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As a template-free, data-driven methodology, the molecular transformer model provides an alternative by which to predict the outcome of chemical reactions and design the route of the retrosynthetic plane in the field of organic synthesis and polymer chemistry. However, in consideration of the small datasets of chemical reactions, the data-driven model suffers from the difficulty of low accuracy in the prediction tasks of chemical reactions. In this contribution, we integrate the molecular transformer model with the strategies of data augmentation and normalization preprocessing to accomplish the three tasks of chemical reactions, including the forward predictions of chemical reactions, and single-step retrosynthetic predictions with and without the reaction classes. It is clearly demonstrated that the prediction accuracy of the molecular transformer model can be significantly raised by the use of proposed strategies for the three tasks of chemical reactions. Notably, after the introduction of the 40-level data augmentation and normalization preprocessing, the top-1 accuracy of the forward prediction increases markedly from 71.6% to 84.2% and the top-1 accuracy of the single-step retrosynthetic prediction with additional reaction class increases from 53.2% to 63.4%. Furthermore, it is found that the superior performance of the data-driven model originates from the correction of the grammatical errors of the SMILES strings, especially for the case of the reaction classes with small datasets.

Liquid-crystallization-driven self-assembly (LCDSA) is an emerging methodology, which has been employed to construct controllable 1D nanostructures. However, 2D nanostructures via living LCDSA are rarely reported, and the complicated growth kinetics are not well-known. Herein, we perform Brownian dynamics (BD) simulations to investigate the 2D living growth of disklike micelles via LCDSA of rod-coil block copolymers. The 2D seeded-growth behavior is achieved by incorporating the unimers onto the edges of disklike seeds with smectic-like liquid-crystalline (LC) cores. The fluidity of such LC-like micellar cores is conducive to the chain adjustments of rod blocks during the 2D living growth process. The apparent growth rate and unique self-similarity kinetics are governed by the interplay between the variations in the growth rate coefficient and the reactive sites at the micelle edges. This work provides an in-depth understanding of the 2D living growth of micelles and guidance to construct well-defined 2D hierarchical nanostructures.

The polymers can be either dynamically tethered to or permanently grafted to the nanoparticle to produce polymer-functionalized nanoparticles. The surface mobility of polymer ligands with one end anchored to the nanoparticle can affect the surface pattern, but the effect remains unclear. Here, we addressed the influence of lateral polymer mobility on surface patterns by performing self-consistent field theory calculations on a modeled polymer-functionalized nanoparticle consisting of immobile and mobile brushes. The results show that except for the radius of nanoparticles and grafting density, the fraction of mobile brushes substantially influences the surface patterning of polymer-functionalized nanoparticles, including striped patterns and patchy patterns with various patches. The number of patches on a nanoparticle increases as the fraction of mobile brushes decreases, favored by the entropy of immobile brushes. Critically, we found that broken symmetry usually occurs in patchy nanoparticles, associated with the balance of enthalpic and entropic effects. The present work provides a fundamental understanding of the dependence of surface patterning on lateral polymer mobility. The work could also guide the preparation of diversified nanopatterns, especially for the asymmetric patchy nanoparticles, enabling the fundamental investigation of the interaction between polymer-functionalized nanoparticles.

Introducing a second component is an effective way to manipulate polymerization behaviors. However, this phenomenon has rarely been observed in colloidal systems, such as polymeric nanoparticles. Here, we report the supramolecular polymerization of polymeric nanorods mediated by block copolymers. Experimental observations and simulation results illustrate that block copolymers surround the polymeric nanorods and mainly concentrate around the two ends, leaving the hydrophobic side regions exposed. These polymeric nanorods connect in a side-by-side manner through hydrophobic interactions to form bundles. As polymerization progresses, the block copolymers gradually deposit onto the bundles and finally assemble into helical nanopatterns on the outermost surface, which terminates the polymerization. It is anticipated that this work could offer inspiration for a general strategy of controllable supramolecular polymerization.

Precise control of size and dimension is the key to constructing complex hierarchical nanostructures, particularly multi-dimensional hybrid nanoassemblies. Herein, we conducted Brownian dynamics simulations to examine the seeded-growth of rod-coil block copolymer assemblies and discovered that 2D-1D (disk-cylinder) hybrid micelles could be formed

Based on the workflow of the materials genome approach, the challenge of enhancing multiple conflicting properties of an advanced thermosetting polymer of polycyanurates was addressed through high-throughout screening using machine learning.

The mixing morphology control plays a crucial role in photovoltaic power generation, yet this specific effect on device performances remains elusive. Here, we employed computational approaches to delineate the photovoltaic properties of layered heterojunction polymer solar cells with tunable mixing morphologies. One-step quench and two-step quench strategies were proposed to adjust the mixing morphology by thermodynamic and kinetic effects. The computation for the one-step quench revealed that modulating interfacial widths and interfacial roughness could significantly promote the photovoltaic performance of layered heterojunction polymer solar cells. The two-step quench can provide a buffer at a lower temperature before the kinetic quenching, leading to the formation of small-length-scale islands connected to the interface and a further increase in photovoltaic performance. Our discoveries are supported by recent experimental evidence and are anticipated to guide the design of photovoltaic materials with optimal performance.

The formation of membrane nanopores is one of the crucial activities of cells and has attracted considerable attention. However, the understanding of their types and mechanisms is still limited. Herein, we report a novel nanopore formation phenomenon achieved through the insertion of polymeric nanotoroids into the cellular membrane. As revealed by theoretical simulations, the nanotoroid can embed in the membrane, leaving a nanopore on the cell. The through-the-cavity wrapping of lipids is critical for the retention of the nanotoroid in the membrane, which is attributed to both a relatively large inner cavity of the nanotoroid and a moderate attraction between the nanotoroid and membrane lipids. Under the guidance of the simulation predictions, experiments using polypeptide toroids as pore-forming agents were performed, confirming the unique biophysical phenomenon. This work demonstrates a distinctive pore-forming pathway, deepens the understanding of the membrane nanopore phenomenon, and assists in the design of advanced pore-forming materials.

Despite advances in machine learning for accurately predicting material properties, forecasting the performance of thermosetting polymers remains a challenge due to the sparsity of historical experimental data and their complicated crosslinked structures. We proposed a machine-learning-assisted materials genome approach (MGA) for rapidly designing novel epoxy thermosets with excellent mechanical properties (high tensile moduli, high tensile strength, and high toughness) through high-throughput screening in a vast chemical space. Machine-learning models were established by combining attention- and gate-augmented graph convolutional networks, multilayer perceptrons, classical gel theory, and transfer learning from small molecules to polymers. Proof-of-concept experiments were carried out, and the structures designed by the MGA were verified. Gene substructures affecting the modulus, strength, and toughness were also extracted, revealing the mechanisms of polymers with high mechanical properties. The developed strategy can be employed to design other thermosetting polymers efficiently.

Programmable coassembly of multicomponent nanoparticles (NPs) into heterostructures has the capability to build upon nanostructured metamaterials with enhanced complexity and diversity. However, a general understanding of how to manipulate the sequence-defined heterostructures using straightforward concepts and quantitatively predict the coassembly process remains unreached. Drawing inspiration from the synthetic concepts of molecular block copolymers is extremely beneficial to achieve controllable coassembly of NPs and access mesoscale structuring mechanisms. We herein report a general paradigm of kinetic pathway guidance for the controllable coassembly of bivalent DNA-functionalized NPs into regular block-copolymer-like heterostructures

Background: Whipple's Disease (WD) is a rare infection caused by Tropheryma whipplei (TW), which affects multiple organs. When the infection invades the respiratory system, severe respiratory failure can be induced. However, due to extremely low prevalence and insufficient awareness, the disease is easily ignored by practitioners. Recently, we found a case of severe pneumonia with TW infection with respiratory failure induced. We combined published cases to perform a retrospective analysis of the clinical features of pneumonia caused by TW, intending to provide a reference for the treatment of WD.Methods: 11 cases of pulmonary TW infection were retrieved from the literature (1992-2022). Together with the single case identified in our hospital, 12 cases were retrospectively analyzed for risk factors, clinical manifestations, diagnosis and treatment, and outcomes.Results: Pulmonary TW infection was more prevalent in middle-aged men without underlying diseases (9/12, 75%). It usually manifested as respiratory symptoms such as cough (6/12, 50%), dyspnoea (7/12, 58.33%), and chest pain (2/12, 16.67%), which can be accompanied by or only manifested as digestive system symptoms, joint pain, fever, and other extrapulmonary symptoms. Pulmonary imaging findings were nonspecific, presenting various alterations, including multiple ground-glass opacities, consolidations, nodules, cavities in both lungs, as well as pleural effusion, interstitial pneumonia, and acute fibrinous and organizing pneumonia. Based on traditional clinical experience, Pulmonary TW infection can be treated by standardized anti-infective therapies.Conclusions: The clinical manifestations and pulmonary imaging findings of Pulmonary TW infection were diverse and non-specific. Hence, it can be easily missed or misdiagnosed. Significant efficacy can be achieved with prompt diagnosis and effective medication, thus more attention should be paid to this disease. To our knowledge, this is the first retrospective study concerning the clinical features of Pulmonary TW infection to date. Nevertheless, the number of cases presented here was small, which requires the supplementation of more clinical data in the future.

Online banks may disclose consumers’ shopping preferences due to various attacks. With differential privacy, each consumer can disturb his consumption amount locally before sending it to online banks. However, directly applying differential privacy in online banks will incur problems in reality because existing differential privacy schemes do not consider handling the noise boundary problem. In this paper, we propose an Optimized Differential prIvate Online tRansaction scheme (O-DIOR) for online banks to set boundaries of consumption amounts with added noises. We then revise O-DIOR to design a RO-DIOR scheme to select different boundaries while satisfying the differential privacy definition. Moreover, we provide in-depth theoretical analysis to prove that our schemes are capable to satisfy the differential privacy constraint. Finally, to evaluate the effectiveness, we have implemented our schemes in mobile payment experiments. Experimental results illustrate that the relevance between the consumption amount and online bank amount is reduced significantly, and the privacy losses are less than 0.5 in terms of mutual information.

Directing nanoparticles into ordered organization in polymer matrix to improve macroscopic properties of nanocomposites remains a challenge. Herein, by means of theoretical simulations, we show the high permittivity of hybrid nanostructures designed with mixtures of AB block copolymer-grafted nanoparticles and lamella-forming AC diblock copolymers. The grafted nanoparticles self-assemble into parallel stripes or highly ordered networks in the lamellae of the AC diblock copolymers. The ordered nanoparticle networks, including honeycomb-like and kagome networks, provide bending and conductive pathways for concentrating electric fields, which results in the improvement of the permittivity. We envisage that this strategy will open a gateway to prepare hierarchically ordered functional nanocomposites with distinctive dielectric properties.

Morphology transition of block copolymer assemblies in response to external stimuli has attracted considerable attention. However, our knowledge about the mechanism of such a transition is still limited, especially for rod-coil block copolymers. Here, we report a programmable morphology evolution of assemblies induced by variation of chain ordering for rod-coil-rod triblock copolymers. A sequence of morphology transition from ellipsoids to disks, bowls, and vesicles is observed by increasing the solution temperature. At high temperatures, the mobility of the rod chain increases and the rigidity of the rod chain decreases. This gives rise to an ellipsoid-to-vesicle morphology transition. Dissipative particle dynamics theoretical simulations were performed to reveal the mechanism of this morphology transition process. It was found that the increase of rod chain mobility and the decrease of rod chain rigidity induce a decrease of chain ordering of rod blocks as temperature increases, which results in an ellipsoid-to-vesicle morphology transition. The gained information can guide the construction of nanoassemblies based on the rod-coil block copolymers.

Precise organization of nanoparticles (NPs) into regularly well-defined arrays represents a continuing challenge in the development of high-performance metamaterials. Herein, zone-annealed diblock ...

High-temperature phthalonitrile resins have a wide range of applications, and understanding their curing mechanism is of great importance for academic research and engineering applications. However, the actual curing mechanism is still elusive. We presented a density functional theory study on the curing mechanism of phthalonitrile resins promoted by aromatic amines using phthalonitrile and aniline as the model compounds. We found that the rate-determining step is the initial nucleophilic addition of amines with nitrile groups on phthalonitrile to generate an amidine intermediate. The amines play a vital role in the H-transfer promoter throughout the curing reaction. The amidine and isoindoline are the critical intermediates, which can readily react with phthalonitrile through 6-membered transition states. The intramolecular cyclization of amidine intermediates is the vital step in forming isoindoline intermediates, which can be significantly promoted by amines. The proposed curing reaction pathways are kinetically more favorable than the previously reported ones, which can account for the formation of triazine, polyisoindoline, and phthalocyanine and provide a molecular-level understanding of the curing reaction.

Self-assembly behaviors of cylinder-forming diblock copolymers directed by an array of anisotropic nanoposts with elliptical shape are explored by large cell simulations of self-consistent field theory. The strategy using elliptical nanoposts allows us to generate long-range order cylinders with single orientation by suppressing other selections of cylinder alignment. The anisotropy of nanoposts plays a significant role in improving the tolerance of commensurability conditions between the dimensions of nanopost lattices and the period of cylinders. Moreover, the local defect structures could be regulated through varying the spacing and orientation of elliptical nanoposts. This work may provide useful guidelines for designing the topographical templates and lay the groundwork for fabricating well-ordered nanostructures of block copolymer lithography.

Equilibrium phase diagrams serve as blueprints for rational design of nanostructured materials of block copolymers, but their construction is time-consuming and requires profound expertise. Herein, by virtue of the knowledge of self-consistent field theory (SCFT), the active-learning method is developed to autonomously construct the phase diagrams of block copolymers. Without human intervention, the SCFT-assisted active-learning method can rapidly search the undetected phases and efficiently reproduce the complicated phase diagrams of diblock copolymers and multiblock terpolymers via decreasing the number of sampling points to about 20%. It is clearly demonstrated that the combined uncertainty sampling/random selection scheme in the active-learning method shows the outperformance in spite of a small amount of initial data set. This work highlights the promising integration of theoretical modeling with machine learning and represents a crucial step toward rational design of nanostructured materials.

We employed a nonequilibrium dissipative particle dynamics method to study viscoelastic properties of hierarchical lamellar structures self-assembled from heptablock copolymers. Three ways of shearing with respect to lamellar planes, including parallel, vertical, and transverse shearing, were imposed to study the viscoelasticity of ordered systems. In parallel shear, with the morphology transformation from disorder to general lamellae to parallel lamellae-in-lamella, both the storage and loss moduli of multiblock copolymer melt show a remarkable improvement. In addition to the parallel lamellae-in-lamella, the multiblock copolymers can form perpendicular lamellae-in-lamella with different viscoelastic behaviors. In vertical shear, parallel lamellae-in-lamella shows terminal behavior, while a low-frequency plateau in the storage modulus exists for the perpendicular lamellae-in-lamella. In transverse shear, the storage moduli for both perpendicular and parallel lamellae-in-lamellae with strong separation of small-length-scale structure exhibit a solid-like plateau at low frequency. The physical origin underlying the distinct viscoelasticity of various hierarchical lamellae was revealed by monitoring the motions of polymer blocks at different length scales. The present work could provide information for preparing advanced materials based on packed lamellae.

We conducted a dissipative particle dynamics simulation on the motion of polymer-grafted nanoparticles in entangled polymer melts. Three regimes for the mean square displacement of the nanoparticle...

We employed nonequilibrium molecular dynamics simulations to elucidate the viscoelastic properties of nanosheet (NS)-filled polymer composites. The effects of NS loadings and NS-polymer interaction on viscoelasticity were examined. The simulation results show that the NS-filled polymer composites exhibit an enhanced storage modulus and loss modulus as the NSs are loaded. There are three regimes of the enhanced process based on the NS loadings. At lower NS loadings, the motion of polymers slows down owing to the interaction between NSs and polymers, and the polymer chains generally follow the Rouse dynamics. As the NS loadings increase, the polymer chains are confined between NSs, leading to a substantial increment in dynamic moduli. At higher NS loadings, a transient network is formed, which strengthens the dynamic moduli further. In addition, the attractive NS-polymer interaction can improve the dispersion of NSs and increase the storage and loss moduli. The present work could provide essential information for designing high-performance hybrid polymeric materials.

Toroids and helices are fundamental geometrical structures in nature. Polymers can self-assemble into various nanostructures, including both toroids and helices; however, nanostructures combining toroidal and helical morphologies (that is, helical toroids) are rarely observed. A binary system is reported containing polypeptide homopolymer and its block copolymer, which can hierarchically self-assemble into uniform helical nanotoroids in solution. The formation of the helical toroids is a successive two-step process. First, the homopolymers aggregate into fibrils and convolve into toroids, thereby resembling the toroidal condensation of deoxyribonucleic acid (DNA) chains. Second, the block copolymers self-assemble on the homopolymer toroids and result in helical surface patterns. Additionally, the chirality of the surface helical patterns can be varied by the chirality of the polypeptide block copolymers.

Designing high-temperature polymers with excellent processability is a long-standing challenge because of the implacable contradiction between high thermal stability and low curing energy. Traditio...

Janus nanoparticles (JPs), which are anisotropic nanoparticles with multiple constituting parts, have been recognized as superior compatibilizers for polymer-blend-based nanocomposites. However, so far, most studies focused on the effects of symmetric JPs on the phase separation dynamics of polymer blends, while the roles of asymmetric JPs during phase separation remain unclear. In this work, the phase separation dynamics of symmetric blends compatibilized by JPs with various compositions was studied by using dissipative particle dynamics (DPD) simulations. It was found that the blends compatibilized by asymmetric JPs tend to undergo morphological transitions from bicontinuous networks to droplets-in-matrix structures at the late stage of phase separation, which is due to the influence of asymmetric JPs on the energetically favored curvature of the interfaces between polymer domains. Such a mechanism is absent for symmetric JPs and other compatibilizers (e.g., triblock copolymers and homogeneous particles) because they lack the unique combination of chemical asymmetry with the particulate nature like the asymmetric JPs. Moreover, it was observed that the asymmetric JPs can stably localize at the interfaces and act as efficient compatibilizers only when the fraction of the minor constituent part exceeds a critical value. These findings not only shed light upon the roles of asymmetric JPs as compatibilizers but also indicate a promising strategy for designing polymer-blend-based nanocomposites with tailor-made structures.

Supramolecular polymerization has been a fascinating frontier of supramolecular chemistry in fabricating well-defined hierarchical nanostructures. However, the reverse process, that is, supramolecu...

The integration of the dynamic self-consistent field theory for polymer molecules and molecular dynamics for nanoparticles is proposed to model the structural evolution of nanocomposites in the cou...

Arylethynyl reactive groups have been widely used in high-temperature polymers, and therefore, understanding their curing mechanism is of great importance for academic research and engineering applications. However, no consensus has been achieved on the actual curing mechanism of arylethynyl-containing resins so far. Herein, we present a density functional theory study on the thermal curing mechanism of arylethynyl-containing resins using phenylacetylene and diphenylacetylene as model compounds. It was discovered that the rate-determining step is the dimerization of arylacetylenes into diradical intermediates. The possibilities of the Straus-type intermediates and concerted Diels-Alder cycloaddition between two arylacetylenes can be ruled out. Cyclobutadiene and cyclic allene are the critical intermediates generated by the intramolecular coupling of diradicals. The formation of polyene is preferred by monoradical initiation rather than diradical growth. The overall reaction pathways can well account for the formation of naphthalenic dimers, benzenic trimers, and polyenic chains. The computational results of reactivity for the dimerization of arylacetylenes were finally compared with the existing experimental findings, and an agreement is shown.

The ability to control the ordering of self-assembled nanostructures is important for block copolymer (BCP) nanotechnology but remains a challenge. Herein, we proposed a facile and feasible approach to generate ordered surface nanostructures via the self-assembly of rod-coil BCPs on a substrate. Micrometer-scale, well-aligned, and vertically orientated stripe nanopatterns are readily constructed on the substrate in a fast and controllable way. The feature sizes of the nanopatterns can be adjusted by the molecular weight of BCPs. In addition, self-assembling conditions such as BCP concentration and temperature were found to possess a significant influence on the surface morphology, as well as the order degree of the nanopatterns. Dissipative particle dynamics theoretical simulations provided complementary information for the experimental observations, including the inner chain packing and the dynamic process of the formation of ordered structures. This work presents a novel and effective strategy for the fabrication of well-aligned nanopatterns as an alternative to traditional methods.