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One of the key design factors that regulate the properties of grafted nanoparticles (GNPs) and their self-assembly is the conformation of the grafted polymer. On the curved surface of the GNP core, the conformation of the polymer chain is not uniform in the radial direction. The segment is a non-Gaussian chain in the concentrated polymer brush (CPB) regime near the interface between GNP core and grafted polymer, while it is less constrained in the semidilute polymer brush (SDPB) regime near the surface of GNP. Here, the property of polymer conformation showing crossover behavior at the CPB/SDPB threshold through the coarse-grain molecular dynamics simulation of nanoparticles with explicit grafted chains is explored. Moreover, the self-assembly structure depends on the effective softness, which is defined as a function of the threshold of two regimes estimated from the conformation of the polymer.
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The investigation of bottlebrush copolymer self-assembly in solution involves a comprehensive approach integrating simulation and experimental research, due to their unique physical characteristics. However, the intricate architecture of bottlebrush copolymers and the diverse solvent conditions introduce a wide range of parameter spaces. In this study, we investigated the solution self-assembly behavior of bottlebrush copolymers by combining dissipative particle dynamics (DPD) simulation results and machine learning (ML) including graph convolutional networks (GCNs). The architecture of bottlebrush copolymers is encoded by graphs including connectivity, side chain length, bead types, and interaction parameters of DPD simulation. Using GCN, we accurately predicted the single chain properties of bottlebrush copolymers with over 95% accuracy. Furthermore, phase behavior was precisely predicted using these single chain properties. Shapley additive explanations (SHAP) values of single chain properties to the various self-assembly morphologies were calculated to investigate the correlation between single chain properties and morphologies. In addition, we analyzed single chain properties and phase behavior as a function of DPD interaction parameters, extracting relevant physical properties for vesicle morphology formation. This work paves the way for tailored design in solution of self-assembled nanostructures of bottlebrush copolymers, offering a GCN framework for precise prediction of self-assembly morphologies under various chain architectures and solvent conditions.
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The goal of most materials discovery is to discover materials that are superior to those currently known. Fundamentally, this is close to extrapolation, which is a weak point for most machine learning models that learn the probability distribution of data. Herein, we develop reinforcement learning-guided combinatorial chemistry, which is a rule-based molecular designer driven by trained policy for selecting subsequent molecular fragments to get a target molecule. Since our model has the potential to generate all possible molecular structures that can be obtained from combinations of molecular fragments, unknown molecules with superior properties can be discovered. We theoretically and empirically demonstrate that our model is more suitable for discovering better compounds than probability distribution-learning models. In an experiment aimed at discovering molecules that hit seven extreme target properties, our model discovered 1315 of all target-hitting molecules and 7629 of five target-hitting molecules out of 100 000 trials, whereas the probability distribution-learning models failed. Moreover, it has been confirmed that every molecule generated under the binding rules of molecular fragments is 100% chemically valid. To illustrate the performance in actual problems, we also demonstrate that our models work well on two practical applications: discovering protein docking molecules and HIV inhibitors.
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In Li metal batteries (LMBs), which boast the highest theoretical capacity, the chemical structure of the solid electrolyte interphase (SEI) serves as the key component that governs the growth of reactive Li. Various types of additives have been developed for electrolyte optimization, representing one of the most effective strategies to enhance the SEI properties for stable Li plating. However, as advanced electrolyte systems become more chemically complicated, the use of additives is empirically optimized. Indeed, their role in SEI formation and the resulting cycle life of LMBs are not well-understood. In this study, we employed cryogenic transmission electron microscopy combined with Raman spectroscopy, theoretical studies including molecular dynamics (MD) simulations and density functional theory (DFT) calculations, and electrochemical measurements to explore the nanoscale architecture of SEI modified by the most representative additives, lithium nitrate (LiNO3) and vinylene carbonate (VC), applied in a localized high-concentration electrolyte. We found that LiNO3 and VC play distinct roles in forming the SEI, governing the solvation structure, and influencing the kinetics of electrochemical reduction. Their collaboration leads to the desired SEI, ensuring prolonged cycle performance for LMBs. Moreover, we propose mechanisms for different Li growth and cycling behaviors that are determined by the physicochemical properties of SEI, such as uniformity, elasticity, and ionic conductivity. Our findings provide critical insights into the appropriate use of additives, particularly regarding their chemical compatibility.
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Metal nanoclusters (NCs) are a special class of nanoparticles composed of a precise number of metal atoms and ligands. Because the proportion of ligands to metal atoms is high in metal NCs, the ligand type determines the physical properties of metal NCs. Furthermore, ligands presumably govern the entire formation process of the metal NCs. However, their roles in the synthesis, especially as factors in the uniformity of metal NCs, are not understood. It is because the synthetic procedure of metal NCs is highly convoluted. The synthesis is initiated by the formation of various metal-ligand complexes, which have different numbers of atoms and ligands, resulting in different coordinations of metal. Moreover, these complexes, as actual precursors to metal NCs, undergo sequential transformations into a series of intermediate NCs before the formation of the desired NCs. Thus, to resolve the complicated synthesis of metal NCs and achieve their uniformity, it is important to investigate the reactivity of the complexes. Herein, we utilize a combination of mass spectrometry, density functional theory, and electrochemical measurements to understand the ligand effects on the reactivity of AuI-thiolate complexes toward the reductive formation of Au NCs. We discover that the stability of the complexes can be increased by either van der Waals interactions induced by the long carbon chain of ligands or by non-thiol functional groups in the ligands, which additionally coordinate with AuI in the complexes. Such structural effects of thiol ligands determine the reduction reactivity of the complexes and the amount of NaBH4 required for the controlled synthesis of the Au NCs.
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The chemical degradation of 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO)-based aqueous energy storage and catalytic systems is pH sensitive. Herein, we voltammetrically monitor the local pH (pHlocal) at a Pt ultramicroelectrode (UME) upon electro-oxidation of imidazolium-linker functionalized TEMPO and show that its decrease is associated with the greater acidity of the cationic (oxidized) rather than radical (reduced) form of TEMPO. The protons that drive the decrease in pH arise from hydrolysis of the conjugated imidazolium-linker functional group of 4-[2-(N-methylimidazolium)acetoxy]-2,2,6,6-tetramethylpiperidine-1-oxyl chloride (MIMAcO-T), which was studied in comparison with 4-hydroxyl-TEMPO (4-OH-T). Voltammetric hysteresis is observed during the electrode oxidation of 4-OH-T and MIMAcO-T at a Pt UME in an unbuffered aqueous solution. The hysteresis arises from the pH-dependent formation and dissolution of Pt oxides, which interact with pHlocal in the vicinity of the UME. We find that electrogenerated MIMAcO-T+ significantly influences pHlocal, whereas 4-OH-T+ does not. Finite element analysis reveals that the thermodynamic and kinetic acid-base properties of MIMAcO-T+ are much more favorable than those of its reduced counterpart. Imidazolium-linker functionalized TEMPO molecules comprising different linking groups were also investigated. Reduced TEMPO molecules with carbonyl linkers behave as weak acids, whereas those with alkyl ether linkers do not. However, oxidized TEMPO+ molecules with alkyl ether linkers exhibit more facile acid-base kinetics than those with carbonyl ones. Density functional theory calculations confirm that OH- adduct formation on the imidazolium-linker functional group of TEMPO is responsible for the difference in the acid-base properties of the reduced and oxidized forms.
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The advanced patterning process is the basis of integration technology to realize the development of next-generation high-speed, low-power consumption devices. Recently, area-selective atomic layer deposition (AS-ALD), which allows the direct deposition of target materials on the desired area using a deposition barrier, has emerged as an alternative patterning process. However, the AS-ALD process remains challenging to use for the improvement of patterning resolution and selectivity. In this study, we report a superlattice-based AS-ALD (SAS-ALD) process using a two-dimensional (2D) MoS2-MoSe2 lateral superlattice as a pre-defining template. We achieved a minimum half pitch size of a sub-10 nm scale for the resulting AS-ALD on the 2D superlattice template by controlling the duration time of chemical vapor deposition (CVD) precursors. SAS-ALD introduces a mechanism that enables selectivity through the adsorption and diffusion processes of ALD precursors, distinctly different from conventional AS-ALD method. This technique facilitates selective deposition even on small pattern sizes and is compatible with the use of highly reactive precursors like trimethyl aluminum. Moreover, it allows for the selective deposition of a variety of materials, including Al2O3, HfO2, Ru, Te, and Sb2Se3.
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Technologies that detect circularly polarized light (CPL), particularly in the UV region, have significant potential for various applications, including bioimaging and optical communication. However, a major challenge in directly sensing CPL arises from the conflicting requirements of planar structures for efficient charge transport and distorted structures for effective interaction with CPL. Here, a novel design of an axially chiral n-type organic semiconductor is presented to surmount the challenge, in which a binaphthyl group results in a high dissymmetry factor at the molecular level, while maintaining excellent electron-transporting characteristics through the naphthalene diimide group. Experimental and computational methods reveal different stacking behaviors in homochiral and heterochiral assemblies, yielding different structures: Nanowires and nanoparticles, respectively. Especially, the homochiral assemblies exhibit effective π-π stacking between naphthalene diimides despite axial chirality. Thus, phototransistors fabricated using enantiomers exhibit a high maximum electron mobility of 0.22 cm2 V-1 s-1 and a detectivity of 3.9 × 1012 Jones, alongside the CPL distinguishing ability with a dissymmetry factor of responsivity of 0.05. Furthermore, the material possesses a wide bandgap, contributing to its excellent visible-blind UV-selective detection. These findings highlight the new strategy for compact CPL detectors, coupled with the demonstration of less-explored n-type and UV region phototransistors.
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Here, we present the synthesis and characterization of a novel 2D crystalline framework, named C2O, which mainly consists of carbon and oxygen in a 2:1 molar ratio and features crown ether holes in its skeletal structure. The covalent-frameworked 2D crown ether can be synthesized on a gram-scale and exhibits fine chemical stability in various environments, including acid, base, and different organic solvents. The C2O efficiently activates KI through the strong coordination of K+ with crown ether holes in a rigid framework, which enhances the nucleophilicity of I- and significantly improves its catalytic activity for CO2 fixation with epoxides. The presence of C2O with KI results in remarkable increases in CO2 conversion from 5.7% to 99.9% and from 2.9% to 74.2% for epichlorohydrin and allyl glycidyl ether, respectively. Moreover, C2O possesses both electrophilic and nucleophilic sites at the edge of its framework, allowing for the customization of physicochemical properties by a diverse range of chemical modifications. Specifically, incorporating allyl glycidyl ether (AGE) as an electrophile or ethoxyethylamine (EEA) as a nucleophile into C2O enables the synthesis of C2O-AGE or C2O-EEA, respectively. These modified frameworks exhibit improved conversions of 97.2% and 99.9% for CO2 fixation with allyl glycidyl ether, outperforming unmodified C2O showing a conversion of 74.2%. This newly developed scalable, durable, and customizable covalent framework holds tremendous potential for the design and preparation of outstanding materials with versatile functionalities, rendering them highly attractive for a wide range of applications.
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Block copolymer self-assembly affords diverse nanostructures, spanning from spheres and cylinders to networks, offering meticulous control over properties and functionalities at the nanoscale. However, creating thermodynamically stable network structures with high packing frustration remains a challenge. In this study, we report a methodology to access diverse network structures such as gyroid, diamond, and primitive phases from diblock copolymers using end group and linker chemistry. The stability of the medial packing of polymer chain ends (plumber's nightmare structure) over skeletal aggregation (gyroid) is attributed to the interplay between the strength of the end-end interactions and the initial shape of the curvature. Our study establishes an approach to develop tailored network structures from block copolymers, providing an important platform for using block copolymers in nanotechnology applications.
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Development of robust electrocatalysts for the oxygen evolution reaction (OER) underpins the efficient production of green hydrogen via anion exchange membrane water electrolysis (AEMWE). This study elucidates the factors contributing to the degradation of cobalt-based (Co-based) OER catalysts synthesized via electrodeposition, thus establishing strategic approaches to enhance their longevity. Systematic variations in the electroplating process and subsequent heat treatment reveal a delicate balance between catalytic activity and durability, substantiated by comprehensive electrochemical assessments and material analyses. Building upon these findings, the Co-based anode is successfully optimized in the AEMWE single-cell configuration, showcasing an average degradation rate of 0.07 mV h-1 over a continuous operation for 1500 h at a current density of 1 A cm-2.
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To construct tissue-like prosthetic materials, soft electroactive hydrogels are the best candidate owing to their physiological mechanical modulus, low electrical resistance and bidirectional stimulating and recording capability of electrophysiological signals from biological tissues1,2. Nevertheless, until now, bioelectronic devices for such prostheses have been patch type, which cannot be applied onto rough, narrow or deep tissue surfaces3-5. Here we present an injectable tissue prosthesis with instantaneous bidirectional electrical conduction in the neuromuscular system. The soft and injectable prosthesis is composed of a biocompatible hydrogel with unique phenylborate-mediated multiple crosslinking, such as irreversible yet freely rearrangeable biphenyl bonds and reversible coordinate bonds with conductive gold nanoparticles formed in situ by cross-coupling. Closed-loop robot-assisted rehabilitation by injecting this prosthetic material is successfully demonstrated in the early stage of severe muscle injury in rats, and accelerated tissue repair is achieved in the later stage.
Asunto(s)
Materiales Biocompatibles , Hidrogeles , Prótesis e Implantes , Heridas y Lesiones , Animales , Ratas , Materiales Biocompatibles/administración & dosificación , Materiales Biocompatibles/química , Materiales Biocompatibles/uso terapéutico , Conductividad Eléctrica , Oro/química , Hidrogeles/administración & dosificación , Hidrogeles/química , Hidrogeles/uso terapéutico , Nanopartículas del Metal/química , Músculos/lesiones , Músculos/inervación , Robótica , Heridas y Lesiones/rehabilitación , Heridas y Lesiones/cirugíaRESUMEN
Lithium-ion transport is significantly retarded in ionic liquids (ILs). In this work, we performed extensive molecular dynamics simulations to mimic the kinetics of lithium ions in ILs using [N-methyl-N-propylpyrrolidium (pyr[Formula: see text])][bis(trifluoromethanesulfonyl)imide (Ntf[Formula: see text])] with added LiNtf[Formula: see text] salt. And we analyzed their transport, developing a two-state model and comparing it to the machine learning-identified states. The transport of lithium ions involves local shell exchanges of the Ntf[Formula: see text] in the medium. We calculated train size distributions over various time scales. The train size distribution decays as a power law, representing non-Poissonian bursty shell exchanges. We analyzed the non-Poissonian processes of lithium ions transport as a two-state (soft and hard) model. We analytically calculated the transition probability of the two-state model, which fits well to the lifetime autocorrelation functions of LiNtf[Formula: see text] shells. To identify two states, we introduced the graph neutral network incorporating local molecular structure. The results reveal that the shell-soft state mainly contributes to the transport of the lithium ions, and their contribution is more important in low temperatures. Hence, it is the key for enhanced lithium ion transport to increase the fraction of the shell-soft state.
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Metal nanoclusters (NCs), an important class of nanoparticles (NPs), are extremely small in size and possess quasi-molecular properties. Due to accurate stoichiometry of constituent atoms and ligands, NCs have strong structure-property relationship. The synthesis of NCs is seemingly similar to that of NPs as both are formed by colloidal phase transitions. However, they are considerably different because of metal-ligand complexes in NC synthesis. Reactive ligands can convert metal salts to complexes, actual precursors to metal NCs. During the complex formation, various metal species occur, having different reactivity and fraction depending on synthetic conditions. It can alter their degree of participation in NC synthesis and the homogeneity of final products. Herein, we investigate the effects of complex formation on the entire NC synthesis. By controlling the fraction of various Au species showing different reactivity, we find that the extent of complex formation alters reduction kinetics and the uniformity of Au NCs. We demonstrate that this concept can be universally applied to synthesize Ag, Pt, Pd, and Rh NCs.
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In this study, the shear-induced lamellar alignment of a thin-film ABA triblock copolymer melt was achieved via a non-equilibrium coarse-grained molecular dynamics simulation. The ABA triblock copolymer system displayed a slightly different phase behavior under different shear conditions compared to the AB diblock copolymer system. Unlike previous studies that only considered the wall velocity, the Flory-Huggins parameter was considered in our study as a factor that determines lamellar alignment. Pre-aligned lamellae and randomly mixed polymers were used as the initial states for the shear simulation to compare the shear-induced lamellar alignment on each. The two initial conditions displayed different alignment behaviors; specifically, in the pre-aligned lamellae, a tilted structure was observed when the system was not aligned in the shear direction. To explain the difference between the tilted and realigned structures, the potential energy over the simulation time, polymer dynamics from the Van Hove correlation function, and the directional order parameter were investigated. It was inferred that a tilted structure is induced by the energy barrier of realignment originating from the restricted movement of the local polymer chains. Once they cross the energy barrier, block copolymers tend to align in the shear direction to attain energy stabilization through the polymer flow.
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In this study, the crystallization behavior of polyvinylidene fluoride (PVDF) in NMP/DMF solvent at 9 to 67 weight percent (wt%) was analyzed by molecular dynamics (MD) simulation. The PVDF phase did not gradually change with the incremental increase in PVDF wt%, but displayed rapid shifts at 34 and 50 wt% in both solvents. The solvation behavior between the two solvents was quite identical from the similar radial distribution functions. However, PVDFs in DMF solvent showed a higher ratio of ß phase crystalline structures than those in NMP solvent. It was found that DMF solvents were more tightly packed near trans state PVDF fluorine compared to NMP solvents. Also, NMP oxygen atoms interacted more favorably with gauche state PVDF hydrogen atoms over DMF oxygen atoms. The evaluation of properties observed in atomic scale interactions, such as trans state inhibition and gauche state preference, can be used as indicators in future solvent research.
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Design of bifunctional multimetallic alloy catalysts, which are one of the most promising candidates for water splitting, is a significant issue for the efficient production of renewable energy. Owing to large dimensions of the components and composition of multimetallic alloys, as well as the trade-off behavior in terms of the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) overpotentials for bifunctional catalysts, it is difficult to search for high-performance bifunctional catalysts with multimetallic alloys using conventional trial-and-error experiments. Here, an optimal bifunctional catalyst for water splitting is obtained by combining Pareto active learning and experiments, where 110 experimental data points out of 77946 possible points lead to effective model development. The as-obtained bifunctional catalysts for HER and OER exhibit high performance, which is revealed by model development using Pareto active learning; among the catalysts, an optimal catalyst (Pt0.15 Pd0.30 Ru0.30 Cu0.25 ) exhibits a water splitting behavior of 1.56 V at a current density of 10 mA cm-2 . This study opens avenues for the efficient exploration of multimetallic alloys, which can be applied in multifunctional catalysts as well as in other applications.
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Screen printing (SP) has been extensively studied owing to its widespread industrial applications; however, only a few studies have focused on the substrate effect. Herein, we demonstrate that a screen-printed line can undergo a broadening effect or lateral undulation, which is determined by the substrate and printed dimensions. The degree of spreading was systematically investigated by employing 1D and 2D geometrical parameters. Based on the liquidity of the ink, we developed a simple inviscid theory with imposed perturbation to analyze the instability of screen-printed lines. The dispersion relation was derived to estimate the geometry of the laterally undulated lines and compared with the experimental results. The proposed argument is particularly applicable to a regime in which SP inks have greater liquidity. The screen-printed patterns exhibited unique undulated shapes and were utilized as photomasks for the facile fabrication of raccoon-type microchannels.
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Benefiting from the demixing of substances in the two-phase region, a smart polymer laminate film system that exhibits direction-controlled phase separation behavior was developed in this study. Here, nanoemulsion films (NEFs) in which liquid nanodrops were uniformly confined in a polymer laminate film through the layer-by-layer deposition of oppositely charged emulsion nanodrops and polyelectrolytes were fabricated. Upon reaching a critical temperature, the NEFs exhibited a micropore-guided demixing phenomenon. A simulation study based on coarse-grained molecular dynamics revealed that the perpendicular diffusion of oil droplets through the micropores generated in the polyelectrolyte layer is crucial for determining the coarsening kinetics and phase separation level, which is consistent with the experimental results. Considering the substantial advantages of this unique and tunable two-dimensional demixing behavior, the viability of using the as-proposed NEF system for providing an efficient route for the development of smart drug delivery patches was demonstrated.
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Unit-cell-thick MoS2 is a promising electrocatalyst for the hydrogen evolution reaction (HER) owing to its tunable catalytic activity, which is determined based on the energetics and molecular interactions of different types of HER active sites. Kinetic responses of MoS2 active sites, including the reaction onset, diffusion of the electrolyte and H2 bubbles, and continuation of these processes, are important factors affecting the catalytic activity of MoS2 . Investigating these factors requires a direct real-time analysis of the HER occurring on spatially independent active sites. Herein, the H2 evolution and electrolyte diffusion on the surface of MoS2 are observed in real time by in situ electrochemical liquid-phase transmission electron microscopy (LPTEM). Time-dependent LPTEM observations reveal that different types of active sites are sequentially activated under the same conditions. Furthermore, the electrolyte flow to these sites is influenced by the reduction potential and site geometry, which affects the bubble detachment and overall HER activity of MoS2 .