收费全文 | 2298篇 |
免费 | 482篇 |
国内免费 | 449篇 |
化学 | 1055篇 |
晶体学 | 36篇 |
力学 | 163篇 |
综合类 | 8篇 |
数学 | 712篇 |
物理学 | 1255篇 |
2024年 | 9篇 |
2023年 | 93篇 |
2022年 | 106篇 |
2021年 | 115篇 |
2020年 | 134篇 |
2019年 | 109篇 |
2018年 | 115篇 |
2017年 | 124篇 |
2016年 | 133篇 |
2015年 | 164篇 |
2014年 | 172篇 |
2013年 | 235篇 |
2012年 | 267篇 |
2011年 | 234篇 |
2010年 | 165篇 |
2009年 | 192篇 |
2008年 | 131篇 |
2007年 | 139篇 |
2006年 | 127篇 |
2005年 | 81篇 |
2004年 | 48篇 |
2003年 | 40篇 |
2002年 | 37篇 |
2001年 | 32篇 |
2000年 | 29篇 |
1999年 | 29篇 |
1998年 | 33篇 |
1997年 | 15篇 |
1996年 | 13篇 |
1995年 | 16篇 |
1994年 | 7篇 |
1993年 | 10篇 |
1992年 | 4篇 |
1991年 | 9篇 |
1990年 | 4篇 |
1989年 | 4篇 |
1988年 | 11篇 |
1987年 | 27篇 |
1986年 | 8篇 |
1985年 | 4篇 |
1983年 | 1篇 |
1981年 | 2篇 |
1936年 | 1篇 |
High-velocity oxy-fuel (HVOF)-sprayed metallic coating can be used to create a surface layer that plays a significant role in enhancing the overall strength, stiffness, and fatigue life of the treated material. The micro-deformation around a single impacted particle is a critical factor that must be considered for the optimization of the HVOF process.
ObjectiveIn this study, the micro-deformation field of stainless steel impacted by a ceramic particle was characterized at the micro-scale.
MethodA grid with a frequency of 1200 lines/mm was fabricated on the surface of stainless steel specimen. The microscopic deformation field formed on the substreate surface, induced by the impact of micro-particles with a diameter of 18 µm, was determined using the electron moiré method and numerical simulations.
ResultsThe in-plane plastic strain around the impacted particle was found to be as high as 9.1%, and the value sharply decreased with the increase of the distance to the edge of the impacted particle. The diameter of the plastic area was about 40 µm, which was approximately 2.2 times larger than the particle size. The experimental results were compared with numerical simulation results, and good agreement between the results was found.
ConclusionsThe electron moiré technique can be a useful tool for the measurement of the deformation field induced by an impacted particle in a very local area with a size on the order of microns.
相似文献Although many effective methods for solving partial differential equations (PDEs) have been proposed, there is no universal method that can solve all PDEs. Therefore, solving partial differential equations has always been a difficult problem in mathematics, such as deep neural network (DNN). In recent years, a method of embedding some basic physical laws into traditional neural networks has been proposed to reveal the dynamic behavior of equations directly from space-time data [i.e., physics-informed neural network (PINN)]. Based on the above, an improved deep learning method to recover the new soliton solution of Huxley equation has been proposed in this paper. As far as we know, this is the first time that we have used an improved method to study the numerical solution of the Huxley equation. In order to illustrate the advantages of the improved method, we use the same network depth, the same hidden layer and neurons contained in the hidden layer, and the same training sample points. We analyze the dynamic behavior and error of Huxley’s exact solution and the new soliton solution and give vivid graphs and detailed analysis. Numerical results show that the improved algorithm can use fewer sample points to reconstruct the exact solution of the Huxley equation with faster convergence speed and better simulation effect.
相似文献