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991.
We analyze the coupled non-linear integro-differential equations whose solution is the thermodynamical limit of the empirical correlation and response functions in the Langevin dynamics for spherical p−spin disordered mean-field models. We provide a mathematically rigorous derivation of their FDT solution (for the high temperature regime) and of certain key properties of this solution, which are in agreement with earlier derivations based on physical grounds. AMS (2000) Subject Classification: Primary: 82C44, Secondery: 82C31, 60H10, 60F15, 60K35  相似文献   
992.
Two complexes that contain the racemic or enantiomerically pure (S) form of the 3,3'-di-tert-butyl-5,5',6,6'-tetramethyl-1,1'-biphenyl-2,2'-diolate (Biphen(2-)) ligand, W(NAr)(CHCMe(2)Ph)(Biphen) (2a) and W(NAr')(CHCMe(2)Ph)(Biphen) (2b) (Ar = 2,6-i-Pr(2)C(6)H(3); Ar' = 2,6-Me(2)C(6)H(3)), were prepared and shown to be viable catalysts for several representative ring-closing reactions to give products in good yields in most cases and high % ee in asymmetric reactions. Exploration of the reaction between 2a and a stoichiometric amount of one desymmetrization substrate allowed two intermediate tungstacyclobutane complexes to be observed, in addition to the final and quite stable tungstacyclobutane complex formed in a reaction between the ring-closed product and a tungsten methylene complex. Reactions involving (13)C labeled ethylene allowed for the observation of an unsubstituted tungstacyclobutane complex, an ethylene complex, an unsubstituted tungstacyclopentane complex, and a heterochiral dimeric form of a methylene complex. The tungstacyclopentane complex was found to catalyze the dimerization of ethylene to 1-butene slowly.  相似文献   
993.
Sentiment analysis aims to automatically classify the subject’s sentiment (e.g., positive, negative, or neutral) towards a particular aspect such as a topic, product, movie, news, etc. Deep learning has recently emerged as a powerful machine learning technique to tackle the growing demand for accurate sentiment analysis. However, the majority of research efforts are devoted to English-language only, while information of great importance is also available in other languages. This paper presents a novel, context-aware, deep-learning-driven, Persian sentiment analysis approach. Specifically, the proposed deep-learning-driven automated feature-engineering approach classifies Persian movie reviews as having positive or negative sentiments. Two deep learning algorithms, convolutional neural networks (CNN) and long-short-term memory (LSTM), are applied and compared with our previously proposed manual-feature-engineering-driven, SVM-based approach. Simulation results demonstrate that LSTM obtained a better performance as compared to multilayer perceptron (MLP), autoencoder, support vector machine (SVM), logistic regression and CNN algorithms.  相似文献   
994.
The present work focuses on spectral analysis of the streamwise velocity fluctuations obtained, utilizing the Cottbus Large Pipe (CoLaPipe) test facility for R+ ≤ 3500, where R+ is the Reynolds number based on the wall friction velocity, uτ, and the pipe radius, R. Measurements of the streamwise spectra have been conducted using a single hot-wire probe. Few runs have been also performed using Particle Image Velocimetry (PIV) as a structure visualization evidence and for spatial correlation purposes. The spectral analysis is being carried out to reveal few insights into pipe flow structure, allowing to follow the foot prints of such structures as well as providing estimates of their energy contents. The cumulative energy is examined as a function of the streamwise wavelength, describing the most energetic motions found in spectral data at various wall normal locations. For the current Reynolds number range, the Very Large Scale Motions (VLSM) and the Large Scale Motions (LSM) were evident as localized peaks in pre-multiplied spectra, having mean wavelengths approximately of 12R, and 3R, respectively. (© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)  相似文献   
995.
996.
Principal mechanical and chemical processes contributing to the observed spontaneous switching from net decrease in permeability to net increase in a fracture in carbonate are examined. The evolution of permeability, and related fracture aperture, is represented through a lumped parameter model. The significant processes of pressure solution beneath bridging asperities, transport of dissolved mass to the fracture void, and subsequent precipitation or dissolution within the fracture void enable the principal characteristics of observed behavior to be followed. The evolution of dissolved mass concentration in the pore fluid is followed for arbitrary applied stress, temperature, and pH conditions, with appropriate feedback to the evolution of fracture permeability. Comparisons with experimental measurements in limestone (Polak et al., 2004, Water Resour. Res. Vol. 40, W03502, doi: 10.1029/2003GL017575) show satisfactory agreement for the evolution of fracture aperture and to a lesser degree in calcium concentrations in the effluent pore fluid. Importantly, the spontaneous switching in permeability change, from aperture reducing to aperture increasing, with no change in environmental conditions, is replicated without the need for an ad hoc trigger. Although this switch is accurately replicated, the lumped parameter model is incapable of replicating the rapid observed growth in permeability that directly follows. This inability results from the assumed form of the lumped asperity model, that is incapable of representing the spatially distributed change in aperture that is seen to occur within the fracture. Despite this inconsistency, the model is shown capable of representing the principal behaviors evident in the response.  相似文献   
997.
Journal of Thermal Analysis and Calorimetry - Increasing the temperature of photovoltaic (PV) cells decreases their electricity generation. The use of phase change materials (PCMs) is one of the...  相似文献   
998.
Journal of Thermal Analysis and Calorimetry - The convective heat transfer coefficient (CHTC) of a fluid is one of the most effective factors on the performance of a fluid in heat transfer...  相似文献   
999.
Journal of Thermal Analysis and Calorimetry - In this study, nonlinear transient thermo-elastic analysis for a thick hollow 1D-FGM (functionally graded material) axisymmetric cylinder with finite...  相似文献   
1000.
The impact of a small amount of polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene (SEBS) on the thermomechanical and electrical properties of blends comprising low-density polyethylene (LDPE) and isotactic polypropylene (PP) is investigated. SEBS is found to assemble at the PP:LDPE interface as well as within isolated PP domains. The addition of 10 wt% SEBS significantly increases the storage modulus between the melting temperatures of the two polyolefins, 110 and 160°C, and results in improved resistance to creep during both tensile deformation as well as compression. Furthermore, the ternary blends display a very low direct-current (DC) conductivity as low as 3.4 × 10−15 S m−1 at 70°C and 30 kV mm−1, which is considerably lower than values measured for neat LDPE. The here presented type of ternary blend shows potential as an insulation material for high-voltage direct current power cables.  相似文献   
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