Macromolecules最新文献

{"title":"Block Copolymer Nanocomposites under Soft Confinement","authors":"Javier Diaz, Marco Pinna, Andrei Zvelindovsky, Ignacio Pagonabarraga","doi":"10.1021/acs.macromol.4c03184","DOIUrl":"https://doi.org/10.1021/acs.macromol.4c03184","url":null,"abstract":"Block copolymer (BCP) melts can be blended with solvents to self-assemble into complex droplets with internal structures. Controlling the morphology of these softly confined structures is crucial for various applications, including drug delivery. The addition of nanoparticles (NPs) to BCP droplets produces hierarchical co-assembly with intricate structures, where BCPs act as scaffolds. However, incorporating NPs can significantly alter the BCP droplet structure, leading to emergent behavior. Computer simulations reveal that confinement-induced frustration leads to a Janus-like morphology, with spatially segregated hexagonal and lamellar structures within the droplet bulk. Systematic exploration of NP loading and chemical interactions demonstrates various phase transitions, which are rationalized based on changes in the effective composition and solubility of the BCP droplet. A time-dependent model enables the study of the kinetics of several NP-induced layered morphologies, indicating that changes in the effective solubility of the BCP droplet result in a slow progression toward an onion morphology.","PeriodicalId":51,"journal":{"name":"Macromolecules","volume":"78 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143945880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physics-Guided Neural Networks for Transferable Property Prediction in Architecturally Diverse Copolymers","authors":"Shengli Jiang,&nbsp; and ,&nbsp;Michael A. Webb*,&nbsp;","doi":"10.1021/acs.macromol.5c0072010.1021/acs.macromol.5c00720","DOIUrl":"https://doi.org/10.1021/acs.macromol.5c00720https://doi.org/10.1021/acs.macromol.5c00720","url":null,"abstract":"<p >The architectural, compositional, and chemical complexities of polymers are fundamentally important to their properties; however, these same factors obfuscate effective predictions. Machine learning offers a promising approach for predicting polymer properties, but model transferability remains a major challenge, particularly when data is scarce due to high acquisition costs or the growth of the parameter space. Here, we examine whether integration with polymer physics theory effectively enhances the transferability of machine learning models to predict properties of architecturally and compositionally diverse polymers. To do so, we first generate <span>ToPoRg-18k</span>─a data set reporting the moments of the distribution of squared radius of gyration for 18,450 polymers with diverse architectures, molecular weights, compositions, and chemical patterns. We then systematically assess the performance of several different models on a series of transferability tasks, such as predicting properties of high-molecular-weight systems from smaller ones or predicting properties of copolymers from homopolymers. We find that a tandem model, <span>GC-GNN</span>, which combines a graph neural network with a fittable model based on ideal Gaussian chain theory, surpasses both standalone polymer physics and graph neural network models in predictive accuracy and transferability. We also demonstrate that predictive transferability varies with polymer architecture due to deviations from the ideal Gaussian chain assumption. Furthermore, the integration with theory endows <span>GC-GNN</span> with additional interpretability, as its learned coefficients correlate strongly with polymer solvophobicity. Overall, this study illustrates the utility of combining polymer physics with data-driven models to improve predictive transferability for architecturally diverse copolymers, showcasing an extension of physics-informed machine learning for macromolecules.</p>","PeriodicalId":51,"journal":{"name":"Macromolecules","volume":"58 10","pages":"4971–4984 4971–4984"},"PeriodicalIF":5.1,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144137604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physics-Guided Neural Networks for Transferable Property Prediction in Architecturally Diverse Copolymers","authors":"Shengli Jiang, Michael A. Webb","doi":"10.1021/acs.macromol.5c00720","DOIUrl":"https://doi.org/10.1021/acs.macromol.5c00720","url":null,"abstract":"The architectural, compositional, and chemical complexities of polymers are fundamentally important to their properties; however, these same factors obfuscate effective predictions. Machine learning offers a promising approach for predicting polymer properties, but model transferability remains a major challenge, particularly when data is scarce due to high acquisition costs or the growth of the parameter space. Here, we examine whether integration with polymer physics theory effectively enhances the transferability of machine learning models to predict properties of architecturally and compositionally diverse polymers. To do so, we first generate <span>ToPoRg-18k</span>─a data set reporting the moments of the distribution of squared radius of gyration for 18,450 polymers with diverse architectures, molecular weights, compositions, and chemical patterns. We then systematically assess the performance of several different models on a series of transferability tasks, such as predicting properties of high-molecular-weight systems from smaller ones or predicting properties of copolymers from homopolymers. We find that a tandem model, <span>GC-GNN</span>, which combines a graph neural network with a fittable model based on ideal Gaussian chain theory, surpasses both standalone polymer physics and graph neural network models in predictive accuracy and transferability. We also demonstrate that predictive transferability varies with polymer architecture due to deviations from the ideal Gaussian chain assumption. Furthermore, the integration with theory endows <span>GC-GNN</span> with additional interpretability, as its learned coefficients correlate strongly with polymer solvophobicity. Overall, this study illustrates the utility of combining polymer physics with data-driven models to improve predictive transferability for architecturally diverse copolymers, showcasing an extension of physics-informed machine learning for macromolecules.","PeriodicalId":51,"journal":{"name":"Macromolecules","volume":"13 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143946370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Butterfly Patterns for Stretched Inhomogeneous Gel Networks Using Large-Scale Molecular Dynamics Simulations","authors":"Katsumi Hagita*,&nbsp; and ,&nbsp;Takahiro Murashima,&nbsp;","doi":"10.1021/acs.macromol.5c0020710.1021/acs.macromol.5c00207","DOIUrl":"https://doi.org/10.1021/acs.macromol.5c00207https://doi.org/10.1021/acs.macromol.5c00207","url":null,"abstract":"<p >Large-scale coarse-grained molecular dynamics simulations of inhomogeneous gel networks were performed to investigate abnormal butterfly patterns in 2D scattering patterns. The networks were diamond lattice-based with distributions in the number of beads between the cross-link points. Remarkably, the results confirm that the abnormal butterfly pattern originates from a stronger inhomogeneity. For the examined systems, the range of scattering wavevector <i>q</i> for the normal butterfly pattern was markedly different from those for the abnormal butterfly patterns. The findings address an essential aspect of the discrepancy between the theoretical prediction and experimental observations. We also confirmed that the peak position <i>q</i>_<i>x</i>* and intensity of the abnormal butterfly pattern decreases and increases, respectively, with increasing stretching ratio λ. As increasing inhomogeneity, it was found that the lower threshold of λ for the region where <i>q</i>_<i>x</i>* and λ have a linear relationship decreased and the peak intensity increased. This analytical approach to the abnormal butterfly pattern allows us to study the difference in network properties of gel networks for different random cross-linking conditions.</p>","PeriodicalId":51,"journal":{"name":"Macromolecules","volume":"58 10","pages":"5368–5376 5368–5376"},"PeriodicalIF":5.1,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144137489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Butterfly Patterns for Stretched Inhomogeneous Gel Networks Using Large-Scale Molecular Dynamics Simulations","authors":"Katsumi Hagita, Takahiro Murashima","doi":"10.1021/acs.macromol.5c00207","DOIUrl":"https://doi.org/10.1021/acs.macromol.5c00207","url":null,"abstract":"Large-scale coarse-grained molecular dynamics simulations of inhomogeneous gel networks were performed to investigate abnormal butterfly patterns in 2D scattering patterns. The networks were diamond lattice-based with distributions in the number of beads between the cross-link points. Remarkably, the results confirm that the abnormal butterfly pattern originates from a stronger inhomogeneity. For the examined systems, the range of scattering wavevector <i>q</i> for the normal butterfly pattern was markedly different from those for the abnormal butterfly patterns. The findings address an essential aspect of the discrepancy between the theoretical prediction and experimental observations. We also confirmed that the peak position <i>q</i>_<i>x</i>* and intensity of the abnormal butterfly pattern decreases and increases, respectively, with increasing stretching ratio λ. As increasing inhomogeneity, it was found that the lower threshold of λ for the region where <i>q</i>_<i>x</i>* and λ have a linear relationship decreased and the peak intensity increased. This analytical approach to the abnormal butterfly pattern allows us to study the difference in network properties of gel networks for different random cross-linking conditions.","PeriodicalId":51,"journal":{"name":"Macromolecules","volume":"19 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143933537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anisotropic Mixed Conduction of Electrons and Ions in Liquid Crystalline Supramolecular Complexes of Polythiophene and Imidazolium-Based Ionic Liquids","authors":"Nika Bondar, Abigail Slimp, Ruiqi Dong, Dahin Kim, Patrick Gruoner, Jason Lin, Chinedum O. Osuji, Shanju Zhang","doi":"10.1021/acs.macromol.5c00499","DOIUrl":"https://doi.org/10.1021/acs.macromol.5c00499","url":null,"abstract":"Mixed ionic-electronic conducting polymers (MIECPs) show promise for next-generation electrochemical devices due to the unique ability to simultaneously conduct both ions and electrons. However, there is a trade-off between electronic and ionic conduction because of their opposite morphology dependence. Here, we report simultaneous high electron-conduction and high ion-conduction in thin films of supramolecular MIECPs through the liquid crystalline (LC) assembly pathway from solution to the solid state. The supramolecular MIECPs are prepared via non-covalent bonding between carboxylated poly(3-alkyl thiophene)s and an imidazolium-based ionic liquid (IL) surfactant and characterized by means of UV–visible (UV–vis) absorption spectroscopy, polarized optical microscopy (POM) and small-angle X-ray scattering (SAXS). After complexation, the system displays colorimetric transitions and optoelectronic changes with the IL surfactant mole ratio. At equal stoichiometry, the polymer displays a rodlike conformation with planarization of the conjugated backbone. The hydrogel of the equimolar solution exhibits a typical LC polydomain texture with strong birefringence under POM, which is identified as a smectic LC mesophase with lamellar periodicity using SAXS. Defect-free LC monodomains containing unidirectional alignment are obtained in the hydrogel through mechanical shearing. After complete solvent evaporation, the LC monodomain structures are retained in the solid-state film, resulting in simultaneously high electronic (10^-2- 10^-1 mS/cm) and ionic (10^-3 - 10^-2 mS/cm) conductivities at ambient temperature. Generally, the block copolymers of MIECPs show high ionic conductivities (10^-2 - 1 mS/cm) but low electronic conductivities (10^-5 - 10^-2 mS/cm). While the homopolymers of MIECPs display high electronic conductivity (10^-6 - 10² mS/cm) but low ionic conductivity (10^-6 - 10^-2 mS/cm). In addition, aligned solid-state films show a significant anisotropy in both electronic (anisotropic ratio of ∼6) and ionic (anisotropic ratio of ∼117) conductivities, with faster charge transport along the shear direction than the perpendicular direction. It is believed that aligned conjugated backbones along the shear direction provide channels for fast band-like transport of electronic charge carriers and aligned imidazolium moieties in the lamellar layers form constrained channels for ion motion.","PeriodicalId":51,"journal":{"name":"Macromolecules","volume":"119 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143933540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rheological Properties and Gelation Behavior of Chitosan in a Weakly Alkaline NaHCO3/Urea Aqueous Solution","authors":"Haoyu Xin, Xuejie Yu, Yiwen Lu, Jie Cai","doi":"10.1021/acs.macromol.4c01673","DOIUrl":"https://doi.org/10.1021/acs.macromol.4c01673","url":null,"abstract":"Sustainable polymer materials derived from renewable resources have become increasingly important in addressing environmental challenges. Chitosan, a derivative of chitin, offers exceptional potential due to its unique biological and physicochemical properties. However, its practical application has been limited by the harsh conditions typically required for dissolution and processing. Here we demonstrate a novel approach using NaHCO₃/urea aqueous solution as a weakly alkaline solvent system that enables efficient chitosan processing under mild conditions. Through comprehensive rheological analysis, we reveal that the sol–gel transition of chitosan in NaHCO₃/urea aqueous solution is governed by the synergistic interplay of hydrogen bonding, hydrophobic interactions, and chain entanglements. The gelation behavior exhibits strong dependence on chitosan concentration and molecular weight, with higher values promoting robust network formation at lower temperatures. Notably, we discover a reversible sol–gel transition mechanism that enables precise control over material properties through temperature modulation, while maintaining long-term stability despite modest changes in molecular characteristics during storage. These findings advance our understanding of polysaccharide self-assembly in weakly alkaline media and establish a new paradigm for developing controllable chitosan-based materials under environmentally friendly conditions.","PeriodicalId":51,"journal":{"name":"Macromolecules","volume":"36 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143931092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rheological Properties and Gelation Behavior of Chitosan in a Weakly Alkaline NaHCO3/Urea Aqueous Solution","authors":"Haoyu Xin,&nbsp;Xuejie Yu,&nbsp;Yiwen Lu and Jie Cai*,&nbsp;","doi":"10.1021/acs.macromol.4c0167310.1021/acs.macromol.4c01673","DOIUrl":"https://doi.org/10.1021/acs.macromol.4c01673https://doi.org/10.1021/acs.macromol.4c01673","url":null,"abstract":"<p >Sustainable polymer materials derived from renewable resources have become increasingly important in addressing environmental challenges. Chitosan, a derivative of chitin, offers exceptional potential due to its unique biological and physicochemical properties. However, its practical application has been limited by the harsh conditions typically required for dissolution and processing. Here we demonstrate a novel approach using NaHCO₃/urea aqueous solution as a weakly alkaline solvent system that enables efficient chitosan processing under mild conditions. Through comprehensive rheological analysis, we reveal that the sol–gel transition of chitosan in NaHCO₃/urea aqueous solution is governed by the synergistic interplay of hydrogen bonding, hydrophobic interactions, and chain entanglements. The gelation behavior exhibits strong dependence on chitosan concentration and molecular weight, with higher values promoting robust network formation at lower temperatures. Notably, we discover a reversible sol–gel transition mechanism that enables precise control over material properties through temperature modulation, while maintaining long-term stability despite modest changes in molecular characteristics during storage. These findings advance our understanding of polysaccharide self-assembly in weakly alkaline media and establish a new paradigm for developing controllable chitosan-based materials under environmentally friendly conditions.</p>","PeriodicalId":51,"journal":{"name":"Macromolecules","volume":"58 10","pages":"5283–5295 5283–5295"},"PeriodicalIF":5.1,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144137547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-Durability Poly(dibenzofuran-co-terphenyl N-methylimidazole) Copolymer Membranes for High-Temperature Polymer Electrolyte Membrane Fuel Cells","authors":"Lele Wang, Sanser Celenk, Qian Wang, Qingfeng Li, Jingshuai Yang","doi":"10.1021/acs.macromol.5c00024","DOIUrl":"https://doi.org/10.1021/acs.macromol.5c00024","url":null,"abstract":"Phosphoric acid (PA)-doped polybenzimidazoles (PBIs) are a state-of-the-art membrane for high-temperature polymer electrolyte membrane fuel cells (HT-PEMFCs). Herein, we develop a new series of imidazole-containing copolymers with π-conjugated structures and multiple hydrogen bonding sites via straightforward polymerization of dibenzofuran, <i>p</i>-terphenyl, and 1-methyl-2-imidazolecarboxaldehyde. The high reactivity of the dibenzofuran monomer provides P(BF_<i>x</i>%-TP_<i>y</i>%-Im) copolymers with high viscosity, while the π-conjugated and hydrophilic furan units also serve as additional PA-binding sites that facilitate the acid doping and proton conduction. The resulting P(BF_20%-TP_80%-Im)/202%PA membrane demonstrates exceptional performance in H₂–O₂ and H₂–air fuel cells, achieving peak power densities of 1085 and 539 mW cm^–2 at 180 °C, respectively, under ambient pressure and humidification. Notably, the H₂–air cell equipped with this membrane shows remarkable stability, maintaining the high performance at 400 mA cm^–2 and 180 °C, with a voltage decay rate as low as 4.3 μV h^–1 over 720 h, likely the best durability result under these highly stressed conditions.","PeriodicalId":51,"journal":{"name":"Macromolecules","volume":"7 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143930880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-Durability Poly(dibenzofuran-co-terphenyl N-methylimidazole) Copolymer Membranes for High-Temperature Polymer Electrolyte Membrane Fuel Cells","authors":"Lele Wang,&nbsp;Sanser Celenk,&nbsp;Qian Wang,&nbsp;Qingfeng Li* and Jingshuai Yang*,&nbsp;","doi":"10.1021/acs.macromol.5c0002410.1021/acs.macromol.5c00024","DOIUrl":"https://doi.org/10.1021/acs.macromol.5c00024https://doi.org/10.1021/acs.macromol.5c00024","url":null,"abstract":"<p >Phosphoric acid (PA)-doped polybenzimidazoles (PBIs) are a state-of-the-art membrane for high-temperature polymer electrolyte membrane fuel cells (HT-PEMFCs). Herein, we develop a new series of imidazole-containing copolymers with π-conjugated structures and multiple hydrogen bonding sites via straightforward polymerization of dibenzofuran, <i>p</i>-terphenyl, and 1-methyl-2-imidazolecarboxaldehyde. The high reactivity of the dibenzofuran monomer provides P(BF_<i>x</i>%-TP_<i>y</i>%-Im) copolymers with high viscosity, while the π-conjugated and hydrophilic furan units also serve as additional PA-binding sites that facilitate the acid doping and proton conduction. The resulting P(BF_20%-TP_80%-Im)/202%PA membrane demonstrates exceptional performance in H₂–O₂ and H₂–air fuel cells, achieving peak power densities of 1085 and 539 mW cm^–2 at 180 °C, respectively, under ambient pressure and humidification. Notably, the H₂–air cell equipped with this membrane shows remarkable stability, maintaining the high performance at 400 mA cm^–2 and 180 °C, with a voltage decay rate as low as 4.3 μV h^–1 over 720 h, likely the best durability result under these highly stressed conditions.</p>","PeriodicalId":51,"journal":{"name":"Macromolecules","volume":"58 10","pages":"5344–5355 5344–5355"},"PeriodicalIF":5.1,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144137543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}