Isoflavonoids from Astragalus membranaceus Hairy Roots

Chemistry of Natural Compounds -     

Effect of temperature on the interactions between cellulose and lignin via molecular dynamics simulations

Cellulose - Heating is essential in various biomass pre-treatments and thermal conversion processes. It is of practical significance to study the characteristics of cellulose-lignin and...     

基于MOF (Cu)@biochar气凝胶的制备及其在缓释氮肥上的应用

以羧甲基纤维素(CMC)、明胶和MOF(Cu)@biochar为原料,采用简单有效的冷冻干燥方法制备了(CMC/Gelatin/MOF(Cu)@biochar)杂化气凝胶,并用傅里叶变换红外光谱(FT-IR)、热重分析(TG)、X射线粉末衍射(XRD)、扫描电镜(SEM)和X射线光电子能谱(XPS)技术对其进行了表征;研究了MOF(Cu)@biochar含量、pH和不同的盐水溶液对杂化气凝胶溶胀行为的影响;以该气凝胶负载氯化铵,制备了一种新型缓释肥料(SRF),并研究了含2%(wt)SRF的沙性土壤的保水能力;SRF在土壤中第30天的累积释放率为79.4%;肥料在土壤中释放符合非Fickian扩散和阳离子交换的协同作用机理。     

Revealing the Effect of Surface Composition on Multiwalled Carbon Nanotubes Supported Pt-Fe Alloy Electrocatalysts for Methanol Oxidation Performance

The designs of efficient and inexpensive Pt-based catalysts for methanol oxidation reaction (MOR) are essential to boost the commercialization of direct methanol fuel cells. Here, the highly catalytic performance PtFe alloys supported on multiwalled carbon nanotubes (MWCNTs) decorating nitrogen-doped carbon (NC) have been successfully prepared via co-engineering of the surface composition and electronic structure. The Pt₁Fe₃@NC/MWCNTs catalyst with moderate Fe³⁺ feeding content (0.86 mA/mg_Pt) exhibits 2.26-fold enhancement in MOR mass activity compared to pristine Pt/C catalyst (0.38 mA/mg_Pt). Furthermore, the CO oxidation initial potential of Pt₁Fe₃@NC/MWCNTs catalyst is lower relative to Pt/C catalyst (0.71 V and 0.80 V). Benefited from the optimal surface compositions, the anti-corrosion ability of MWCNT, strong electron interaction between PtFe alloys and MWCNTs and the N-doped carbon (NC) layer, the Pt₁Fe₃@NC/MWCNTs catalyst presents an improved MOR performance and anti-CO poisoning ability. This study would open up new perspective for designing efficient electrocatalysts for the DMFCs field.     

Graphene Saturable Absorber Mirror for Mode-Locked Orange Pulse Laser

Journal of Russian Laser Research - We demonstrate a passively-mode-locked Pr3+: LuLiF4 laser operated at the 604 nm orange wave-length, using monolayer graphene as a saturable absorber. The...     

Quantum Watermark Algorithm Based on Maximum Pixel Difference and Tent Map

International Journal of Theoretical Physics - A new quantum watermark algorithm is presented by combining maximum pixel difference partitioning with the least significant bit substitution...     

Large sets with multiplicity

Designs, Codes and Cryptography - Large sets of combinatorial designs has always been a fascinating topic in design theory. These designs form a partition of the whole space into combinatorial...     

基于不确定控制理论的最优策略研究

本文在不确定理论的框架下,研究一类带背景状态变量的最优控制模型.在乐观值准则下,利用不确定动态规划的方法,证明了不确定最优性原则,得到最优性方程.作为应用,求解一个固定缴费(DC)型养老金的最优投资策略问题,在乐观值准则下,以工资变量为背景状态变量,建立养老金模型.通过求解不确定最优性方程得到最优投资策略和最优支付率.     

Lower Bounds for the Robustness of Multilevel Coherence

International Journal of Theoretical Physics - Quantum coherence, coming from quantum superposition, occupies a significant position in the field of physics. We put forward a lower bound of the...     

基于GA_XGBoost模型的大学生科研能力预测问题研究

科学评价大学生科研创新能力对我国科研水平的提高具有重要意义.采用机器学习模型来预测大学生科研能力可以起到良好的效果,提出一种GAXGBoost模型来实现对大学生的科研能力预测.此模型是以Xgboost算法为基础,然后充分利用遗传算法的全局搜索能力自动搜索Xgboost最优超参数,避免了人为经验调参不准确的缺陷,最后采用精英选择策略以此确保每一轮都是最佳的进化结果.通过分析表明,所采用的GAXGBoost模型在大学生科研能力预测的结果中具有很高的精度,将此模型与Logistic Regression、Random Forest、SVM等模型进行对比,GAXGBoost模型的预测精度最高.