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Accurate prediction of the remaining useful life (RUL) is a key function for ensuring the safety and stability of lithium-ion batteries. To solve the capacity regeneration and model adaptability under different working conditions, a hybrid RUL prediction model based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and a bi-directional gated recurrent unit (BiGRU) is proposed. CEEMDAN is used to divide the capacity into intrinsic mode functions (IMFs) to reduce the impact of capacity regeneration. In addition, an improved grey wolf optimizer (IGOW) is proposed to maintain the reliability of the BiGRU network. The diversity of the initial population in the GWO algorithm was improved using chaotic tent mapping. An improved control factor and dynamic population weight are adopted to accelerate the convergence speed of the algorithm. Finally, capacity and RUL prediction experiments are conducted to verify the battery prediction performance under different training data and working conditions. The results indicate that the proposed method can achieve an MAE of less than 4% with only 30% of the training set, which is verified using the CALCE and NASA battery data.

Insulators of the kind used for overhead transmission lines institute important kinds of insulation control, namely, electrical insulation and mechanical fixing. Because of their large exposure to the environment, they are affected by factors such as climate, temperature, durability, the easy occurrence of explosions, damage, the threat of going missing, and other faults. These seriously influence the safety of the power transmission, so insulation monitoring must be conducted. With the development of unmanned technology, the staff used unmanned aircraft to take aerial photos of the detected insulators, and the insulator images were obtained by naked eye observation. Although this method looks very reliable, in practice, due to the large quantity of insulator-collected seismic data, and the complex background, workers are usually relying on their experience to make judgements, so it is easy for mistakes to appear. In recent years, with the rapid development of computer technology, more and more attention has been paid to fault detection and identification in insulators by computer-aided workers. In order to improve the detection accuracy of self-exploding insulators, especially in bad weather environments, and to overcome the influence of fog on target detection, a regression attention convolutional neural network is used for optimization. Through the recursive operation of multi-scale attention, multi-scale feature information is connected in series, the regional focus is recursively generated from coarse to fine, and the target region is detected to achieve optimal results. The experimental results show that the proposed method can effectively improve the fault diagnosis ability of insulators. Compared with the accuracy of other basic models, such as FCAN and MG-CNN, the accuracy of RA-CNN in multi-layer cascade optimization is higher than that in the previous two models, which is 74.9% and 75.6%, respectively. In addition, the results of the ablation experiments at different scales showed that the identification results of different two-level combinations were 78.2%, 81.4%, and 83.6%, and the accuracy of selecting three-level combinations was up to 85.3%, which was significantly higher than the other models.

Combined with the theoretical calculations, electrocatalysts for hydrogen evolution reaction (HER) with unprecedented catalytic performance compared to Pt/C are rationally designed and synthesized. Herein, we perform the density functional theory (DFT) calculations to predict remarkable catalytic performance of Fe 0.33 Co 0.33 Ni 0.33 P for the close to zero free energy value of hydrogen absorption. Based on the theoretical prediction, a series of highly efficient homogeneous quadruple multimetallic phosphides of Fe x Co y Ni z P (where x+y+z=1) nanosheet for HER was successfully prepared. Surprisingly, the experimental results were in agreement with the theoretical prediction. The afforded Fe 0.33 Co 0.33 Ni 0.33 P electrocatalyst exhibits the lowest overpotential of 38 mV and 89 mV to achieve the current density of 10 mA/cm 2 and 100 mA/cm 2 respectively, and long-term stability in acidic electrolyte. To our knowledge, the activity of Fe 0.33 Co 0.33 Ni 0.33 P is superior to most of the known HER catalysts reported to date, proving the feasibility of Fe x Co y Ni z P to improve HER activity.

The execution of the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER) requires active, low-cost, and earth-abundant electrocatalysts to realize large-scale water splitting. Herein, by utilization of the electrodeposition technique, a new category of nickel-based materials, i.e. nanoporous nickel hydroxide@nickel (Ni(OH)2@Ni) films on carbon cloth (Ni(OH)2@Ni/CC), has been reported as a Janus electrocatalyst for overall water splitting. The as-deposited Ni(OH)2@Ni/CC exhibited remarkable catalytic performance for the HER in alkaline electrolytes with an overpotential of 68 mV needed to drive the current density of 10 mA cm−2 and much better durability than Pt/C. This film is also efficient for catalyzing the OER in basic media. These films can be employed as catalysts on both the anode and cathode for overall water splitting that approaches 10 mA cm−2 at a cell voltage of 1.58 V, with catalytic stability exceeding those with RuO2 and Pt/C catalysts. Density functional theory calculations further demonstrate that the Ni(OH)2 and Ni in Ni(OH)2@Ni films synergistically favor the chemisorption of hydrogen-containing intermediates, thus leading to highly enhanced water splitting activity.

Atomically mimicking the enzyme-like active sites based on nanomaterials would develop unexpected single-atom nanozymes., Conventional nanozyme technologies face formidable challenges of intricate size-, composition-, and facet-dependent catalysis and inherently low active site density. We discovered a new class of single-atom nanozymes with atomically dispersed enzyme-like active sites in nanomaterials, which significantly enhanced catalytic performance, and uncovered the underlying mechanism. With oxidase catalysis as a model reaction, experimental studies and theoretical calculations revealed that single-atom nanozymes with carbon nanoframe–confined FeN5 active centers (FeN5 SA/CNF) catalytically behaved like the axial ligand–coordinated heme of cytochrome P450. The definite active moieties and crucial synergistic effects endow FeN5 SA/CNF with a clear electron push-effect mechanism, as well as the highest oxidase-like activity among other nanozymes (the rate constant is 70 times higher than that of commercial Pt/C) and versatile antibacterial applications. These suggest that the single-atom nanozymes have great potential to become the next-generation nanozymes.

Replacement of precious Pt with earth-abundant electrocatalysts for the hydrogen evolution reaction (HER) holds great promise for clean energy devices, but the development of low-cost and durable HER catalysts with Pt-like activity is still a huge challenge. In this communication, we report on the development of self-standing ternary FexCo1–xP nanowire array on carbon cloth (FexCo1–xP/CC) as a Pt-free HER catalyst with activities being strongly related to Fe substitution ratio. Electrochemical tests show that Fe0.5Co0.5P/CC not only possesses Pt-like activity with the need of overpotential of only 37 mV to drive 10 mA cm–2, outperforming all non-noble-metal HER catalysts reported to date, but demonstrates superior long-term durability in 0.5 M H2SO4. Density functional theory calculations further reveal that Fe substitution of Co in CoP leads to more optimal free energy of hydrogen adsorption to the catalyst surface. This study offers us a promising flexible monolithic catalyst for practical applications.

The reduction of O

Replacement of precious Pt with earth-abundant electrocatalysts for the hydrogen evolution reaction (HER) holds great promise for clean energy devices, but the development of low-cost and durable HER catalysts with Pt-like activity is still a huge challenge. In this communication, we report on the development of self-standing ternary Fe

We report a high-yield strategy for the synthesis of very small silver nanoclusters (2 to 5 silver atoms) formed from conventional silver salts and scaffolds as high-performance catalysts for oxygen reduction reaction (ORR). The work demonstrates that Ag NCs are excellent catalysts for ORR and show great potential in alkaline fuel cells.

Adenylate kinase (ADK) has been explored widely, through both experimental and theoretical studies. However, still less is known about how the functional dynamics of ADK is modulated explicitly by its natural substrates. Here, we report a quantitative study of the dynamic energy landscape for ADK responding to the substrate binding by integrating both experimental investigations and theoretical modeling. We make theoretical predictions which are in remarkable agreement with the single molecule experiments on the substrate-bound complex. With our combined models of ADK in its apo form, in the presence of AMP or ATP, and in complex with both substrates, we specifically address the following key questions: (1) Are there intermediate state(s) during their catalytic cycle and if so how many? (2) How many pathways are there along the open-to-closed transitions and what are their corresponding weights? (3) How do substrates influence the pathway weights and the stability of the intermediates? (4) Which lid's motion is rate-limiting along the turnover cycle, the NMP or the LID domain? Our models predict two major parallel stepwise pathways and two on-pathway intermediates which are denoted as IN (NMP domain open while LID domain closed) and IL (LID domain open and NMP domain closed), respectively. Further investigation of temperature effects suggests that the IN pathway is dominant at room temperature, but the IL pathway is dominant at the optimal temperature. This leads us to propose that the IL pathway is more dominant by entropy and IN pathway by enthalpy. Remarkably, our results show that even with maximum concentrations of natural substrates, ADK still fluctuates between multiple functional states, reflecting an intrinsic capability of large-scale conformational fluctuations which may be essential to its biological function. The results based on the dual-ligands model provide the theoretical validation of random bisubstrate biproducts (Bi-Bi) mechanism for the enzymatic reaction of ADK. Additionally, the pathway flux analysis strongly suggests that the motion of the NMP domain is the rate-determining step for the conformational cycle (opening and closing).

A three-tiered cake-style composite is elaborately established, with the characteristic of a double-deck of MoS2 nanosheets and reduction of graphene oxide (RGO) sheets dotted with CoS2 nanoparticles (CoS2@MoS2/RGO). Because of the prominent synergistic effect of graphene acting as conductive support, MoS2 and CoS2 providing abundant catalytically active sites, and the cake-style structure promoting mechanical stability, the CoS2@MoS2/RGO exhibits a superior hydrogen evolution reaction activity with a small overpotential of 98 mV at cathodic current density of 10 mA cm−2, and a small Tafel slope of 37.4 mV dec−1, as well as excellent cycling stability. Density functional theory calculations reveal that the hydrogen adsorption free energy of CoS2@MoS2/RGO is close to zero.

Biomolecular functions are determined by their interactions with other molecules. Biomolecular recognition is often flexible and associated with large conformational changes involving both binding and folding. However, the global and physical understanding for the process is still challenging. Here, we quantified the intrinsic energy landscapes of flexible biomolecular recognition in terms of binding–folding dynamics for 15 homodimers by exploring the underlying density of states, using a structure-based model both with and without considering energetic roughness. By quantifying three individual effective intrinsic energy landscapes (one for interfacial binding, two for monomeric folding), the association mechanisms for flexible recognition of 15 homodimers can be classified into two-state cooperative “coupled binding–folding” and three-state noncooperative “folding prior to binding” scenarios. We found that the association mechanism of flexible biomolecular recognition relies on the interplay between the underlying effective intrinsic binding and folding energy landscapes. By quantifying the whole global intrinsic binding–folding energy landscapes, we found strong correlations between the landscape topography measure Λ (dimensionless ratio of energy gap versus roughness modulated by the configurational entropy) and the ratio of the thermodynamic stable temperature versus trapping temperature, as well as between Λ and binding kinetics. Therefore, the global energy landscape topography determines the binding–folding thermodynamics and kinetics, crucial for the feasibility and efficiency of realizing biomolecular function. We also found “U-shape” temperature-dependent kinetic behavior and a dynamical cross-over temperature for dividing exponential and nonexponential kinetics for two-state homodimers. Our study provides a unique way to bridge the gap between theory and experiments.

Basic evidence is provided for the benefits of using cytosine-rich DNA strands as scaffolds for fluorescent silver nanoclusters. The DFT-calculated fluorescence spectra of silver nanoclusters (AgNCs) protected by DNA monomers (dC, dA, dT, and dG) were in good agreement with the experimentally obtained spectra, showing that only the use of cytosine-rich DNA strands as scaffolds gives fluorescent nanoclusters.

The identification and application of druggable pockets of targets play a key role in in silico drug design, which is a fundamental step in structure-based drug design. Herein, some recent progresses and developments of the computational analysis of pockets have been covered. Also, the pockets at the protein-protein interfaces (PPI) have been considered to further explore the pocket space for drug discovery. We have presented two case studies targeting the kinetic pockets generated by normal mode analysis and molecular dynamics method, respectively, in which we focus upon incorporating the pocket flexibility into the two-dimensional virtual screening with both affinity and specificity. We applied the specificity and affinity (SPA) score to quantitatively estimate affinity and evaluate specificity using the intrinsic specificity ratio (ISR) as a quantitative criterion. In one of two cases, we also included some applications of pockets located at the dimer interfaces to emphasize the role of PPI in drug discovery. This review will attempt to summarize the current status of this pocket issue and will present some prospective avenues of further inquiry.

Self-assembled monolayers (SAMs) of 4,4'-thiobisbenzenethiol (TBBT) can be formed on Au surface spontaneously. The structural characteristics and adsorption behavior of TBBT SAMs on Au have been investigated by surface enhanced Raman scattering (SERS), electrochemical cyclic voltammetry (CV), ac impedance spectroscopy (EIS), and atomic force microscopy (AFM). It is demonstrated that TBBT adsorbed on Au by losing a H atom, forming one Au-S bond, and the other mercapto group is free at the surface of the monolayer owing to the presence of the nu(S-H) at 2513 cm(-1) and the delta(C-S-H) at 910 cm(-1) in SERS. The enhancement of the vibration of C-S (1064 cm(-1)), the aromatic C-H vibration (3044 cm(-1)), and the absence of the vibration of S-S illustrate TBBT adsorbed on Au forming a monolayer with one benzene ring tilted with respect to the Au surface. The interpretation of the observed frequencies is aided by ab initio molecular orbital (MO) calculations at the HF/6-31G level of theory. Electrochemical CV and EIS indicate TBBT monolayers can passivate the Au effectively for its low ratio of pinhole defects (theta = 99.6%). AFM studies give details about the surface morphology. The applications of TBBT SAMs have been extensively investigated by exposure of Cu2+ ion to TBBT SAMs on Au and covalent adsorption of metal nanoparticles. Electrochemical, X-ray photoelectron spectroscopic, and SERS results indicate that Cu2+ can react with TBBT SAMs and present on TBBT SAMs as Cu(I). A scanning electron microscopic image of Ag nanoparticles on TBBT/Au and the Raman spectrum of TBBT in smooth macroscopic Au/TBBT SAMs/Ag nanoparticle sandwich structure indicate that metal nanoparticles can be adsorbed on TBBT SAMs effectively through covalent linkage.

A facile synthesis of chiral penicillamine protected Au nanoclusters with different optical properties has been reported. We have for the first time observed the reversal of CD signals after the scaffolds adsorbed onto the surface of Au NCs. Such Au NCs are utilized for bioimaging due to their low cytotoxicity and stable fluorescence emission.

Histone chaperones facilitate assembly and disassembly of nucleosomes. Understanding the process of how histone chaperones associate and dissociate from the histones can help clarify their roles in chromosome metabolism. Some histone chaperones are intrinsically disordered proteins (IDPs). Recent studies of IDPs revealed that the recognition of the biomolecules is realized by the flexibility and dynamics, challenging the century-old structure-function paradigm. Here we investigate the binding between intrinsically disordered chaperone Chz1 and histone variant H2A.Z-H2B by developing a structure-based coarse-grained model, in which Debye-Hückel model is implemented for describing electrostatic interactions due to highly charged characteristic of Chz1 and H2A.Z-H2B. We find that major structural changes of Chz1 only occur after the rate-limiting electrostatic dominant transition state and Chz1 undergoes folding coupled binding through two parallel pathways. Interestingly, although the electrostatic interactions stabilize bound complex and facilitate the recognition at first stage, the rate for formation of the complex is not always accelerated due to slow escape of conformations with non-native electrostatic interactions at low salt concentrations. Our studies provide an ionic-strength-controlled binding/folding mechanism, leading to a cooperative mechanism of “local collapse or trapping” and “fly-casting” together and a new understanding of the roles of electrostatic interactions in IDPs' binding., Author Summary Histone chaperones facilitate the assembly and disassembly of nucleosome by interacting with the corresponding histones or histone variants. As the biomolecules in nucleosome are highly charged, electrostatic interactions are particularly important in these processes. The experiments have explored that the histone chaperon Chz1 as an intrinsically disordered protein (IDP) can fold by binding to its histone variants H2A.Z-H2B. Here, we developed a molecular simulation program that treated electrostatic interactions with Debye-Hückel model to study the mechanism of the association. We found that the inter-chain electrostatic interactions facilitate the coupled folding and binding transitions, consistent with the kinetic experiments and microscopic structural perspectives. Furthermore, we show that the intra-chain electrostatic interactions collapse Chz1 and slow the binding rate. The collapsed structure in IDPs caused by intra-chain electrostatic interactions has been widely found in experiments and the effect in binding is well studied in our work. Our theoretical approach shed new light on the role of electrostatics on inter-chain and intra-chain interactions for IDPs' binding and is applicable to the binding/folding of other IDPs to their targets.