrow temperature window. The phase change temperature can be further tuned by engineering the diameters of the nanofibers, making such a thermal conductivity regulation scheme adaptable to different application needs. The findings can stimulate significant research interest in nanoscale heat transfer control

Postsynthetic Metalation of Bipyridyl-Containing Metal–Organic Frameworks for Highly Efficient Catalytic Organic Transformations

We have designed highly stable and recyclable single-site solid catalysts via postsynthetic metalation of the 2,2′-bipyridyl-derived metal–organic framework (MOF) of the UiO structure (bpy-UiO). The Ir-functionalized MOF (bpy-UiO-Ir) is a highly active catalyst for both borylation of aromatic C–H bonds using B₂(pin)₂ (pin = pinacolate) and <i>ortho</i>-silylation of benzylicsilyl ethers; the <i>ortho</i>-silylation activity of the bpy-UiO-Ir is at least 3 orders of magnitude higher than that of the homogeneous control. The Pd-functionalized MOF (bpy-UiO-Pd) catalyzes the dehydrogenation of substituted cyclohexenones to afford phenol derivatives with oxygen as the oxidant. Most impressively, the bpy-UiO-Ir was recycled and reused 20 times for the borylation reaction without loss of catalytic activity or MOF crystallinity. This work highlights the opportunity in designing highly stable and active catalysts based on MOFs containing nitrogen donor ligands for important organic transformations

Flexible Expectile Regression in Reproducing Kernel Hilbert Spaces

<p>Expectile, first introduced by Newey and Powell in <a href="#cit0017" target="_blank">1987</a> in the econometrics literature, has recently become increasingly popular in risk management and capital allocation for financial institutions due to its desirable properties such as coherence and elicitability. The current standard tool for expectile regression analysis is the multiple linear expectile regression proposed by Newey and Powell in <a href="#cit0017" target="_blank">1987</a>. The growing applications of expectile regression motivate us to develop a much more flexible nonparametric multiple expectile regression in a reproducing kernel Hilbert space. The resulting estimator is called KERE, which has multiple advantages over the classical multiple linear expectile regression by incorporating nonlinearity, nonadditivity, and complex interactions in the final estimator. The kernel learning theory of KERE is established. We develop an efficient algorithm inspired by majorization-minimization principle for solving the entire solution path of KERE. It is shown that the algorithm converges at least at a linear rate. Extensive simulations are conducted to show the very competitive finite sample performance of KERE. We further demonstrate the application of KERE by using personal computer price data. Supplementary materials for this article are available online.</p

Molecular Fin Effect from Heterogeneous Self-Assembled Monolayer Enhances Thermal Conductance across Hard–Soft Interfaces

Thermal transport across hard–soft interfaces is critical to many modern applications, such as composite materials, thermal management in microelectronics, solar–thermal phase transition, and nanoparticle-assisted hyperthermia therapeutics. In this study, we use equilibrium molecular dynamics (EMD) simulations combined with the Green–Kubo method to study how molecularly heterogeneous structures of the self-assembled monolayer (SAM) affect the thermal transport across the interfaces between the SAM-functionalized gold and organic liquids (hexylamine, propylamine and hexane). We focus on a practically synthesizable heterogeneous SAM featuring alternating short and long molecular chains. Such a structure is found to improve the thermal conductance across the hard–soft interface by 46–68% compared to a homogeneous nonpolar SAM. Through a series of further simulations and analyses, it is found that the root reason for this enhancement is the penetration of the liquid molecules into the spaces between the long SAM molecule chains, which increase the effective contact area. Such an effect is similar to the fins used in macroscopic heat exchanger. This “molecular fin” structure from the heterogeneous SAM studied in this work provides a new general route for enhancing thermal transport across hard–soft material interfaces

Metal–Organic Frameworks Stabilize Solution-Inaccessible Cobalt Catalysts for Highly Efficient Broad-Scope Organic Transformations

New and active earth-abundant metal catalysts are critically needed to replace precious metal-based catalysts for sustainable production of commodity and fine chemicals. We report here the design of highly robust, active, and reusable cobalt-bipyridine- and cobalt-phenanthroline-based metal–organic framework (MOF) catalysts for alkene hydrogenation and hydroboration, aldehyde/ketone hydroboration, and arene C–H borylation. In alkene hydrogenation, the MOF catalysts tolerated a variety of functional groups and displayed unprecedentedly high turnover numbers of ∼2.5 × 10⁶ and turnover frequencies of ∼1.1 × 10⁵ h^–1. Structural, computational, and spectroscopic studies show that site isolation of the highly reactive (bpy)­Co­(THF)₂ species in the MOFs prevents intermolecular deactivation and stabilizes solution-inaccessible catalysts for broad-scope organic transformations. Computational, spectroscopic, and kinetic evidence further support a hitherto unknown (bpy^•–)­Co^I(THF)₂ ground state that coordinates to alkene and dihydrogen and then undergoing σ-complex-assisted metathesis to form (bpy)­Co­(alkyl)­(H). Reductive elimination of alkane followed by alkene binding completes the catalytic cycle. MOFs thus provide a novel platform for discovering new base-metal molecular catalysts and exhibit enormous potential in sustainable chemical catalysis

Cycloastragenol restrains keratinocyte hyperproliferation by promoting autophagy via the miR-145/STC1/Notch1 axis in psoriasis

Psoriasis is characterized by inflammation and hyperproliferation of epidermal keratinocytes. Cycloastragenol (CAG) is an active molecule of Astragalus membranaceus that potentially plays a repressive role in psoriasis. Activated cell autophagy is an effective pathway for alleviating psoriasis progression. Thus, we investigated the role of CAG in the proliferation and autophagy of interleukin (IL)-22-stimulated keratinocytes. A psoriasis model was established by stimulating HaCaT cells with IL-22. Gene or protein expression levels were measured by qRT-PCR or western blot. Autophagy flux was observed with mRFP-GFP-LC3 adenovirus transfection assay under confocal microscopy. Stanniocalcin-1 (STC1) secretion levels were determined using ELISA kits. The apoptosis rate was assessed using flow cytometry. Interactions between miR-145 and STC1 or STC1 and Notch1 were validated by luciferase reporter gene assays, RIP, and Co-IP assays. CAG repressed cell proliferation and promoted apoptosis and autophagy in IL-22-stimulated HaCaT cells. Additionally, CAG promoted autophagy by enhancing miR-145. STC1 silencing ameliorated autophagy repression in IL-22-treated HaCaT cells. Moreover, miR-145 negatively regulated STC1, and STC1 was found to activate Notch1. Lastly, STC1 overexpression reversed CAG-promoted autophagy. CAG alleviated keratinocyte hyperproliferation through autophagy enhancement via regulating the miR-145/STC1/Notch1 axis in psoriasis.</p

Additional file 1: of trumpet: transcriptome-guided quality assessment of m6A-seq data

Source code of the trumpet R package. (ZIP 2229 kb

Additional file 2: of trumpet: transcriptome-guided quality assessment of m6A-seq data

Supplementary Material (including Table S1-S4) for trumept. (DOCX 21 kb

DMRT1 Is Required for Mouse Spermatogonial Stem Cell Maintenance and Replenishment

<div><p>Male mammals produce sperm for most of postnatal life and therefore require a robust germ line stem cell system, with precise balance between self-renewal and differentiation. Prior work established <i>doublesex-</i> and <i>mab-3</i>-related transcription factor 1 (<i>Dmrt1</i>) as a conserved transcriptional regulator of male sexual differentiation. Here we investigate the role of <i>Dmrt1</i> in mouse spermatogonial stem cell (SSC) homeostasis. We find that <i>Dmrt1</i> maintains SSCs during steady state spermatogenesis, where it regulates expression of <i>Plzf</i>, another transcription factor required for SSC maintenance. We also find that <i>Dmrt1</i> is required for recovery of spermatogenesis after germ cell depletion. Committed progenitor cells expressing <i>Ngn3</i> normally do not contribute to SSCs marked by the <i>Id4-Gfp</i> transgene, but do so when spermatogonia are chemically depleted using busulfan. Removal of <i>Dmrt1</i> from <i>Ngn3</i>-positive germ cells blocks the replenishment of Id4-GFP-positive SSCs and recovery of spermatogenesis after busulfan treatment. Our data therefore reveal that <i>Dmrt1</i> supports SSC maintenance in two ways: allowing SSCs to remain in the stem cell pool under normal conditions; and enabling progenitor cells to help restore the stem cell pool after germ cell depletion.</p></div