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Lithium aluminosilicate glass-ceramics are well known for good transparency, high fracture toughness, low thermal expansion, and good ion exchange ability. In this study, new transparent Li2O-Al2O3-SiO2 (LAS) glass-ceramics with petalite and β-spodumene solid solution as the major crystalline phases were invented for favorable mechanical properties and potential for application in the hollowware, tableware, container, and plate glass industries. Crystal phases are mainly influenced by the ratio of Al2O3 to SiO2 concentrations. The concentration of SiO2 required to form specific crystalline phases in the glass-ceramics is higher than that inferred from the ternary phase diagram. Al2O3 content is required to be sufficiently high for the formation of crystals, instead of balancing excess amounts of Li2O in the glass. The average transmittances of 2.0 ± 0.1 mm thickness samples in visible light regions (400–700 nm) can reach more than 80% with crystal sizes of 20–40 nm. Transmittance is significantly decreased for heat treatments around 710°C, due to the high growth rate of β-spodumene solid solution crystals. Vickers hardness, indentation toughness, and crack probabilities of transparent LAS glass-ceramics are significantly improved compared with standard soda lime silicate glass, due to the crack bridging and deflection of crystal grains.  相似文献   
3.
A strategy for creating potent and pan-genotypic stimulator of interferon genes (STING) agonists is described. Locking a bioactive U-shaped conformation of cyclic dinucleotides by introducing a transannular macrocyclic bridge between the nucleic acid bases leads to a topologically novel macrocycle-bridged STING agonist (MBSA). In addition to substantially enhanced potency, the newly designed MBSAs, exemplified by clinical candidate E7766 , exhibit broad pan-genotypic activity in all major human STING variants. E7766 is shown to have potent antitumor activity with long lasting immune memory response in a mouse liver metastatic tumor model. Two complementary stereoselective synthetic routes to E7766 are also described.  相似文献   
4.
This article investigates the effect of inlet shape, entrance length, and turbulence promoters on mass transfer by using 3D-printed electrolyzers. Our results show that the inlet design can promote turbulence and lead to an earlier transition to turbulent flow. The Reynolds number at which the transition occurs can be predicted by the ratio of the cross-sectional area of the inlet to the cross-sectional area of the electrolyzer channel. A longer entrance length results in more laminar behavior and a later transition to turbulent flow. With an entrance length of 550 mm, the inlet design did no longer affect the mass transfer performance significantly. The addition of gyroid type turbulence promoters resulted in a factor of 2 to 4 increase in mass transfer depending on inlet design, entrance length, and the type of promoter. From one configuration to another, there was a minimal variation in pressure drop (<1600 Pa).  相似文献   
5.
Herein, we describe a reduced‐scale test (“Cube” test), measuring the fire performance of specimens including a fire barrier (FB) and a flammable core material, which acts as the main fuel load. The specimen is intended to reproduce a cross‐section of a composite product where heat/mass transfer occurs primarily in a direction perpendicular to the FB. The Cube test procedure and benefits are discussed in this work by adopting residential upholstery furniture as an exemplary study. One flexible polyurethane foam, one polypropylene cover fabric, and 10 commercially available FBs were selected. They were used to compare the fire performance of FBs, measured in terms of peak of heat release rate, in the ASTM E1474‐14 standard test and the newly developed Cube test. Edge effects severely affected the performance of FBs in the ASTM E1474‐14 standard test but not in the Cube test. Furthermore, appropriate test conditions were determined in the Cube test to measure the so‐called “wetting point,” that is, the time and value of heat release rate measured when flammable liquid products were first observed on the bottom of the specimen. The relevance of the “wetting point” in terms of full‐scale fire performance and failure mechanism of FBs is discussed.  相似文献   
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A series of bio-rubber (BR) tougheners for thermosetting epoxy resins was prepared by grafting renewable fatty acids with different chain lengths onto epoxidized soybean oil at varying molar ratios. BR-toughened samples were prepared by blending BRs with diglycidyl ether of bisphenol A resins, Epon 828 and Epon 1001F, at different weight fractions and stoichiometrically cured using an amine curing agent, 4, 4′-methylene biscyclohexanamine (PACM). Fracture toughness properties of the unmodified and BR toughened polymer samples—including critical strain energy release rate (GIc), and critical stress intensity factor (KIc)—were measured to investigate the toughening effect of prepared BRs. It was found that the degree of phase separation and toughening were more controllable relative to similar polymers cured using the aromatic curing agent Epikure W, and the use of higher molecular epoxy resins produces a synergistic effect increasing the toughness much more than similar polymers made with lower molecular weight epoxy resins. Average BR domain sizes ranging from 200 to 900 nm were observed, and formulations with GIc, values KIc as high as 1.0 kJ/m2 and 1.4 MPa m1/2 were attained respectively for epoxy systems with Tg greater than 130°C.  相似文献   
8.
While the challenges associated with the stability of metal halide perovskites are well known and intensely studied, variability in electronic properties represents an equally significant, yet seldom studied, challenge that could potentially slow or inhibit the commercial viability of these systems. In this work, the contactless characterization technique time-resolved microwave conductivity (TRMC) is used to quantify the variability in electronic properties of the prototypical perovskite, methylammonium lead iodide (MAPbI3) both between different samples, and at different locations within the same sample. Using scanning electron microscopy (SEM) and a quasi-automated image-analysis strategy, it is possible to evaluate the metrics of heterogeneity in surface microstructure and correlate them with the electronic properties as obtained by TRMC. Substantial intra-sample and inter-sample variation is observed in the mobility-yield product in samples prepared following differing protocols, and in samples prepared following identical protocols.  相似文献   
9.
The Gli-B1-encoded γ-gliadins and non-coding γ-gliadin DNA sequences for 15 different alleles of common wheat have been compared using seven tests: electrophoretic mobility (EM) and molecular weight (MW) of the encoded major γ-gliadin, restriction fragment length polymorphism patterns (RFLPs) (three different markers), Gli-B1-γ-gliadin-pseudogene known SNP markers (Single nucleotide polymorphisms) and sequencing the pseudogene GAG56B. It was discovered that encoded γ-gliadins, with contrasting EM, had similar MWs. However, seven allelic variants (designated from I to VII) differed among them in the other six tests: I (alleles Gli-B1i, k, m, o), II (Gli-B1n, q, s), III (Gli-B1b), IV (Gli-B1e, f, g), V (Gli-B1h), VI (Gli-B1d) and VII (Gli-B1a). Allele Gli-B1c (variant VIII) was identical to the alleles from group IV in four of the tests. Some tests might show a fine difference between alleles belonging to the same variant. Our results attest in favor of the independent origin of at least seven variants at the Gli-B1 locus that might originate from deeply diverged genotypes of the donor(s) of the B genome in hexaploid wheat and therefore might be called “heteroallelic”. The donor’s particularities at the Gli-B1 locus might be conserved since that time and decisively contribute to the current high genetic diversity of common wheat.  相似文献   
10.
Machine learning (ML) models are valuable research tools for making accurate predictions. However, ML models often unreliably extrapolate outside their training data. The multiparameter delta method quantifies uncertainty for ML models (and generally for other nonlinear models) with parameters trained by least squares regression. The uncertainty measure requires the gradient of the model prediction and the Hessian of the loss function, both with respect to model parameters. Both the gradient and Hessian can be readily obtained from most ML software frameworks by automatic differentiation. We show examples of the uncertainty method in applications of molecular simulations and neural networks. We further show that the uncertainty measure is larger for input space regions that are not part of the training data. Therefore, this method can be used to identify extrapolation and to aid in selecting training data or assessing model reliability.  相似文献   
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