Single-chain Model Research Articles

Innovation and Practice of Diversified Business Model of New Energy Power Generation Enterprises

With the growing global demand for clean energy, new energy power generation enterprises are facing new opportunities and challenges. This paper explores the diversified business model of new energy power generation enterprises. Firstly, the theoretical basis of the business model of new energy power generation enterprises is analyzed, including the characteristics and income sources of single and multiple industrial chain models. The advantages and applications of different business models are analyzed through the study of cases at home and abroad, such as the European aggregated generation side resource model, the United States focused on controllable load demand response model, and the domestic cases of Shanghai and Shenzhen virtual power plant projects and distributed photovoltaic power generation. Then it puts forward the diversified business model innovation strategy of new energy power generation enterprises, covering the innovation of comprehensive energy services, the development of power side energy storage business, and the expansion of key businesses and profit models. Finally, the research conclusions are summarized and the future research directions are prospected. In short, the exploration of diversified business models of new energy power generation enterprises is of great significance to promote the development of clean energy and improve the competitiveness of enterprises.

Direct computations of viscoelastic moduli of biomolecular condensates.

In vitro facsimiles of biomolecular condensates are formed by different types of intrinsically disordered proteins including prion-like low complexity domains (PLCDs). PLCD condensates are viscoelastic materials defined by time-dependent, sequence-specific complex shear moduli. Here, we show that viscoelastic moduli can be computed directly using a generalization of the Rouse model and information regarding intra- and inter-chain contacts that is extracted from equilibrium configurations of lattice-based Metropolis Monte Carlo (MMC) simulations. The key ingredient of the generalized Rouse model is the Zimm matrix that we compute from equilibrium MMC simulations. We compute two flavors of Zimm matrices, one referred to as the single-chain model that accounts only for intra-chain contacts, and the other referred to as a collective model, that accounts for inter-chain interactions. The single-chain model systematically overestimates the storage and loss moduli, whereas the collective model reproduces the measured moduli with greater fidelity. However, in the long time, low-frequency domain, a mixture of the two models proves to be most accurate. In line with the theory of Rouse, we find that a continuous distribution of relaxation times exists in condensates. The single crossover frequency between dominantly elastic versus dominantly viscous behaviors is influenced by the totality of the relaxation modes. Hence, our analysis suggests that viscoelastic fluid-like condensates are best described as generalized Maxwell fluids. Finally, we show that the complex shear moduli can be used to solve an inverse problem to obtain distributions of relaxation times that underlie the dynamics within condensates.

Design of Multi-Chain Traceability Model for Pepper Products Based on Traceability Code

In the specific application scenario of pepper product supply chain traceability, with the advancement of pepper product production, the expansion of links, and the increase of nodes, the quantity of data will become more and more enormous. The single-chain model is less efficient for querying if the data are all stored into the same blockchain. In order to improve the efficiency of blockchain data querying, this paper proposes a traceability model with one main chain and multiple side chain structures, which separate the uplinked data from each link and use multi-chain transactions to improve the efficiency of data queries. This model builds an indexing mechanism with a product traceability code, using one main chain and multiple side chains. The main and side chains form a one-to-many mapping relationship, storing the mapping relationship between the traceability code and the transaction address of the side chain traceability information in the main chain. This enables information to travel through the main chain traversal query based on the mapping relationship and then query the direct index out of the side chain, to achieve fast traceability query and improve the efficiency of querying.

Density Functional Theory-Based Approach For Dielectric Constant Estimation of Soluble Polyimide Insulators.

Evaluation of the insulating properties of polymers, such as the dielectric constant and dissipation factor, is crucial in electronic devices, including field-effect transistors and wireless communication applications. This study applies density functional theory (DFT) to predict the dielectric constant of soluble polyimides (SPIs). Various SPIs containing trifluoromethyl groups in the backbone with different pendant types, numbers, and symmetries are successfully synthesized, and their dielectric constants are evaluated and compared with the DFT-estimated values. Two types of DFT-optimized SPIs, single-chain and stacked-chain models, are used to describe the local geometries of the SPIs. In addition, to reveal the relationship between the molecular structure and dielectric constant, further investigations are conducted by considering the dielectric constant of composing ionic and electronic components. The DFT-estimated static dielectric constant of the single-chain model accurately reproduces the corresponding experimental value with at least 80% accuracy. Our approach provides a rational and accelerated strategy to evaluate polymer insulators for electronic devices based on cost-effective DFT calculations.

On the theory of mechanically induced chemiluminescence in multiple network elastomers

Mechanophores, force-sensitive molecules, can be covalently linked into polymer networks to reveal the damage properties of polymeric materials under deformation. Recent works have introduced bis-adamantyl dioxetane (Ad) into multiple network elastomers. These mechanoluminescent cross-linking molecules can emit luminescence as they break. The experimental results can directly visualize the damage behaviors of multiple network elastomers and reveal the damage mechanism of these materials during deformation. In this work, we develop a constitutive model to describe the complex mechanical behaviors of multiple network elastomers based on observations from mechano-chemiluminescent experiments. The free energy density consists of the contributions from the filler network, the matrix network, and the entangled network. A new type of single-chain model is developed for the filler network, while the classic eight-chain mapping is adopted for the micro–macro transition. The chains in the filler network are progressively damaged under deformation to explain the stress-softening behaviors observed in the small and median strain regions of multiple network elastomers. The entangled network is rooted in individual fragments of the damaged filler network, which can be further damaged in the large deformation regime. The model can comprehensively capture the complex mechanical responses of multiple network elastomers with different values of the prestretching ratio of the filler network, including linear response, necking instability, and re-hardening phenomena in quadruple networks. By assuming that the luminescence intensity of the materials is proportional to the total percentage of damage from both filler and entangled networks, we quantify the relationship between damage and the luminescence intensity from mechanophores, which is further validated in quantifying luminescence intensity against different sets of experimental data on the uniaxial tension of multiple network elastomers. The model is further implemented for finite element analysis, demonstrating the ability to visualize and characterize the damage behaviors around a crack.

Efficient Prediction Model of mRNA End-to-End Distance and Conformation: Three-Dimensional RNA Illustration Program (TRIP).

The secondary and tertiary structures of RNA play a vital role in the regulation of biological reactions. These structures have been experimentally studied through in vivo and in vitro analyses, and in silico models have become increasingly accurate in predicting them. Recent technologies have diversified RNA structure predictions, from the earliest thermodynamic and molecular dynamic-based RNA structure predictions to deep learning-based conformation predictions in the past decade. While most research on RNA structure prediction has focused on short non-coding RNAs, there has been limited research on predicting the conformation of longer mRNAs. Our study introduces a computer simulation model called the Three-dimensional RNA Illustration Program (TRIP). TRIP is based on single-chain models and angle restriction of each bead component from previously reported single-molecule fluorescence in situ hybridization (smFISH) experiments. TRIP is a fast and efficient application that only requires up to three inputs to acquire outputs. It can also provide a rough visualization of the 3D conformation of RNA, making it a valuable tool for predicting RNA end-to-end distance.

CC+ : A searchable database of validated coiled coils in PDB structures and AlphaFold2 models.

α-Helical coiled coils are common tertiary and quaternary elements of protein structure. In coiled coils, two or more α helices wrap around each other to form bundles. This apparently simple structural motif can generate many architectures and topologies. Coiled coil-forming sequences can be predicted from heptad repeats of hydrophobic and polar residues, hpphppp, although this is not always reliable. Alternatively, coiled-coil structures can be identified using the program SOCKET, which finds knobs-into-holes (KIH) packing between side chains of neighboring helices. SOCKET also classifies coiled-coil architecture and topology, thus allowing sequence-to-structure relationships to be garnered. In 2009, we used SOCKET to create a relational database of coiled-coil structures, CC+ , from the RCSB Protein Data Bank (PDB). Here, we report an update of CC+ following an update of SOCKET (to Socket2) and the recent explosion of structural data and the success of AlphaFold2 in predicting protein structures from genome sequences. With the most-stringent SOCKET parameters, CC+ contains ≈12,000 coiled-coil assemblies from experimentally determined structures, and ≈120,000 potential coiled-coil structures within single-chain models predicted by AlphaFold2 across 48 proteomes. CC+ allows these and other less-stringently defined coiled coils to be searched at various levels of structure, sequence, and side-chain interactions. The identified coiled coils can be viewed directly from CC+ using the Socket2 application, and their associated data can be downloaded for further analyses. CC+ is available freely at http://coiledcoils.chm.bris.ac.uk/CCPlus/Home.html. It will be updated automatically. We envisage that CC+ could be used to understand coiled-coil assemblies and their sequence-to-structure relationships, and to aid protein design and engineering.

A Quality Traceability System for Fruit and Vegetable Supply Chain Based on Multi-Chain Blockchain

To enhance the efficiency and security of traceability in the fruit and vegetable industry, this paper proposes an optimized model based on multi-chain blockchain technology. Firstly, an analysis is conducted on the supply chain information of the fruit and vegetable industry, where traceability codes and product information from various stages of the supply chain are organized and extracted. Next, a trusted traceability optimization model is established based on blockchain technology. Finally, an information traceability system for the VFSC is implemented using Hyperledger fabric, and an improved Kafka load balancing algorithm is proposed to enhance message transmission efficiency. Simulation results demonstrate that the multi-chain traceability model proposed outperforms traditional single-chain blockchain models in terms of query efficiency when the number of data records exceeds 1000. After 10000 data records are deployed on the blockchain, the efficiency of the multi-chain model is improved by over 90% compared to the traditional single-chain model.

Production Change Optimization Model of Nonlinear Supply Chain System under Emergencies

Aiming at the problem that the upstream manufacturer cannot accurately formulate the production plan after the link of the nonlinear supply chain system changes under emergencies, an optimization model of production change in a nonlinear supply chain system under emergencies is designed. Firstly, based on the structural characteristics of the supply chain system and the logical relationship between production, sales, and storage parameters, a three-level single-chain nonlinear supply chain dynamic system model containing producers, sellers, and retailers was established based on the introduction of nonlinear parameters. Secondly, the radial basis function (RBF) neural network and improved fast variable power convergence law were introduced to improve the traditional sliding mode control, and the improved adaptive sliding mode control is proposed so that it can have a good control effect on the unknown nonlinear supply chain system. Finally, based on the numerical assumptions, the constructed optimization model was parameterized and simulated for comparison experiments. The simulation results show that the optimized model can reduce the adjustment time by 37.50% and inventory fluctuation by 42.97%, respectively, compared with the traditional sliding mode control, while helping the supply chain system to return the smooth operation after the change within 5 days.

Elasticity of Slide-Ring Gels.

Slide-ring gels are polymer networks with cross-links that can slide along the chains. In contrast to conventional unentangled networks with cross-links fixed along the chains, the slide-ring networks are strain-softening and distribute tension much more uniformly between their strands due to the so-called "pulley effect". The sliding of cross-links also reduces the elastic modulus in comparison with the modulus of conventional networks with the same number density of cross-links and elastic strands. We develop a single-chain model to account for the redistribution of monomers between network strands of a primary chain. This model takes into account both the pulley effect and fluctuations in the number of monomers per network strand. The pulley effect leads to modulus reduction and uniform tension redistribution between network strands, while fluctuations in the number of strand monomers dominate the strain-softening, the magnitude of which decreases upon network swelling and increases upon deswelling.

A Constitutive Model for Mechanical Behaviors of Novel Double Network Hydrogels with Mechanophores

Double network hydrogels (DN hydrogels) with high stretchability and toughness have attracted broad research interest. Recently, a kind of novel tough DN hydrogels was designed by means of the reactive strand extension strategy, which introduced mechanophores into the first network. When the strands of the first network reach their nominal stretching limit, the mechanophores allow the strands to survive through force-coupled reactions instead of fracture. As a consequence, the novel hydrogels can achieve a better mechanical performance compared with the conventional DN hydrogels. In this work, we aim to develop a constitutive model for the novel DN hydrogels. The model is based on the worm-like single-chain model by introducing bond deformation. The network alteration theory is used to account for the damage behaviors. The theoretical framework is capable of clarifying the difference in mechanical behaviors between conventional and novel DN hydrogels, which demonstrates the importance of bond deformation on the mechanical behaviors of DN hydrogels.

B-SSMD: A Fine-Grained Secure Sharing Scheme of Medical Data Based on Blockchain

The application of blockchain technology in the medical information system is gradually triggering profound changes, which has heterogeneous, cross-domain, and open network characteristics. However, today’s electronic medical systems fall short of ensuring the confidentiality and safe sharing of medical data, which poses serious threats to their authenticity and accuracy. Moreover, most of the current blockchain medical systems are under great transmission and storage pressure. Based on the aforementioned security and performance considerations, this paper proposes a fine-grained secure sharing scheme of medical data based on blockchain (B-SSMD). We design a three-chain model to store patient information, medical staff information, and medical records hierarchically. The integration of IPFS technology and the encryption algorithm ensures secure and efficient off-chain data storage. The user classification is realized by assigning attributes, and the attribute encryption technology is adopted for secondary encryption of the key and ciphertext path. Meanwhile, through hierarchical encryption, the risk of a system attack is greatly reduced. Our scheme not only solves the problems of low throughput and poor stability in the single chain model but also improves the data confidentiality and enables medical data to be managed more safely and efficiently in the sharing process. We provide the security and performance analysis and it is confirmed that our scheme has higher security and controllability.

A single-chain model for the linear viscoelasticity of unentangled melts of associating polymers

Existing single-chain models for unentangled associating polymers account for the association by assigning the sticky junctions a large value of the monomeric friction coefficient, which prevents them from moving in space unless stickers effectively dissociate. With such an assumption, comparison of model predictions with linear viscoelastic data is not fully successful in the intermediate range of frequency. In this work, we improve agreement with data by developing a single-chain model where sticky junctions are allowed to quickly move in space without dissociating. We also account for a random distribution of the stickers but differently from the recent model by Jiang et al. [Macromolecules 53, 3438–3451 (2020)]. Predictions of the model are successfully compared with unentangled melt data for two different copolymer chemistries and different sticker concentrations. Particularly significant are the data by Cui et al. [J. Rheol., 62, 1155–1174 (2018)] of melts of polymers with only two stickers per chain, revealing that sticky junctions are in fact also endowed with fast mobility.

Freely jointed chain models with extensible links.

Analytical relations for the mechanical response of single polymer chains are valuable for modeling purposes, on both the molecular and the continuum scale. These relations can be obtained using statistical thermodynamics and an idealized single-chain model, such as the freely jointed chain model. To include bond stretching, the rigid links in the freely jointed chain model can be made extensible, but this almost always renders the model analytically intractable. Here, an asymptotically correct statistical thermodynamic theory is used to develop analytic approximations for the single-chain mechanical response of this model. The accuracy of these approximations is demonstrated using several link potential energy functions. This approach can be applied to other single-chain models, and to molecular stretching in general.

Single-chain models illustrate the 3D RNA folding shape during translation

The three-dimensional conformation of RNA is important in the function and fate of the molecule. The common conformation of mRNA is formed based on the closed-loop structure and internal base pairings with the activity of the ribosome movements. However, recent reports suggest that the closed-loop structure might not be formed in many mRNAs. This implies that mRNA can be considered as a single polymer in the cell. Here, we introduce the Three-dimensional RNA Illustration Program (TRIP) to model the three-dimensional RNA folding shape based on single-chain models and angle restriction of each bead component from previously reported single-molecule fluorescence in situ hybridization (smFISH) experimental data. This simulation method was able to recapitulate the mRNA conformation change of the translation activity and three-dimensional positional interaction between an organelle and its localized mRNAs as end-to-end distances. Within the analyzed cases, base-pairing interactions only have minor effects on the three-dimensional mRNA conformation, and instead single-chain polymer characteristics have a more significant impact on the conformation. This top-down method will be used to interpret the aggregation mechanism of mRNA under different cellular conditions such as nucleolus and phase-separated granules.

Clarifying the effect of chemical structure on high-temperature resistance of polyimides based on DFT and ReaxFF based molecular dynamic simulation

In this work, the pyrolysis route and high-temperature resistance of 3,3′, 4,4′-biphenyltetracarboxylic dianhydride (BPDA)/p-phenylenediamine (p-PDA), BPDA/m-phenylenediamine (m-PDA), BPDA/3,5-diaminobenzoic acid (DABA), BPDA/4,4′-oxydianiline (ODA), pyromellitic dianhydride (PMDA)/ODA, and 4,4′-oxydiphthalic anhydride (ODPA)/ODA were studied by molecular simulation and thermogravimetric analysis (TGA). Simulation based on density functional theory (DFT) was used for isothermal pyrolysis simulation of single-chain block copolymer models; molecular dynamics (MD) based on reaction force field (ReaxFF) was used for isothermal pyrolysis simulation of condensed state models. Two novel and facile methods, named as fragment counting method and total substances counting method, respectively, were proposed to evaluate the high-temperature resistance and explore the pyrolysis mechanisms of PIs. The results show that the BPDA/p-PDA PI presents the best thermostability. Compared with p-PDA, introducing m-PDA and DABA promotes the cleavages of C–N bonds and benzene rings to impair the high-temperature stability of PIs molecular chains. In addition, carboxyl groups in DABA lead to the release of large amounts of CO2 during pyrolysis process. The cleavage of ether bonds in ODA and ODPA is observed at the early stage of pyrolysis, therefore leading to significant decrease of high-temperature resistance of PIs. PMDA slightly reduces the high-temperature resistance of PIs compared with BPDA when the diamine unit is ODA. Besides, 2 kinds of pyrolysis mechanisms are revealed by analyzing the proportion of volatiles in the by-products. In DABA-containing PIs, the pyrolysis process is dominated by the generation of volatiles and molecular chains breakage, and presents two-stage weight loss, which is considered as the first pyrolysis mechanism. The pyrolysis process of DABA-free PIs is dominated by molecular chains cleavage, and displays only one-stage weight loss, which is considered as the second mechanism. The above simulation results are in good agreement with the experimental results from TGA, proving the reliability of the simulation. Mayer bond order (MBO) analysis of the target PI models was performed, and it is found that varying the chemical structure will lead to significant changes of bond strength, which is suggested to be one of the important reasons affecting the high-temperature stability and pyrolysis process of PIs. This work is believed to be of great help to the molecular design of high-temperature resistance PIs.

Molecular dynamics simulation of nonisothermal crystallization of a single polyethylene chain and short polyethylene chains based on OPLS force field

Abstract Molecular dynamics simulations on the nonisothermal crystallization of a single polyethylene chain and short polyethylene chains based on the all-atom model and optimized potentials for liquid simulations-all atom (OPLS-AA) force field are conducted in this article. Four all-atom single chain models with different chain lengths (C1000, C2000, C3000, and C4000) and four all-atom short chain models with the same chain length and different number of chains (2C500, 4C500, 6C500, and 8C500) are constructed. The collapse process at a high temperature of 600 K and the nonisothermal crystallization process with different cooling rates at the temperature range of 600–300 K are simulated. Roles of chain length, number of chains, cooling rate on the potential energy, van der Waals (V dw) energy, radius of gyration, root mean square deviation, and crystallinity are explored. By comparing with the existing results obtained by the united atom model, the validity and accuracy of this study are proved. Results show that in the collapse process, the chain length is the major factor, whereas the cooling rate has the greatest influence during the nonisothermal crystallization process. As the cooling rate decreases, a “platform” appeared in the V dw energy curve, which has a profound impact on the crystallization.

Sticky Rouse Model and Molecular Dynamics Simulation for Dual Polymer Networks

Dual polymer networks with stickers have a reputation for enhanced modulus and toughness. We propose a modified sticky Rouse model (SRM) from the single-chain perspective for permanent and transient dual networks, aiming to find a universal description of associative polymer dynamics. The computational complexity of obtaining the analytical relaxation spectrum is simplified by graph theory, implementing matrix reduction of the Rouse–Zimm matrix based on the symmetry. The analytical relaxation spectrum can also return to the case of linear polymers and permanent networks. The modified SRM for dual polymer networks predicts a Rouse-like scale of the linear relaxation modulus G(t) ∝ t–1/2 in sticker relaxation, consistent with the existing experimental results. In particular, the key parameter in the SRM, namely, the effective friction coefficient, can be extracted from the lifetime of sticky bonds and diffusion of chains, obtained by molecular dynamics simulations (MD). Based on that, the SRM model can predict the linear viscoelasticity of dual polymer networks, quantitatively in agreement with our MD results. Our work strongly supports the applicability of the single-chain molecular model SRM for polymer complex networks with reversible associative interactions.

The Impacts of the Cross-Chain Collaboration Center Model on Transportation Performance: A Case Study of a Bulk Transportation Network in Thailand

This paper studies the impacts of a cross-chain collaboration center model (4CM) on bulk transportation network performance. The 4CM is based on the interaction and collaboration between shippers and carriers participating in the transportation network. The network formulation is based on collaborative bidirectional multi-period vehicle routing (CBMVRP). The performance of the 4CM is represented by three transportation performance indices, including the percentage differences in the total cost, shipper cost and carrier cost between the 4CM and single-chain collaboration model (SCCM). The impacts of the 4CM are investigated using five uncertain input parameters: fuel cost, holding cost, maximum acceptable proportion of the differences between the cost of a carrier and average cost of all carriers, demand per job and number of vehicles per carrier. An experiment was conducted according to a central composite design (CCD). The proposed methodology was applied to assess bulk transportation in Thailand. The computational results revealed that a 4CM can significantly reduce the differences in the total cost, shipper cost and carrier cost. Moreover, we organized a focus group to collect data about the criteria and the probability of changing from an SCCM to a 4CM of the case study network and generated a classification tree of the levels of possibility to change from an SCCM to a 4CM for each possible situation using the ID3 algorithm.

Radial Distribution Functions of Entanglements in Primitive Chain Network Simulations

Although the entanglement network among polymers has been widely investigated, the spatial distribution of entanglement nodes has been rarely discussed. In this study, we obtained the radial distribution functions (RDFs) for the entanglement nodes from the snapshots of multi-chain slip-link simulations. The model employed in this study is the primitive chain network (PCN) model, which has been validated to reproduce the entangled polymer dynamics semi-quantitatively. The statistics of captured entanglement networks were compared to those reported for the primitive path network extracted by the CReTA procedure from the full-atomistic molecular model of a polyethylene melt. In the range of distance longer than the average strand length, the network structure from PCN does not show any structural correlation, and the intra-chain correlation is close to that for Gaussian chains with non-interacting slip-links. These features are consistent with the CReTA network and the conventional assumptions made for single-chain models. Meanwhile, in the short-range, the structural correlation in PCN is much weaker than that in CReTA. This discrepancy is because the short-range structure in PCN is realized as a result of imposed fluctuations, whereas it is determined by the minimization of the primitive path in CReTA.