Exploring the Adaptability of 4D Printed Shape Memory Polymer Featuring Dynamic Covalent Bonds.

4D printing (4DP) of high-performance shape memory polymers (SMPs), particularly using digital light processing (DLP), has garnered intense global attention due to its capability for rapid and high-precision fabrication of complex configurations, meeting diverse application requirements. However, the development of high-performance dynamic shape memory polymers (DSMPs) for DLP printing remains a significant challenge due to the inherent incompatibilities between the photopolymerization process and the curing/polymerization of high-strength polymers. Here, a mechanically robust DSMP compatible is developed with DLP printing, which incorporates dynamic covalent bonds of imine linking polyimide rigid segments, exhibiting remarkable mechanical performance (tensile strength ≈41.7 MPa, modulus ≈1.63 GPa) and thermal stability (Tg ∼ 113 °C, Td ∼ 208 °C). More importantly, benefiting from the solid-state plasticity conferred by dynamic covalent bonds, 4D printed structures demonstrate rapid network adaptiveness, enabling effortless realization of reconfiguration, self-healing, and recycling. Meanwhile, the extensive π-π conjugated structures bestow DSMP with an intrinsic photothermal effect, allowing controllable morphing of the 4D configuration through dual-mode triggering. This work not only greatly enriches the application scope of high-performance personalized configurations but also provides a reliable approach to addressing environmental pollution and energy crises.

Experimental study on the influence of water-rock interaction on the time-varying characteristics of coal rock mass.

In order to study the influence of water-rock interaction on the mass time-varying characteristics of coal rocks, coal was selected as the research object and subjected to chemical immersion tests with different pH aqueous solutions for 12 days. By experiment, the time-varying patterns of mass change fraction in coal samples, pH value in solution, and ions concentration of calcium and magnesium were obtained. Based on the gray correlation theory, the correlation degree between the mass change fraction and four influencing factors was analyzed. The gray prediction models for the mass time-varying characteristics of coal rocks have been established. The research shows that: (1) the influence ways and degree of different pH aqueous solutions on the mass changes of coal rocks are different, (2) during the process of water-rock interaction, the change law of pH value, ions concentration of calcium and magnesium in solution are obvious, (3) the multiple regression models can be used to predict the mass change of coal rocks accurately under water-rock interaction.

The mechanism of the irradiation synergistic effect of silicon bipolar junction transistors explained by multiscale simulations of Monte Carlo and excited-state first-principle calculations.

Neutron and γ-ray irradiation damages to transistors are found to be non-additive, and this is denoted as the irradiation synergistic effect (ISE). Its mechanism is not well-understood. The recent defect-based model [Song and Wei, ACS Appl. Electron. Mater. 2, 3783 (2020)] for silicon bipolar junction transistors (BJTs) achieves quantitative agreement with experiments, but its assumptions on the defect reactions are unverified. Going beyond the model requires directly representing the effect of γ-ray irradiation in first-principles calculations, which was not feasible previously. In this work, we examine the defect-based model of the ISE by developing a multiscale method for the simulation of the γ-ray irradiation, where the γ-ray-induced electronic excitations are treated explicitly in excited-state first-principles calculations. We find the calculations agree with experiments, and the effect of the γ-ray-induced excitation is significantly different from the effects of defect charge state and temperature. We propose a diffusion-based qualitative explanation of the mechanism of positive/negative ISE in NPN/PNP BJTs in the end.

Speed-dependent adaptive partitioning in QM/MM MD simulations of displacement damage in solid-state systems.

Solids undergo displacement damage (DD) when interacting with energetic particles, which may happen during the fabrication of semiconductor devices, in harsh environments and in certain analysis techniques. Simulations of DD generation are usually carried out using classical molecular dynamics (MD), but classical MD does not account for all the effects in DD, as demonstrated by ab initio calculations of model systems in the literature. A complete ab initio simulation of DD generation is impractical due to the large number of atoms involved. In my previous paper [Yang, Phys. Chem. Chem. Phys., 2020, 22, 19307], I developed an adaptive-center (AC) method for the adaptive-partitioning (AP) of quantum mechanics/molecular mechanics (QM/MM) simulations, allowing the active region centers and the QM/MM partition to be determined on-the-fly for energy-conserving AP-QM/MM methods. I demonstrated that the AC-AP-QM/MM is applicable to the simulation of DD generation, so that the active regions can be treated using an ab initio method. The AC method could not be used to identify the fast-moving recoil ions in DD generation as active region centers, however, and the accuracy is negatively affected by the rapid change in the QM/MM partition of the system. In this paper, I extend the AC method and develop a speed-dependent adaptive-center (SDAC) method for accurate AP-QM/MM simulations of DD. The SDAC method is applicable to general problems with speed-dependent active regions, and is compatible with all existing energy-conserving partitioning-by-distance AP-QM/MM methods. The artifact due to the speed-dependent potential energy surface can be made small by choosing suitable criteria. I demonstrate the SDAC method by simulations of DD generation in bulk silicon.

Plasma miR-1, but not Extracellular Vesicle miR-1, Functions as a Potential Biomarker for Colorectal Cancer Diagnosis.

BACKGROUND: miRNAs have been proved to function as diagnostic biomarkers. Extracellular vesicles (EVs) are carriers of miRNAs. This study aimed to investigate the diagnostic potential of miR-1 in plasma and extracellular vesicles (EVs) for patients with colorectal cancer (CRC). METHODS: Bioinformatics analysis was used to find a target miRNA and its potential functions. miR-1 was then detected in plasma and EV from 49 control samples and 40 CRC samples. Next, the diagnostic potential of plasma and EV miR-1 were compared based on common biomarkers including CEA and CA211. RESULTS: miR-1 was differentially expressed in CRC. Target gene and function analyses showed that it might participate in cell migration and the regulation of mRNA splicing via the spliceosome. Plasma miR-1 levels in CRC samples were significantly higher than those in control samples, whereas EV miR-1 levels were not statistically different. Based on receiver operating characteristic (ROC) curve analysis, comparing their predictive power compared to that of CEA and CA211, plasma miR-1 performed better and EV miR-1 performed worse. CONCLUSIONS: Our data indicate that plasma miR-1, but not EV miR-1, could function as a potential biomarker for CRC diagnosis.

On-the-fly determination of active region centers in adaptive-partitioning QM/MM.

Quantum mechanics/molecular mechanics (QM/MM) methods are widely used in molecular dynamics (MD) simulations of large systems. By partitioning the system into active and environmental regions and treating them with different levels of theory, QM/MM methods achieve accuracy and efficiency at the same time. Adaptive-partitioning (AP) QM/MM allows the partition of the system to change during the MD simulation, making it possible to simulate processes in which the active and environmental regions exchange atoms or molecules, such as processes in solutions or solids. AP-QM/MM methods usually partition the system according to distances to centers of active regions. For energy-conserving AP-QM/MM methods, these centers are chosen beforehand and remain fixed during the MD simulation, making it difficult to simulate processes in which active regions may occur or vanish. In this paper, I develop an adaptive-center (AC) method that allows on-the-fly determination of the centers of active regions according to any geometrical criterion or any criterion dependent on the potential energy. The AC method is compatible with all existing energy-conserving AP-QM/MM methods, and the resulting potential energy surface is smooth. The application of the AC method is demonstrated with two examples in solid systems.

Extending scaled-interaction adaptive-partitioning QM/MM to covalently bonded systems.

Quantum mechanics/molecular mechanics (QM/MM) is the method of choice for atomistic simulations of large systems that can be partitioned into active and environmental regions. Adaptive-partitioning (AP) methods extend the applicability of QM/MM, allowing active regions to change during the simulation. AP methods achieve continuous potential energy surface (PES) by introducing buffer regions in which atoms have both QM and MM characters. Most of the existing AP-QM/MM methods require multiple QM calculations per time step, which can be expensive for systems with many atoms in buffer regions. Although one can lower the computational cost by grouping atoms into fragments, this may not be possible for all systems, especially for applications in covalent solids. The SISPA method [Field, J. Chem. Theory Comput., 2017, 13, 2342] differs from other AP-QM/MM methods by only requiring one QM calculation per time step, but it has the flaw that the QM charge density and wavefunction near the buffer/MM boundary tend to those of isolated atoms/fragments. Besides, regular QM/MM methods for treating covalent bonds cut by the QM/MM boundary are incompatible with SISPA. Due to these flaws, SISPA in its original form cannot treat covalently bonded systems properly. In this work, I show that a simple modification to the SISPA method improves the treatment of covalently bonded systems. I also study the effect of correcting the charge density in SISPA by developing a density-corrected pre-scaled algorithm. I demonstrate the methods with simple molecules and bulk solids.

Understanding band gaps of solids in generalized Kohn-Sham theory.

The fundamental energy gap of a periodic solid distinguishes insulators from metals and characterizes low-energy single-electron excitations. However, the gap in the band structure of the exact multiplicative Kohn-Sham (KS) potential substantially underestimates the fundamental gap, a major limitation of KS density-functional theory. Here, we give a simple proof of a theorem: In generalized KS theory (GKS), the band gap of an extended system equals the fundamental gap for the approximate functional if the GKS potential operator is continuous and the density change is delocalized when an electron or hole is added. Our theorem explains how GKS band gaps from metageneralized gradient approximations (meta-GGAs) and hybrid functionals can be more realistic than those from GGAs or even from the exact KS potential. The theorem also follows from earlier work. The band edges in the GKS one-electron spectrum are also related to measurable energies. A linear chain of hydrogen molecules, solid aluminum arsenide, and solid argon provide numerical illustrations.

Direct Extraction of Excitation Energies from Ensemble Density-Functional Theory.

A very specific ensemble of ground and excited states is shown to yield an exact formula for any excitation energy as a simple correction to the energy difference between orbitals of the Kohn-Sham ground state. This alternative scheme avoids either the need to calculate many unoccupied levels as in time-dependent density functional theory (TDDFT) or the need for many self-consistent ensemble calculations. The symmetry-eigenstate Hartree-exchange (SEHX) approximation yields results comparable to standard TDDFT for atoms. With this formalism, SEHX yields approximate double excitations, which are missed by adiabatic TDDFT.

Excitons in Time-Dependent Density-Functional Theory.

This chapter gives an overview of the description of the optical and dielectric properties of bulk insulators and semiconductors in time-dependent density-functional theory (TDDFT), with an emphasis on excitons. We review the linear-response formalism for periodic solids, discuss excitonic exchange-correlation kernels, calculate exciton binding energies for various materials, and compare the treatment of excitons with TDDFT and with the Bethe-Salpeter equation.

Communication: Near-locality of exchange and correlation density functionals for 1- and 2-electron systems.

The uniform electron gas and the hydrogen atom play fundamental roles in condensed matter physics and quantum chemistry. The former has an infinite number of electrons uniformly distributed over the neutralizing positively charged background, and the latter only one electron bound to the proton. The uniform electron gas was used to derive the local spin density approximation to the exchange-correlation functional that undergirds the development of the Kohn-Sham density functional theory. We show here that the ground-state exchange-correlation energies of the hydrogen atom and many other 1- and 2-electron systems are modeled surprisingly well by a different local spin density approximation (LSDA0). LSDA0 is constructed to satisfy exact constraints but agrees surprisingly well with the exact results for a uniform two-electron density in a finite, curved three-dimensional space. We also apply LSDA0 to excited or noded 1-electron densities, where it works less well. Furthermore, we show that the localization of the exact exchange hole for a 1- or 2-electron ground state can be measured by the ratio of the exact exchange energy to its optimal lower bound.

Excitations and benchmark ensemble density functional theory for two electrons.

A new method for extracting ensemble Kohn-Sham potentials from accurate excited state densities is applied to a variety of two-electron systems, exploring the behavior of exact ensemble density functional theory. The issue of separating the Hartree energy and the choice of degenerate eigenstates is explored. A new approximation, spin eigenstate Hartree-exchange, is derived. Exact conditions that are proven include the signs of the correlation energy components and the asymptotic behavior of the potential for small weights of the excited states. Many energy components are given as a function of the weights for two electrons in a one-dimensional flat box, in a box with a large barrier to create charge transfer excitations, in a three-dimensional harmonic well (Hooke's atom), and for the He atom singlet-triplet ensemble, singlet-triplet-singlet ensemble, and triplet bi-ensemble.

Combination of handgrip strength and high-sensitivity modified Glasgow prognostic score predicts survival outcomes in patients with colon cancer.

Objective: Handgrip strength (HGS) and the high-sensitivity modified Glasgow prognostic score (HS-mGPS) are associated with the survival of patients with cancer. However, no studies have investigated the combined effect of HGS and HS-mGPS on the overall survival (OS) of patients with colon cancer. Methods: Prospective follow-up data of colon cancer patients undergoing radical resection from April, 2016 to September, 2019 were retrospectively collected. We combined the HGS and HS-mGPS to create a new composite index, HGS-HS-mGPS. The hazard ratio (HR) and 95% confidence interval (CI) were calculated using Cox regression models to assess the association between variables and OS. Risk factors on OS rates were investigated by Cox analyses and the nomogram was constructed using significant predictors and HGS-HS-mGPS. The predictive performance of the nomogram was evaluated by receiver operating characteristic curve and calibration curve. Results: This study included a total of 811 patients, of which 446 (55.0%) were male. The HGS optimal cut-off values of male and female patients were 28.8 and 19.72 kg, respectively. Multivariate analysis revealed that low HGS and high HS-mGPS were independent risk factors of colon cancer after adjusting confounders (adjusted HR = 3.20; 95% CI: 2.27-4.50; p < 0.001 and adjusted HR = 1.55; 95% CI: 1.12-2.14; p = 0.008 respectively). Patients with low HGS and high HS-mGPS had a 10.76-fold higher mortality risk than those with neither (adjusted HR = 10.76; 95% CI: 5.38-21.54; p < 0.001). A nomogram predicting 1-, 3-, and 5 year OS was constructed based on three clinicopathologic prognostic factors. Importantly, incorporating HGS-HS-mGPS into the nomogram model meaningfully improved the predictive performance. The decision curve analyses demonstrated the application value of the HGS-HS-mGPS nomogram for predicting OS of patients with colon cancer. Conclusion: HGS-HS-mGPS is associated with the survival of patients with colon cancer. These findings indicate the usefulness of HGS and HS-mGPS measurements in clinical practice for improving patient assessment, cancer prognosis, and precise intervention.

Super-Durable, Tough Shape-Memory Polymeric Materials Woven from Interlocking Rigid-Flexible Chains.

Developing advanced engineering polymers that combine high strength and toughness represents not only a necessary path to excellence but also a major technical challenge. Here for the first time a rigid-flexible interlocking polymer (RFIP) is reported featuring remarkable mechanical properties, consisting of flexible polyurethane (PU) and rigid polyimide (PI) chains cleverly woven together around the copper(I) ions center. By rationally weaving PI, PU chains, and copper(I) ions, RFIP exhibits ultra-high strength (twice that of unwoven polymers, 91.4 ± 3.3 MPa), toughness (448.0 ± 14.2 MJ m-3), fatigue resistance (recoverable after 10 000 cyclic stretches), and shape memory properties. Simulation results and characterization analysis together support the correlation between microstructure and macroscopic features, confirming the greater cohesive energy of the interwoven network and providing insights into strengthening toughening mechanisms. The essence of weaving on the atomic and molecular levels is fused to obtain brilliant and valuable mechanical properties, opening new perspectives in designing robust and stable polymers.

Flexible Cages Enable Robust Supramolecular Elastomers.

Advances in modern industrial technology continue to place stricter demands on engineering polymeric materials, but simultaneously possessing superior strength and toughness remains a daunting challenge. Herein, a pioneering flexible cage-reinforced supramolecular elastomer (CSE) is reported that exhibits superb robustness, tear resistance, anti-fatigue, and shape memory properties, achieved by innovatively introducing organic imide cages (OICs) into supramolecular networks. Intriguingly, extremely small amounts of OICs make the elastomer stronger, significantly improving mechanical strength (85.0 MPa; ≈10-fold increase) and toughness (418.4 MJ m-3; ≈7-fold increase). Significantly, the cooperative effect of gradient hydrogen bonds and OICs is experimentally and theoretically demonstrated as flexible nodes, enabling more robust supramolecular networks. In short, the proposed strengthening strategy of adding flexible cages effectively balances the inherent conflict between material strength and toughness, and the prepared CSEs are anticipated to be served in large-scale devices such as TBMs in the future.

A stretchable, mechanically robust polymer exhibiting shape-memory-assisted self-healing and clustering-triggered emission.

Self-healing and recyclable polymer materials are being developed through extensive investigations on noncovalent bond interactions. However, they typically exhibit inferior mechanical properties. Therefore, the present study is aimed at synthesizing a polyurethane-urea elastomer with excellent mechanical properties and shape-memory-assisted self-healing behavior. In particular, the introduction of coordination and hydrogen bonds into elastomer leads to the optimal elastomer exhibiting good mechanical properties (strength, 76.37 MPa; elongation at break, 839.10%; toughness, 308.63 MJ m-3) owing to the phased energy dissipation mechanism involving various supramolecular interactions. The elastomer also demonstrates shape-memory properties, whereby the shape recovery force that brings damaged surfaces closer and facilitates self-healing. Surprisingly, all specimens exhibite clustering-triggered emission, with cyan fluorescence is observed under ultraviolet light. The strategy reported herein for developing multifunctional materials with good mechanical properties can be leveraged to yield stimulus-responsive polymers and smart seals.

Mechanically Ultra-Robust Elastomers Integrating Self-Healing and Recycling Properties Enable Information Encryption and Hierarchical Decryption.

Developing high-performance elastomers with distinctive features opens up new vistas and exciting possibilities for information encryption but remains a daunting challenge. To surmount this difficulty, an unprecedented synthetic approach, "modular molecular engineering", was proposed to develop tailor-made advanced elastomers. The customized hydrophobic poly(urea-urethane) (HPUU-R) elastomer perfectly integrated ultrahigh tensile strength (∼75.3 MPa), extraordinary toughness (∼292.5 MJ m-3), satisfactory room-temperature healing, high transparency, puncture-, scratch-, and water-resistance; and miraculously, its 0.20 g film could lift objects over 100 000 times its weight without rupture. Intriguingly, we unexpectedly discovered that the elastomers fluoresce brightly at the optimal excitation wavelength attributed to the "clusterization-triggered emission". Based on the gradient hydrophobicity and fluorescent properties of HPUU-R, a hierarchical information encryption/decryption mode was innovatively established. Using high-performance HPUU-R as a double encryption platform makes the information highly stable and persistent, thus providing a stronger guarantee for the encrypted information. More attractively, given the impressive recyclability and self-healing of HPUU-R, information encryption can be realized by using recycled elastomers, injecting new vitality into green and sustainable development.

Reconfigurable, Solvent-Processable, NIR-Triggerable Shape Memory Cyanate Esters for Smart Molds.

Shape memory polymer (SMP)-based smart molds, which could provide high-resolution mold shape and morph in response to external stimuli for readily demolding the complex structure, attract extensive attention. However, the suitable SMP for smart molds is usually confined with low stretchability that likely causes damage during demolding. Herein, we present a cyanate ester smart composite (CESC) with a reconfigurable, solvent-processable, and near-infrared (NIR)-triggerable shape memory effect (SME), which enables the 2D sheet with a variety of morphed complex shapes through deformation in a mild situation. Notably, the reconfigurable SME and the recyclability of the shape memory cyanate ester (SMCE) were addressed for the first time, attributed to the dynamic covalent bonds of transesterification and the novel cyanurate exchange. In addition, we found that the mechanism of solvent-processable SME is attributed to the varied cross-linking density and the mobility of the polymer chain. Integrating the multiple responsive SME and reconfigurable SME, the CESC demonstrated versatile applications as a smart mold. The results demonstrate a wide scope of application of the integrated SME and provide a new design strategy for thermoset cyanate materials.

Effect of cusps in time-dependent quantum mechanics.

Within nonrelativistic quantum mechanics, spatial cusps in initial wave functions can lead to nonanalytic behavior in time. We suggest a method for calculating the short-time behavior in such situations. For these cases, the density does not match its Taylor expansion in time, but the Runge-Gross proof of time-dependent density functional theory still holds, as it requires only the potential to be time analytic.

A minimal model for excitons within time-dependent density-functional theory.

The accurate description of the optical spectra of insulators and semiconductors remains an important challenge for time-dependent density-functional theory (TDDFT). Evidence has been given in the literature that TDDFT can produce bound as well as continuum excitons for specific systems, but there are still many unresolved basic questions concerning the role of dynamical exchange and correlation (xc). In particular, the roles of the long spatial range and the frequency dependence of the xc kernel f(xc) for excitonic binding are still not very well explored. We present a minimal model for excitons in TDDFT, consisting of two bands from a one-dimensional (1D) Kronig-Penney model and simple approximate xc kernels, providing an easily accessible model system for studying excitonic effects in TDDFT. For the 1D model system, it is found that adiabatic xc kernels can produce at most two bound excitons, confirming that the long spatial range of f(xc) is not a necessary condition. It is shown how the Wannier model, featuring an effective electron-hole interaction, emerges from TDDFT. The collective, many-body nature of excitons is explicitly demonstrated.