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The complex anatomy of teeth limits the accessibility and efficacy of regenerative treatments. Therefore, the application of well-known inducers as injectable hydrogels for the regeneration of the dentin-pulp complex is considered a promising approach. In this regard, this study aimed to develop an injectable hydrogel containing mineral trioxide aggregate (MTA). The injectable chitosan/oxidized-nanocrystalline cellulose/MTA (CS/OCNC/MTA) hydrogels were prepared, and the physicochemical properties of these hydrogels were evaluated by TGA, FTIR, Rheological analysis, and SEM. Moreover, the effect of MTA on the swelling and degradability of scaffolds was assessed. The proliferative effects of synthesized hydrogels were also determined on human dental pulp stem cells (hDPSCs) by MTT assay. For induction of differentiation and biomineralization in these cells, the alkaline phosphatase activity and Alizarin Red S staining tests were performed in the presence of fabricated scaffolds. The proliferation of hDPSCs was significantly increased in the presence of these hydrogels. Moreover, the addition of MTA to hydrogel structure dramatically improved the differentiation of hDPSCs. These results suggested that this novel injectable hydrogel provides appropriate physiochemical properties and can be considered a promising scaffold for regenerative endodontic procedures.
Graphical abstractFluid atomic behavior is an important factor for industrial applications. Computer simulations based on simple models predict Poiseuille flow for these atomic structures with the presence of external force. In this work, we describe the dynamical properties of Ar and O2 flows with precise atomic arrangement via dissipative particle dynamics (DPD) and molecular dynamics (MD) simulation approaches. In these methods, each model is represented by using Large-scale Atomic/Molecular Massively Parallel Simulator package. Simulation results show that maximum rate for velocity of Ar flow in platinum and copper microchannels is 0.100 (unit less)/0.091 Å ps?1 and 0.121 (unit less)/0.105 Å ps?1 by using DPD/MD approach. This atomic parameter changes to 0.111 (unit less)/0.102 Å ps?1 and 0.125 (unit less)/0.108 Å ps?1 for O2 fluid with mentioned approaches. By decreasing the microchannel size, the maximum rate of velocity reaches to 0.101 (unit less)/0.099 Å ps?1 and maximum temperature rate decreases to 485 (unit less)/440 K with DPD/MD approaches. These calculated parameters can be used in industrial application designing for some processes such as heat transfer in structures. It was seen that the developed DPD approach was able to simulate the fluid flow and heat transfer of various types of fluids at micro- and nanoscales with suitable accuracy versus MD.
相似文献Pyrolysis is a commonly used method for the recovery of used lubricating oil (ULO), which should be kinetically improved by a catalyst, due to its high level of energy consumption. In this research, the catalytic effects of carbon nanotube (CNT) and graphene nanoplatelets on the pyrolysis of ULO were studied through thermogravimetric analysis. First, the kinetic parameters of ULO pyrolysis including activation energy were calculated to be 170.12 and 167.01 kJ mol?1 by FWO and KAS methods, respectively. Then, the catalytic effects of CNT and graphene nanoplatelets on pyrolysis kinetics were studied. While CNT had a negligible effect on the pyrolysis process, graphene nanoplatelets significantly reduced the temperature of maximum conversion during pyrolysis from 400 to 350 °C, due to high thermal conductivity and homogenous heat transfer in the pyrolysis process. On the other hand, graphene nanoplatelets maximized the rate of conversion of highly volatile components at lower temperatures (<?100 °C), which was mainly due to the high affinity of these components toward graphene nanoplatelets and also the effect of nanoplatelets’ edges which have free tails and can bond with other molecules. Moreover, graphene nanoplatelets decreased the activation energy of the conversion to 154.48 and 152.13 kJ mol?1 by FWO and KAS methods, respectively.
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