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| 1 | Direct electrochemistry behavior of Cytochrome c on silicon dioxide nanoparticles-modified electrode显示文摘A newfangled direct electrochemistry behavior of Cytochrome c (Cyt c) was found on glassy carbon (GC) electrode modified with the silicon dioxide (SiO2) nanoparticles by physical adsorption. A pair of stable and well-defined redox peaks of Cyt c′ quasi-reversible electrochemical reaction were obtained with a heterogeneous electron transfer rate constant of 1.66×10-3 cm/s and a formal potential of 0.069 V (vs. Ag/AgCl) (0.263 V versus NHE) in 0.1 mol/L pH 6.8 PBS. Both the size and the amount of SiO2 nanoparticles could influence the electron transfer between Cyt c and the electrode. Electrostatic interaction which is between the negative nanoparticle surface and positively charged amino acid residues on the Cyt c surface is of importance for the stability and reproducibility toward the direct electron transfer of Cyt c. It is suggested that the modification of SiO2 nanoparticles proposes a novel approach to realize the direct electrochemistry of proteins. | ZHU Lin SUN DongMei LU TianHong CAI ChenXin LIU ChangPeng XING Wei | 2007 | Science China Chemistry2007，50，3： | 1 |
| 2 | Multi-scale modeling of Arabidopsis thaliana response to different CO2 conditions: From gene expression to metabolic flux显示文摘Multi-scale investigation from gene transcript level to metabolic activity is important to uncover plant response to environment perturbation. Here we integrated a genome-scale constraint-based metabolic model with transcriptome data to explore Arabidopsis thaliana response to both elevated and low CO_2 conditions. The four condition-specific models from low to high CO_2 concentrations show differences in active reaction sets, enriched pathways for increased/decreased fluxes, and putative post-transcriptional regulation, which indicates that condition-specific models are necessary to reflect physiological metabolic states. The simulated CO_2 fixation flux at different CO_2 concentrations is consistent with the measured Assimilation-CO_2 intercellularcurve. Interestingly, we found that reactions in primary metabolism are affected most significantly by CO_2 perturbation, whereas secondary metabolic reactions are not influenced a lot. The changes predicted in key pathways are consistent with existing knowledge. Another interesting point is that Arabidopsis is required to make stronger adjustment on metabolism to adapt to the more severe low CO_2 stress than elevated CO_2. The challenges of identifying post-transcriptional regulation could also be addressed by the integrative model. In conclusion, this innovative application of multi-scale modeling in plants demonstrates potential to uncover the mechanisms of metabolic response to different conditions. | Lin Liu Fangzhou Shen Changpeng Xin Zhuo Wang | 2016 | Journal of Integrative Plant Biology2016，58，1： | 1 |
| 3 | Enhancing low-temperature electrochemical kinetics and high-temperature cycling stability by decreasing ionic packing factor显示文摘Present-day Liþstorage materials generally suffer from sluggish low-temperature electrochemical kinetics and poor high-temperature cycling stability.Herein,based on a Ca2þsubstituted Mg_(2)Nb_(34)O_(87) anode material,we demonstrate that decreasing the ionic packing factor is a two-fold strategy to enhance the low-temperature electrochemical kinetics and high-temperature cyclic stability.The resulting Mg_(1.5)Ca_(0.5)Nb_(34)O_(87) shows the smallest ionic packing factor among Wadsley–Roth niobate materials.Compared with Mg_(2)Nb_(34)O_(87),Mg1.5Ca0.5Nb_(34)O_(87) delivers a 1.6 times faster Liþdiffusivity at-20C,leading to 56%larger reversible capacity and 1.5 times higher rate capability.Furthermore,Mg_(1.5)Ca_(0.5)Nb_(34)O_(87) exhibits an 11%smaller maximum unit-cell volume expansion upon lithiation at 60℃,resulting in better cyclic stability;at 10C after 500 cycles,it has a 7.1%higher capacity retention,and its reversible capacity at 10C is 57%larger.Therefore,Mg_(1.5)Ca_(0.5)Nb_(34)O_(87) is an allclimate anode material capable of working at harsh temperatures,even when its particle sizes are in the order of micrometers. | Changpeng Lv Chunfu Lin Xiu Song Zhao | 2023 | eScience2023，3，6： | 0 |
| 4 | Anti-Jahn-Teller effect induced ultrafast insulator to metal transition in perovskite BaBiO_(3)显示文摘The Jahn-Teller(JT)effect involves the ions M with a degenerate electronic state distorting the corner-sharing MO_(6)octahedra to lift the degeneracy,inducing strong coupling of electrons to lattice,and mediating the exotic properties in perovskite oxides.Conversely,the anti-Jahn–Teller(AJT)effect refers to the deformation against the Jahn-Teller-distorted MO_(6)octahedra.However,it is difficult to experimentally execute both effects descending from the fine-tuning of crystal structures.We propose the AJT can be introduced by THz laser illumination at 11.71 THz in a candidate superconducting perovskite material BaBiO_(3)near room temperature.The illumination coherently drives the infrared-active phonon that excites the Raman breathing mode through the quadratic-linear nonlinear interaction.The process is characterized by the emergence of an AJT effect,accompanied by an insulator-to-metal transition occurring on the picosecond timescale.This study underlines the important role of crystal structure engineering by coherent phonon excitation in designing optoelectronic devices. | Nan Feng Jian Han Changpeng Lin Zhengwei Ai Chuwen Lan Ke Bi Yuanhua Lin Kan-Hao Xue Ben Xu | 2022 | npj Computational Materials2022，，1： | 0 |
| 5 | General invariance and equilibrium conditions for lattice dynamics in 1D,2D,and 3D materials显示文摘The long-wavelength behavior of vibrational modes plays a central role in carrier transport,phonon-assisted optical properties,superconductivity,and thermomechanical and thermoelectric properties of materials.Here,we present general invariance and equilibrium conditions of the lattice potential;these allow to recover the quadratic dispersions of flexural phonons in low-dimensional materials,in agreement with the phenomenological model for long-wavelength bending modes.We also prove that for any low-dimensional material the bending modes can have a purely out-of-plane polarization in the vacuum direction and a quadratic dispersion in the long-wavelength limit.In addition,we propose an effective approach to treat invariance conditions in crystals with non-vanishing Born effective charges where the long-range dipole-dipole interactions induce a contribution to the lattice potential and stress tensor.Our approach is successfully applied to the phonon dispersions of 158 two-dimensional materials,highlighting its critical relevance in the study of phonon-mediated properties of low-dimensional materials. | Changpeng Lin Samuel Poncé Nicola Marzari | 2022 | npj Computational Materials2022，，1： | 0 |
| 6 | Million-scale data integrated deep neural network for phonon properties of heuslers spanning the periodic table显示文摘Existing machine learning potentials for predicting phonon properties of crystals are typically limited on a material-to-materialbasis, primarily due to the exponential scaling of model complexity with the number of atomic species. We address this bottleneckwith the developed Elemental Spatial Density Neural Network Force Field, namely Elemental-SDNNFF. The effectiveness andprecision of our Elemental-SDNNFF approach are demonstrated on 11,866 full, half, and quaternary Heusler structures spanning 55elements in the periodic table by prediction of complete phonon properties. Self-improvement schemes including active learningand data augmentation techniques provide an abundant 9.4 million atomic data for training. Deep insight into predicted ultralowlattice thermal conductivity (<1 Wm^(−1) K^(−1)) of 774 Heusler structures is gained by p–d orbital hybridization analysis. Additionally, aclass of two-band charge-2 Weyl points, referred to as “double Weyl points”, are found in 68% and 87% of 1662 half and 1550quaternary Heuslers, respectively. | Alejandro Rodriguez Changpeng Lin Hongao Yang Mohammed Al-Fahdi Chen Shen Kamal Choudhary Yong Zhao Jianjun Hu Bingyang Cao Hongbin Zhang Ming Hu | 2023 | npj Computational Materials2023，，1： | 0 |
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