The transcription factor FoxP3 can fold into two dimerization states with divergent implications for regulatory T cell function and immune homeostasis.

FoxP3 is an essential transcription factor (TF) for immunologic homeostasis, but how it utilizes the common forkhead DNA-binding domain (DBD) to perform its unique function remains poorly understood. We here demonstrated that unlike other known forkhead TFs, FoxP3 formed a head-to-head dimer using a unique linker (Runx1-binding region [RBR]) preceding the forkhead domain. Head-to-head dimerization conferred distinct DNA-binding specificity and created a docking site for the cofactor Runx1. RBR was also important for proper folding of the forkhead domain, as truncation of RBR induced domain-swap dimerization of forkhead, which was previously considered the physiological form of FoxP3. Rather, swap-dimerization impaired FoxP3 function, as demonstrated with the disease-causing mutation R337Q, whereas a swap-suppressive mutation largely rescued R337Q-mediated functional impairment. Altogether, our findings suggest that FoxP3 can fold into two distinct dimerization states: head-to-head dimerization representing functional specialization of an ancient DBD and swap dimerization associated with impaired functions.

FOXP3 recognizes microsatellites and bridges DNA through multimerization.

FOXP3 is a transcription factor that is essential for the development of regulatory T cells, a branch of T cells that suppress excessive inflammation and autoimmunity1-5. However, the molecular mechanisms of FOXP3 remain unclear. Here we here show that FOXP3 uses the forkhead domain-a DNA-binding domain that is commonly thought to function as a monomer or dimer-to form a higher-order multimer after binding to TnG repeat microsatellites. The cryo-electron microscopy structure of FOXP3 in a complex with T3G repeats reveals a ladder-like architecture, whereby two double-stranded DNA molecules form the two 'side rails' bridged by five pairs of FOXP3 molecules, with each pair forming a 'rung'. Each FOXP3 subunit occupies TGTTTGT within the repeats in a manner that is indistinguishable from that of FOXP3 bound to the forkhead consensus motif (TGTTTAC). Mutations in the intra-rung interface impair TnG repeat recognition, DNA bridging and the cellular functions of FOXP3, all without affecting binding to the forkhead consensus motif. FOXP3 can tolerate variable inter-rung spacings, explaining its broad specificity for TnG-repeat-like sequences in vivo and in vitro. Both FOXP3 orthologues and paralogues show similar TnG repeat recognition and DNA bridging. These findings therefore reveal a mode of DNA recognition that involves transcription factor homomultimerization and DNA bridging, and further implicates microsatellites in transcriptional regulation and diseases.

Rice LIKE EARLY STARVATION1 cooperates with FLOURY ENDOSPERM6 to modulate starch biosynthesis and endosperm development.

In cereal grains, starch is synthesized by the concerted actions of multiple enzymes on the surface of starch granules within the amyloplast. However, little is known about how starch-synthesizing enzymes access starch granules, especially for amylopectin biosynthesis. Here, we show that the rice (Oryza sativa) floury endosperm9 (flo9) mutant is defective in amylopectin biosynthesis, leading to grains exhibiting a floury endosperm with a hollow core. Molecular cloning revealed that FLO9 encodes a plant-specific protein homologous to Arabidopsis (Arabidopsis thaliana) LIKE EARLY STARVATION1 (LESV). Unlike Arabidopsis LESV, which is involved in starch metabolism in leaves, OsLESV is required for starch granule initiation in the endosperm. OsLESV can directly bind to starch by its C-terminal tryptophan (Trp)-rich region. Cellular and biochemical evidence suggests that OsLESV interacts with the starch-binding protein FLO6, and loss-of-function mutations of either gene impair ISOAMYLASE1 (ISA1) targeting to starch granules. Genetically, OsLESV acts synergistically with FLO6 to regulate starch biosynthesis and endosperm development. Together, our results identify OsLESV-FLO6 as a non-enzymatic molecular module responsible for ISA1 localization on starch granules, and present a target gene for use in biotechnology to control starch content and composition in rice endosperm.

LncRNA-disease association identification using graph auto-encoder and learning to rank.

Discovering the relationships between long non-coding RNAs (lncRNAs) and diseases is significant in the treatment, diagnosis and prevention of diseases. However, current identified lncRNA-disease associations are not enough because of the expensive and heavy workload of wet laboratory experiments. Therefore, it is greatly important to develop an efficient computational method for predicting potential lncRNA-disease associations. Previous methods showed that combining the prediction results of the lncRNA-disease associations predicted by different classification methods via Learning to Rank (LTR) algorithm can be effective for predicting potential lncRNA-disease associations. However, when the classification results are incorrect, the ranking results will inevitably be affected. We propose the GraLTR-LDA predictor based on biological knowledge graphs and ranking framework for predicting potential lncRNA-disease associations. Firstly, homogeneous graph and heterogeneous graph are constructed by integrating multi-source biological information. Then, GraLTR-LDA integrates graph auto-encoder and attention mechanism to extract embedded features from the constructed graphs. Finally, GraLTR-LDA incorporates the embedded features into the LTR via feature crossing statistical strategies to predict priority order of diseases associated with query lncRNAs. Experimental results demonstrate that GraLTR-LDA outperforms the other state-of-the-art predictors and can effectively detect potential lncRNA-disease associations. Availability and implementation: Datasets and source codes are available at http://bliulab.net/GraLTR-LDA.

"Atomic Topping" of MnOx on Al2O3 to Create Electron-Rich, Aperiodic, Lattice Oxygens that Resemble Noble Metals for Catalytic Oxidation.

Enhancing the catalytic oxidation activity of traditional transition-metal oxides to rival that of noble metals has been a prominent focus in the field of catalysis. However, existing synthesis strategies that focus on controlling the electronic states of metal centers have not yet fully succeeded in achieving this goal. Our current research reveals that manipulating the electronic states of oxygen centers can yield unexpected results. By creating electron-rich, aperiodic lattice oxygens through atomic topping of MnOx, we have produced a catalyst with performance that closely resembles supported Pt. Spherical aberration-corrected transmission electron microscopy and X-ray absorption spectra have confirmed that the atomic topping of the MnOx layer on Al2O3 can form an aperiodic arrangement oxide structure. Near-ambient pressure X-ray photoelectron spectroscopy, in situ diffuse reflectance infrared Fourier transform spectroscopy, reaction kinetics test, and theoretical calculations demonstrated that this structure significantly increases the electron density around the oxygen in MnOx, shifting the activation center for CO adsorption from Mn to O, thereby exhibiting catalytic activity and stability close to that of the precious metal Pt. This study presents a fresh perspective on designing efficient oxide catalysts by targeting electron-rich anionic centers, thereby deepening the understanding of how these centers can be altered to enhance catalytic efficiency in oxidation reactions.

iSnoDi-LSGT: identifying snoRNA-disease associations based on local similarity constraints and global topological constraints.

Growing evidence proves that small nucleolar RNAs (snoRNAs) have important functions in various biological processes, the malfunction of which leads to the emergence and development of complex diseases. However, identifying snoRNA-disease associations is an ongoing challenging task due to the considerable time- and money-consuming biological experiments. Therefore, it is urgent to design efficient and economical methods for the identification of snoRNA-disease associations. In this regard, we propose a computational method named iSnoDi-LSGT, which utilizes snoRNA sequence similarity and disease similarity as local similarity constraints. The iSnoDi-LSGT predictor further employs network embedding technology to extract topological features of snoRNAs and diseases, based on which snoRNA topological similarity and disease topological similarity are calculated as global topological constraints. To the best of our knowledge, the iSnoDi-LSGT is the first computational method for snoRNA-disease association identification. The experimental results indicate that the iSnoDi-LSGT predictor can effectively predict unknown snoRNA-disease associations. The web server of the iSnoDi-LSGT predictor is freely available at http://bliulab.net/iSnoDi-LSGT.

idenMD-NRF: a ranking framework for miRNA-disease association identification.

Identifying miRNA-disease associations is an important task for revealing pathogenic mechanism of complicated diseases. Different computational methods have been proposed. Although these methods obtained encouraging performance for detecting missing associations between known miRNAs and diseases, how to accurately predict associated diseases for new miRNAs is still a difficult task. In this regard, a ranking framework named idenMD-NRF is proposed for miRNA-disease association identification. idenMD-NRF treats the miRNA-disease association identification as an information retrieval task. Given a novel query miRNA, idenMD-NRF employs Learning to Rank algorithm to rank associated diseases based on high-level association features and various predictors. The experimental results on two independent test datasets indicate that idenMD-NRF is superior to other compared predictors. A user-friendly web server of idenMD-NRF predictor is freely available at http://bliulab.net/idenMD-NRF/.

A fast microbial nitrogen-assimilation technology enhances nitrogen migration and single-cell-protein production in high-ammonia piggery wastewater.

Conventional methods, such as freshwater dilution and ammonia stripping, have been widely employed for microalgae-based piggery wastewater (PW) treatment, but they cause high freshwater consumption and intensive ammonia loss, respectively. This present work developed a novel fast microbial nitrogen-assimilation technology by integrating nitrogen starvation, zeolite-based adsorption, pH control, and co-culture of microalgae-yeast for the PW treatment. Among them, the nitrogen starvation accelerated the nitrogen removal and shortened the treatment period, but it could not improve the tolerance level of microalgal cells to ammonia toxicity based on oxidative stress. Therefore, zeolite was added to reduce the initial total ammonia-nitrogen concentration to around 300 mg/L by ammonia adsorption. Slowly releasing ammonia at the later phase maintained the total ammonia-nitrogen concentration in the PW. However, the pH increase could cause lots of ammonia loss air and pollution and inhibit the desorption of ammonia from zeolite and the growth and metabolism of microalgae during the microalgae cultivation. Thus, the highest biomass yield (3.25 g/L) and nitrogen recovery ratio (40.31%) were achieved when the pH of PW was controlled at 6.0. After combining the co-cultivation of microalgae-yeast, the carbon-nitrogen co-assimilation and the alleviation of pH fluctuation further enhanced the nutrient removal and nitrogen migration to high-protein biomass. Consequently, the fast microbial nitrogen-assimilation technology can help update the industrial system for high-ammonia wastewater treatment by improving the treatment and nitrogen recovery rates.

Electrocoagulation enhanced gravity driven membrane bioreactor for advanced treatment of rural sewage.

The daily discharge of rural sewage in China occupies 30 % of the national wastewater discharge, and developing an energy-efficient, easy to operate, and decentralized rural sewage treatment technology becomes an important task. In this work, a novel rural sewage treatment technology, Electrocoagulation enhanced Gravity-Driven Membrane Bioreactor (EC-GDMBR) was exploited for the rural sewage treatment under long-term operation (160 days). Two EC-GDMBRs with various module structures of ceramic membrane (horizontal module and side module) not only displayed the desirable effluent quality, but also sustained the stable flux (8-13 LMH). The electrocoagulation, electrooxidation, biodegradation, and separation in EC-GDMBRs were able to synergistically remove the particle matter, organic (CODCr effluent <11.6 ± 1.2 mg/L) and nutrients (NH3-N effluent <0.1 mg/L, TN effluent <8.5 mg/L, TP effluent <0.05 mg/L). Besides, the high permeability of ceramic membrane and large porosity of biofilm on its surface improved the sustainability of stable flux during the long-term operation. Moreover, by analyzing bacterial abundance, Extracellular Polymeric Substances, Adenosine Tri-Phosphate and Confocal Laser Scanning Microscopy, a large number of microorganisms grew and accumulated on the carrier, as well as formed the biofilm (23.46-659.9 µm), while Nitrobacteria (1.6-4.1 %) and Nitrate (0.01-0.06 %) exited in the carrier biofilms, promoting the nitrogen removal. Compared with EC-GDMBR with side module of ceramic membrane, EC-GDMBR with horizontal module of ceramic membrane has advantages in flux behavior, organic/nutrient removal, microbial abundance/activity, abundance of nitrogen removal functional bacteria and water permeability of biofilm, because the ceramic membrane of horizontal module can promote the uniform growth of biofilm and improve the uniformity of flow penetration distribution. In general, the findings of this work verify the reliability of EC-GDMBR for the sustainable operation of wastewater treatment and improve its application value of rural sewage treatment.

[Comparative Study of the Embryo Development and Clinical Outcomes of 3 Ovarian Stimulation Protocols in Different Age Groups]. / 不同年龄段人群三种促排卵方案胚胎发育及临床结局比较.

Objective: The main purpose of this study is to compare the embryo development and clinical outcomes of women in different age groups undergoing in vitro fertilization (IVF) processes using gonadotrophin-releasing hormone (GnRH) antagonist protocol, GnRH agonist long protocol, and early follicular phase protocol. We aim to provide reliable reference for future clinical treatments. Methods: We conducted a detailed analysis of patients who underwent treatment between January 2021 and February 2023. 1) In the overall patient population, we comprehensively compared the basic characteristics, the embryo development, and the clinical outcomes of patients treated with three different ovarian stimulation protocols, including the GnRH antagonist protocol group (n=4173), the agonist long protocol group (n=2410), and the early follicular phase long protocol group (n=341). 2) We divided the overall population into three age groups, one group for patients under 30 years old (n=2576), one for patients aged 30-35 (n=3249), and one for patients older than 35 years old (n=1099). Then, we compared the three stimulation protocols based on the group division. We separately compared the embryo development and clinical outcomes of patients using the three stimulation protocols in the under 30 years old, the 30-35 years old, and the over 35 years old age groups. With this analysis, we aimed to explore the response of different age groups to different stimulation protocols and their impact on the success rate of IVF. Results: 1) In the overall population, we found that the average number of oocytes retrieved in the GnRH agonist long protocol group was significantly higher than that in the GnRH antagonist protocol group ([13.85±7.162] vs. [13.36±7.862], P=0.0224), as well as the early follicular phase long protocol group ([13.85±7.162] vs. [11.86±6.802], P<0.0001). Patients in the GnRH antagonist protocol group not only had a significantly lower starting dose of gonadotrophin (Gn) compared to the other two groups (P<0.05) but also had a significantly lower number of days of Gn use (P<0.05). The blastocyst formation rate in the GnRH antagonist protocol group was the highest among the three groups, significantly higher compared to the GnRH agonist long protocol group (64.91% vs. 62.35%, P<0.0001) and the early follicular phase long protocol group (64.91% vs. 61.18%, P=0.0001). However, there were no significant differences in the clinical pregnancy rates or the live birth rates among the three groups treated with different ovarian stimulation protocols (P>0.05). 2) In the <30 age group, the blastocyst formation rate in the GnRH antagonist protocol group was the highest among the three groups, significantly higher compared to the GnRH agonist long protocol group (66.12% vs. 63.33%, P<0.0001) and the early follicular phase long protocol group (66.12% vs. 62.13%, P=0.0094). In the 30-35 age group, the blastocyst formation rate in the GnRH antagonist protocol group was the highest among the three groups, significantly higher compared to the GnRH agonist long protocol group (64.88% vs. 62.93%, P=0.000 9) and the early follicular phase long protocol group (64.88% vs. 60.39%, P=0.0011). In the >35 age group, the blastocyst formation rate in the GnRH antagonist protocol group was significantly higher than that in the GnRH agonist long protocol group (59.83% vs. 56.51%, P=0.0093), while there was no significant difference compared to that of the early follicular phase long protocol group (P>0.05). In the three age groups, we found that there were no significant differences in clinical pregnancy rate, live birth rate, and neonatal outcome indicators (fetal weight and Apgar score) among the three stimulation protocols (antagonist protocol, GnRH agonist long protocol, and early follicular phase long protocol) (P>0.05). The findings showed no significant differences between clinical and neonatal outcomes in patients of all ages, regardless of the ovarian stimulation protocol, suggesting that the three ovarian stimulation protocols have similar therapeutic effects in patients of different ages. The results of this study have important implications for the selection of an appropriate ovarian stimulation protocol and the prediction of treatment outcomes. Conclusion: In the younger than 30 and 30-35 age groups, the GnRH antagonist protocol showed a more significant advantage over the GnRH agonist long protocol and the early follicular phase long protocol. This suggests that for younger and middle-aged patients, the antagonist protocol may lead to better outcomes during ovarian stimulation. In the older than 35 age group, while the antagonist protocol still outperformed the GnRH agonist long protocol, there was no significant difference compared to the early follicular phase long protocol. This may imply that with increasing age, the early follicular phase long protocol may have effects similar to the antagonist protocol to some extent. The advantages of the antagonist protocol lie in its ability to reduce stimulation duration and the dosage of GnRH, while enhancing patient compliance with treatment. This means that patients may find it easier to accept and adhere to this treatment protocol, thereby improving treatment success rates. Particularly for older patients, the use of the antagonist protocol may significantly increase the blastocyst formation rate, which is crucial for improving the success rates. Although there were no significant differences in the clinical outcomes of patients treated with the three protocols in each age group, further research is still needed to validate these findings. Future multicenter studies and increased sample sizes may help comprehensively assess the efficacy of different stimulation protocols. Additionally, prospective studies are needed to further validate these findings and determine the optimal treatment strategies.

Dual function of VGLL4 in muscle regeneration.

VGLL4 has previously been identified as a negative regulator of YAP. Here we show that VGLL4 regulates muscle regeneration in both YAP-dependent and YAP-independent manners at different stages. Knockout of VGLL4 in mice leads to smaller myofiber size and defective muscle contraction force. Furthermore, our studies reveal that knockout of VGLL4 results in increased muscle satellite cells proliferation and impaired myoblast differentiation, which ultimately leads to delayed muscle regeneration. Mechanistically, the results show that VGLL4 works as a conventional repressor of YAP at the proliferation stage of muscle regeneration. At the differentiation stage, VGLL4 acts as a co-activator of TEAD4 to promote MyoG transactivation and facilitate the initiation of differentiation in a YAP-independent manner. Moreover, VGLL4 stabilizes the protein-protein interactions between MyoD and TEAD4 to achieve efficient MyoG transactivation. Our findings define the dual roles of VGLL4 in regulating muscle regeneration at different stages and may open novel therapeutic perspectives for muscle regeneration.

Dispersing LiCl in Zwitterionic COF for Highly Efficient Ammonia Storage and Separation.

Efficient and inherently safe NH3 storage and separation are of significant importance for the chemical industry. Herein, we proposed zwitterionic COF as a porous host to disperse LiCl for highly efficient NH3 storage and separation with record adsorption capacity. The equivalently cationic and anionic groups in the channels of zwitterionic COF could act as two separated sites to facilitate the dispersion of LiCl, hence the optimal composite exhibits a high capture capacity of 44.98 mmol/g at 25 °C and 1 bar, far exceeding other existing porous materials. Notably, the adsorption capacity is completely reversible and the efficient separation of NH3 from NH3 /CO2 /N2 mixture is achieved through breakthrough experiments. DFT calculation combined with XPS and 7 Li NMR experimental results give insight into the interaction between zwitterionic COF and LiCl. This work extends possibilities for the development of efficient adsorbents for NH3 storage and separation.

iPiDA-LTR: Identifying piwi-interacting RNA-disease associations based on Learning to Rank.

Piwi-interacting RNAs (piRNAs) are regarded as drug targets and biomarkers for the diagnosis and therapy of diseases. However, biological experiments cost substantial time and resources, and the existing computational methods only focus on identifying missing associations between known piRNAs and diseases. With the fast development of biological experiments, more and more piRNAs are detected. Therefore, the identification of piRNA-disease associations of newly detected piRNAs has significant theoretical value and practical significance on pathogenesis of diseases. In this study, the iPiDA-LTR predictor is proposed to identify associations between piRNAs and diseases based on Learning to Rank. The iPiDA-LTR predictor not only identifies the missing associations between known piRNAs and diseases, but also detects diseases associated with newly detected piRNAs. Experimental results demonstrate that iPiDA-LTR effectively predicts piRNA-disease associations outperforming the other related methods.

Ionic COF Composite Membranes for Selective Perfluoroalkyl Substances Separation.

High-performance membranes are critical to membrane separation technology. In recent years, 2D covalent organic frameworks (2D COFs) have attracted extensive attention in the field of membrane separation due to their high porosity, ordered channels, and fine-tuned pore sizes, which are considered as excellent candidate to solve the trade-off between membrane selectivity and permeability. Herein, two kinds of ionic 2D COFs with different charge properties (termed as iCOFs) are integrated into polyacrylonitrile (PAN) substrates to form two composite membranes (PAN@iCOFs) with excellent selective perfluoroalkyl substances (PFASs) separation performance with high solvent permeability and good mechanical properties. The as-prepared PAN@iCOFs composite membranes can selectively reject more than 99.0% of positively and negatively charged PFASs in wastewater while maintaining good stability and recyclability.

Absolute CO2 /Xenon Separation in Ultramicropore MOF for Anesthetic Gases Regeneration.

Xe is an ideal anesthetic gas, but it has not been widely used in practice due to its high cost and low output. Closed-circuit Xe recovery and recycling is an economically viable method to ensure adequate supply in medical use. Herein, we design an innovative way to recover Xe by using a stable fluorinated metal-organic framework (MOF) NbOFFIVE-1-Ni to eliminate CO2 from moist exhaled anesthetic gases. Unlike other Xe recovery MOFs with low Xe/CO2 selectivity (less than 10), NbOFFIVE-1-Ni could achieve absolute molecular sieve separation of CO2 /Xe with excellent CO2 selectivity (825). Mixed-gas breakthrough experiments assert the potential of NbOFFIVE-1-Ni as a molecular sieve adsorbent for the effective and energy-efficient removal of carbon dioxide with 99.16 % Xe recovery. Absolute CO2 /Xe separation in NbOFFIVE-1-Ni makes closed-circuit Xe recovery and recycling can be easily realized, demonstrating the potential of NbOFFIVE-1-Ni for important anesthetic gas regeneration under ambient conditions.

HF Resistant Porous Aromatic Frameworks for Electronic Special Gases Separation.

Here we report two HF acid resistant porous aromatic frameworks as adsorbents for high value-added electronic special gases (e.g., SF6, NF3, CF4, Xe, Kr) separation. The New-PAF-1 and N-SO3H exhibit exceptional adsorption selectivity for Xe and F-gases from semiconductor exhaust gas along with high physicochemical stability and excellent reusability, which have been collaboratively confirmed by single-component gas adsorption experiments, time-dependent adsorption rate tests, dynamic breakthrough experiments and regeneration tests. The theoretical calculations based on DFT and Mulliken atomic charge analyses elucidated the adsorption mechanism of New-PAF-1 and N-SO3H toward F-gases, Xe, Kr, and N2 at molecular level, including adsorption site, binding energy and electrostatic potentials distribution. The systematic investigation sufficiently manifests that PAFs can act as highly stable porous adsorbents in harsh operating conditions.

The interfacial interactions of nanomaterials with human serum albumin.

The fates of nanomaterials (NMs) in vivo are greatly dependent on their interactions with human serum proteins. However, the interfacial molecular details of NMs-serum proteins are still difficult to be probed. Herein, the molecular interaction details of human serum albumin (HSA) with Au and SiO2 nanoparticles have been systematically interrogated and compared by using lysine reactivity profiling mass spectrometry (LRP-MS). We demonstrated the biocompatibility of Au is better than SiO2 nanoparticles and the NMs surface charge state played a more important role than particle size in the combination of NMs-HSA at least in the range of 15-40 nm. Our results will contribute to the fundamental mechanism understanding of NMs-serum protein interactions as well as the NMs rational design.

Life cycle assessment of combustion-based electricity generation technologies integrated with carbon capture and storage: A review.

Carbon capture and storage (CCS) is the key technology to reduce CO2 emissions from the conventional power systems. CCS has the flexibility, compatibility, and great potential to reduce emissions when combined with the current energy infrastructure. Through quantifying the environmental benefits of the combustion-based electricity generation system with CCS by life cycle assessment (LCA), decision-makers can grasp the contribution of upstream and downstream processes to various environmental impacts, a better trade-off between climate change and non-climate impact categories. This work reviews the LCA research on the combustion-based electricity generation system integrated with CCS in the past 10 years. These studies show that CCS can reduce the direct CO2 emissions from power plants by nearly 90%. While CCS effectively mitigates climate change, it also increases other environmental impacts to varying degrees and results in energy penalty of 15-44%. The actual greenhouse gas of the power plant is reduced by 40-80%. We further analyze a series of key issues involved in the LCA of the combustion-based electricity generation system integrated with CCS, including the functional unit, basic assumptions, system boundaries and assessment methods. Time span and the leakage need to be considered by researchers in LCA. The perspective of research needs to shift from the specific application of a single CCS to the impact assessment of large-scale deployment, and a single environment or economic discipline to interdisciplinary assessment. It is more cost-effective to realize the coordinated emission reduction between the power plant and the upstream and downstream supply chain.

Fluorine-Containing Flow Modifier for BN/PPS Composites Enabled by Low Surface Energy.

In this study, a fluorine-containing flow modifier (Si-DF) with low surface energy is successfully synthesized, which is applied to fabricate ideal electronic packaging materials (BN/PPS composites) with high thermal conductivity, excellent dielectric properties, processability, and toughness by conventional melt blending. Si-DPF is located at the interface between the BN fillers and the PPS matrix, which not only improves the dispersion of BN fillers but also strengthens the interaction. With the help of 5 wt% Si-DF, BN/PPS/Si-DF (70/25/5) still exhibits the high thermally conductive coefficient (3.985 W/m·K) and low dielectric constant (3.76 at 100 MHz) although BN fillers are loaded as high as 70 wt%. Moreover, the sample processes a lower stable torque value (2.5 N·m), and the area under the stress-strain curves is also increased. This work provides an efficient way to develop high-performance polymer-based composites with high thermally conductive coefficients and low dielectric constants for electronic packaging applications.

The Fabrication of High-Hardness and Transparent PMMA-Based Composites by an Interface Engineering Strategy.

The high-hardness and transparent PMMA-based composites play a significant role in modern optical devices. However, a well-known paradox is that conventional PMMA-based composites with high loadings of nanoparticles usually possess high surface hardness at the cost of poor transparency and toughness due to the aggregation of nanoparticles. In this work, ideal optical materials (SiO2/PMMA composites) with high transparency and high surface hardness are successfully fabricated through the introduction of the flow modifier Si-DPF by conventional melt blending. Si-DPF with low surface energy and high transparency, which is located at the SiO2/PMMA interface, and nano-SiO2 particles are homogeneously dispersed in the PMMA matrix. As an example, the sample SiO2/PMMA/Si-DPF (30/65/5) shows outstanding transparency (>87.2% transmittance), high surface hardness (462.2 MPa), and notched impact strength (1.18 kJ/m2). Moreover, SiO2/PMMA/Si-DPF (30/65/5) also presents a low torque value of composite melt (21.7 N⋅m). This work paves a new possibility for the industrial preparation of polymer-based composites with excellent transparency, surface hardness, processability, and toughness.