Thermogravimetry-synchronized, reference-free quantitative mass spectrometry for accurate compositional analysis of polymer systems without prior knowledge of constituents.

Compositional analysis (CA)-identification and quantification of the system constituents-is the most fundamental and decisive approach for investigating the system of interest. Pyrolysis mass spectrometry (MS) with a high resolution of over 10 000 is very effective for chemical identification and is directly applicable to polymer materials regardless of their solubilities. However, it is less helpful for quantification, especially when the references, i.e., pure constituents, are unknown, non-isolable and thus cannot be prepared. To compensate for this weakness, herein we propose reference-free quantitative mass spectrometry (RQMS) with enhanced quantification accuracy assisted by synchronized thermogravimetry (TG). The key to success lies in correlating the instantaneous weight loss from TG with the MS signal, enabling the quantitative evaluation of the distinct ionization efficiency for each fragment individually. The determined ionization efficiencies allow the conversion of MS signal intensities of pyrolyzed fragments into weight abundances. In a benchmark test using ternary polymer systems, this new framework named TG-RQMS demonstrates accurate CA within ±1.3 wt% errors without using any prior knowledge or spectra of the references. This simple yet accurate and versatile CA method would be an invaluable tool to investigate polymer materials whose composition is hardly accessible via other analytical methods.

Decoding thermal properties in polymer-inorganic heat dissipators: a data-driven approach using pyrolysis mass spectrometry.

Polymeric materials can boost their performances by strategically incorporating inorganic substances. Heat dissipators are a representative class of such composite materials, where inorganic fillers and matrix polymers contribute to high thermal conductivity and strong adhesion, respectively, resulting in excellent heat dissipation performance. However, due to the complex interaction between fillers and polymers, even slight differences in structural parameters, e.g. dispersion/aggregation degree of fillers and crosslink density of polymers, may significantly impact material performance, complicating the quality management and guidelines for material developments. Therefore, we introduce pyrolysis mass spectra (MS) as material descriptors. On the basis of these spectra, we construct prediction models using a data-driven approach, specifically focusing on thermal conductivity and adhesion, which are key indicators for heat dissipating performance. Pyrolysis-MS observes thermally decomposable polymers, which occupy only 0.1 volume fraction of the heat dissipators; nevertheless, the physical states of non-decomposable inorganic fillers are implicitly reflected in the pyrolyzed fragment patterns of the matrix polymers. Consequently, pyrolysis-MS provides sufficient information to construct accurate models for predicting heat dissipation performance, simplifying quality management by substituting time-consuming performance evaluations with rapid pyrolysis-MS measurements. Furthermore, we elucidate that higher crosslinking density of the matrix polymers enhances thermal conductivity. This data-driven method promises to streamline the identification of key functional factors in complex composite materials.

Using pyrolysis-MS as a material descriptor allows for the prediction of composite materials' heat dissipation capabilities and the identification of key factors influencing these properties.

Revealing factors influencing polymer degradation with rank-based machine learning.

The efficient treatment of polymer waste is a major challenge for marine sustainability. It is useful to reveal the factors that dominate the degradability of polymer materials for developing polymer materials in the future. The small number of available datasets on degradability and the diversity of their experimental means and conditions hinder large-scale analysis. In this study, we have developed a platform for evaluating the degradability of polymers that is suitable for such data, using a rank-based machine learning technique based on RankSVM. We then made a ranking model to evaluate the degradability of polymers, integrating three datasets on the degradability of polymers that are measured by different means and conditions. Analysis of this ranking model with a decision tree revealed factors that dominate the degradability of polymers.

A data-driven sequencer that unveils latent "codons" in synthetic copolymers.

The recent emergence of sequence engineering in synthetic copolymers has been innovating polymer materials, where short sequences, hereinafter called "codons" using an analogy from nucleotide triads, play key roles in expressing functions. However, the codon compositions cannot be experimentally determined owing to the lack of efficient sequencing methods, hindering the integration of experiments and theories. Herein, we propose a polymer sequencer based on mass spectrometry of pyrolyzed oligomeric fragments. Despite the random fragmentation along copolymer main-chains, the characteristic fragment patterns of the codons are identified and quantified via unsupervised learning of a spectral dataset of random copolymers. The codon complexities increase with their length and monomer component number. Our data-driven approach accommodates the increasing complexities by expanding the dataset; the codon compositions of binary triads, binary pentads and ternary triads are quantifiable with small datasets (N < 100). The sequencer allows describing copolymers with their codon compositions/distributions, facilitating sequence engineering toward innovative polymer materials.

Highly Reversible Sodium Metal Battery Anodes via Alloying Heterointerfaces.

As a promising pathway toward low-cost, long-duration energy storage, rechargeable sodium batteries are of increasing interest. Batteries that incorporate metallic sodium as anode promise a high theoretical specific capacity of 1166 mAh g-1 , and low reduction potential of -2.71 V. The high reactivity and poor electrochemical reversibility of sodium anodes render sodium metal anode (SMA) cells among the most challenging for practical implementation. Here, the failure mechanisms of Na anodes are investigated and the authors report that loss of morphological control is not the fundamental cause of failure. Rather, it is the inherently poor anchoring/root structure of electrodeposited Na to the electrode substrate that leads to poor reversibility and cell failure. Poorly anchored Na deposits are prone to break away from the current collector, producing orphaning and poor anode utilization. Thin metallic coatings in a range of chemistries are proposed and evaluated as SMA substrates. Based on thermodynamic and ion transport considerations, such substrates undergo reversible alloying reactions with Na and are hypothesized to promote good root growth-regardless of the morphology. Among the various options, Au stands out for its ability to support long Na anode lifetime and high reversibility (Coulombic Efficiency > 98%), for coating thicknesses in the range of 10-1000 nm. As a first step toward evaluating practical utility of the anodes, their performance in Na||SPAN cells with N:P ratio close to 1:1 is evaluated.

Self-template-assisted micro-phase segregation in blended liquid-crystalline block copolymers films toward three-dimensional structures.

In-plane mesopatterns derived from block-copolymer (BCP) micro-phase segregation in thin films have attracted much interest in practical applications as well as fundamental research programs. However, phase segregation along the film-normal direction has been less studied. Here, we describe a strategy to concurrently, yet independently, control in-plane micro-phase and out-of-plane macro-phase segregation in multiblended films composed of liquid-crystalline BCPs (LCBCPs), affording spontaneously layered three-dimensional (3D) mesostructures. This strategy relies on sequential liquid crystallization during the cooling process in thermal annealing as follows. The constituent LCBCP with the highest isotropic-transition temperature (Tiso) first liquid-crystallizes and segregates from the other LCBCP mixture remaining in isotropic states to form a noncontaminated layer at the top surface. This preformed LCBCP layer preserves its inherent in-plane pattern and acts as a template guiding the subsequent micro-phase segregations of the other low-Tiso LCBCPs underneath. This self-template-assisted micro-phase segregation (STAMPS) readily provides 3D mesostructures, the potential toward rational material design of which is also demonstrated in water-separation applications.

Simple Synthesis of Elastomeric Photomechanical Switches That Self-Heal.

This article introduces a simple two-stage method to synthesize and program a photomechanical elastomer (PME) for light-driven artificial muscle-like actuations in soft robotics. First, photochromic azobenzene molecules are covalently attached to a polyurethane backbone via a two-part step-growth polymerization. Next, mechanical alignment is applied to induce anisotropic deformations in the PME-actuating films. Cross-linked through dynamic hydrogen bonds, the PMEs also possess autonomic self-healing properties without external energy input. This self-healing allows for a single alignment step of the PME film and subsequent "cut and paste" assembly for multi-axis actuation of a self-folded soft-robotic gripper from a single degree of freedom optical input.

A strategy for sequence control in vinyl polymers via iterative controlled radical cyclization.

There is a growing interest in sequence-controlled polymers toward advanced functional materials. However, control of side-chain order for vinyl polymers has been lacking feasibility in the field of polymer synthesis because of the inherent feature of chain-growth propagation. Here we show a general and versatile strategy to control sequence in vinyl polymers through iterative radical cyclization with orthogonally cleavable and renewable bonds. The proposed methodology employs a repetitive and iterative intramolecular cyclization via a radical intermediate in a one-time template with a radical-generating site at one end and an alkene end at the other, each of which is connected to a linker via independently cleavable and renewable bonds. The unique design specifically allowed control of radical addition reaction although inherent chain-growth intermediate (radical species) was used, as well as the iterative cycle and functionalization for resultant side chains, to lead to sequence-controlled vinyl polymers (or oligomers).

Embryonic Medaka Model of Microglia in the Developing CNS Allowing In Vivo Analysis of Their Spatiotemporal Recruitment in Response to Irradiation.

Radiation therapy (RT) is pivotal in the treatment of many central nervous system (CNS) pathologies; however, exposure to RT in children is associated with a higher risk of secondary CNS tumors. Although recent research interest has focused on the reparative and therapeutic role of microglia, their recruitment following RT has not been elucidated, especially in the developing CNS. Here, we investigated the spatiotemporal dynamics of microglia during tissue repair in the irradiated embryonic medaka brain by whole-mount in situ hybridization using a probe for Apolipoprotein E (ApoE), a marker for activated microglia in teleosts. Three-dimensional imaging of the distribution of ApoE-expressing microglia in the irradiated embryonic brain clearly showed that ApoE-expressing microglia were abundant only in the late phase of phagocytosis during tissue repair induced by irradiation, while few microglia expressed ApoE in the initial phase of phagocytosis. This strongly suggests that ApoE has a significant function in the late phase of phagocytosis by microglia in the medaka brain. In addition, the distribution of microglia in p53-deficient embryos at the late phase of phagocytosis was almost the same as in wild-type embryos, despite the low numbers of irradiation-induced apoptotic neurons, suggesting that constant numbers of activated microglia were recruited at the late phase of phagocytosis irrespective of the extent of neuronal injury. This medaka model of microglia demonstrated specific recruitment after irradiation in the developing CNS and could provide a useful potential therapeutic strategy to counteract the detrimental effects of RT.

Neurocytotoxic effects of iron-ions on the developing brain measured in vivo using medaka (Oryzias latipes), a vertebrate model.

PURPOSE: Exposure to heavy-ion radiation is considered a critical health risk on long-term space missions. The developing central nervous system (CNS) is a highly radiosensitive tissue; however, the biological effects of heavy-ion radiation, which are greater than those of low-linear energy transfer (LET) radiation, are not well studied, especially in vivo in intact organisms. Here, we examined the effects of iron-ions on the developing CNS using vertebrate organism, fish embryos of medaka (Oryzias latipes). MATERIALS AND METHODS: Medaka embryos at developmental stage 28 were irradiated with iron-ions at various doses of 0-1.5 Gy. At 24 h after irradiation, radiation-induced apoptosis was examined using an acridine orange (AO) assay and histologically. To estimate the relative biological effectiveness (RBE), we quantified only characteristic AO-stained rosette-shaped apoptosis in the developing optic tectum (OT). At the time of hatching, morphological abnormalities in the irradiated brain were examined histologically. RESULTS: The dose-response curve utilizing an apoptotic index for the iron-ion irradiated embryos was much steeper than that for X-ray irradiated embryos, with RBE values of 3.7-4.2. Histological examinations of irradiated medaka brain at 24 h after irradiation showed AO-positive rosette-shaped clusters as aggregates of condensed nuclei, exhibiting a circular hole, mainly in the marginal area of the OT and in the retina. However, all of the irradiated embryos hatched normally without apparent histological abnormalities in their brains. CONCLUSION: Our present study indicates that the medaka embryo is a useful model for evaluating neurocytotoxic effects on the developing CNS induced by exposure to heavy iron-ions relevant to the aerospace radiation environment.