全文获取类型
收费全文 | 57739篇 |
免费 | 9487篇 |
国内免费 | 5980篇 |
专业分类
电工技术 | 3467篇 |
技术理论 | 7篇 |
综合类 | 5406篇 |
化学工业 | 10892篇 |
金属工艺 | 1470篇 |
机械仪表 | 2286篇 |
建筑科学 | 3034篇 |
矿业工程 | 511篇 |
能源动力 | 4963篇 |
轻工业 | 1498篇 |
水利工程 | 781篇 |
石油天然气 | 1173篇 |
武器工业 | 312篇 |
无线电 | 5254篇 |
一般工业技术 | 5585篇 |
冶金工业 | 3137篇 |
原子能技术 | 805篇 |
自动化技术 | 22625篇 |
出版年
2024年 | 891篇 |
2023年 | 2711篇 |
2022年 | 4192篇 |
2021年 | 4179篇 |
2020年 | 3671篇 |
2019年 | 2753篇 |
2018年 | 2178篇 |
2017年 | 2124篇 |
2016年 | 2247篇 |
2015年 | 2272篇 |
2014年 | 3230篇 |
2013年 | 3487篇 |
2012年 | 3333篇 |
2011年 | 3893篇 |
2010年 | 3017篇 |
2009年 | 3046篇 |
2008年 | 2989篇 |
2007年 | 3141篇 |
2006年 | 2838篇 |
2005年 | 2667篇 |
2004年 | 2111篇 |
2003年 | 1941篇 |
2002年 | 1655篇 |
2001年 | 1291篇 |
2000年 | 1124篇 |
1999年 | 888篇 |
1998年 | 849篇 |
1997年 | 718篇 |
1996年 | 613篇 |
1995年 | 523篇 |
1994年 | 394篇 |
1993年 | 365篇 |
1992年 | 337篇 |
1991年 | 210篇 |
1990年 | 204篇 |
1989年 | 181篇 |
1988年 | 129篇 |
1987年 | 100篇 |
1986年 | 105篇 |
1985年 | 55篇 |
1984年 | 72篇 |
1983年 | 48篇 |
1982年 | 31篇 |
1965年 | 26篇 |
1964年 | 27篇 |
1963年 | 23篇 |
1959年 | 30篇 |
1957年 | 23篇 |
1955年 | 23篇 |
1951年 | 29篇 |
排序方式: 共有10000条查询结果,搜索用时 78 毫秒
1.
2.
《International Journal of Hydrogen Energy》2022,47(75):32031-32038
The activity of catalysts with various sizes was compared in a fixed-bed Fischer–Tropsch reactor under similar operating conditions by determining the deactivation model. Catalyst size had no impact on the type of deactivation model. The smaller catalyst showed a smaller deactivation constant of catalyst (kd) and a lower deactivation rate in the initial stage. The decline in the activities of the catalyst with a mesh size of 40 was lower than the other catalysts, suggesting its higher long-term stability (ass). Larger catalyst sizes led to the fouling of carbon and heavy hydrocarbons, decreasing the specific surface of the catalyst, thus increasing the pore diffusion resistance and further decrementing the catalyst activities. 相似文献
3.
《International Journal of Hydrogen Energy》2022,47(80):33955-33965
We report the study of conductive polyaniline (PANI) chain embedded Ti-MOF functionalized with CoS as a cocatalyst for hydrogen evolution reaction (HER) application. The post synthetically modified hybrid photocatalyst PANI/Ti-MOF/CoS greatly influences the redox and e? ? h+ separation process and exhibits an impressive rate of HER (~1322 μmol h?1g?1), suppressing the pristine Ti-MOF (~62 μmol h?1g?1) with apparent quantum yield (AQY) of ~3.2 and transient current response of ~46.4 μA cm?2. In this system, Ti-MOF provides the circulation of Ti3+ and Ti4+ to the reaction of photocatalytic H2 generation, where the additional PANI and CoS amended the performance of H2 production through electron enrichment and thereby improving the stability and integrity of Ti-MOF. The Electrochemical studies demonstrated increased photocurrent by interweaving Ti-MOF crystal with PANI through cation-π interaction thereby enhancing interface connection and then promoting electron transfers. The charge dynamics revealed the initial charge transfer from photoexcited PANI to encapsulated MOF framework to boost the photocatalytic performance of the system. Further, the electron movement at the Ti-MOF/CoS interface is investigated through work function and electrochemical potential of electrons (Fermi level). DFT results demonstrate the importance of CoS in improving the photocatalytic performance of hybrid Ti-MOF catalyst, which leads to superior catalytic behaviour. These results establish that the encapsulation of catalytic active sites inside MOFs with desirable energy band gaps would be an ideal choice for the production of solar fuels. 相似文献
4.
Machine learning algorithms have been widely used in mine fault diagnosis. The correct selection of the suitable algorithms is the key factor that affects the fault diagnosis. However, the impact of machine learning algorithms on the prediction performance of mine fault diagnosis models has not been fully evaluated. In this study, the windage alteration faults (WAFs) diagnosis models, which are based on K-nearest neighbor algorithm (KNN), multi-layer perceptron (MLP), support vector machine (SVM), and decision tree (DT), are constructed. Furthermore, the applicability of these four algorithms in the WAFs diagnosis is explored by a T-type ventilation network simulation experiment and the field empirical application research of Jinchuan No. 2 mine. The accuracy of the fault location diagnosis for the four models in both networks was 100%. In the simulation experiment, the mean absolute percentage error (MAPE) between the predicted values and the real values of the fault volume of the four models was 0.59%, 97.26%, 123.61%, and 8.78%, respectively. The MAPE for the field empirical application was 3.94%, 52.40%, 25.25%, and 7.15%, respectively. The results of the comprehensive evaluation of the fault location and fault volume diagnosis tests showed that the KNN model is the most suitable algorithm for the WAFs diagnosis, whereas the prediction performance of the DT model was the second-best. This study realizes the intelligent diagnosis of WAFs, and provides technical support for the realization of intelligent ventilation. 相似文献
5.
本文主要总结了新冠疫情期间作者的电磁场理论课程在线教学经验。对比分析了录播和直播的优缺点后,选择录播教学方式。基于超星网络教学平台,展示了录播网络教学的具体措施,包括网上答疑和学习效果检查以及在线批改作业等。给出了网络教学可以为线下教学继续使用的方法和手段,为疫情结束后的正常教学提供了新的网络教学补充措施。 相似文献
6.
边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明:和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。 相似文献
7.
In the Internet of Things (IoT), a huge amount of valuable data is generated by various IoT applications. As the IoT technologies become more complex, the attack methods are more diversified and can cause serious damages. Thus, establishing a secure IoT network based on user trust evaluation to defend against security threats and ensure the reliability of data source of collected data have become urgent issues, in this paper, a Data Fusion and transfer learning empowered granular Trust Evaluation mechanism (DFTE) is proposed to address the above challenges. Specifically, to meet the granularity demands of trust evaluation, time–space empowered fine/coarse grained trust evaluation models are built utilizing deep transfer learning algorithms based on data fusion. Moreover, to prevent privacy leakage and task sabotage, a dynamic reward and punishment mechanism is developed to encourage honest users by dynamically adjusting the scale of reward or punishment and accurately evaluating users’ trusts. The extensive experiments show that: (i) the proposed DFTE achieves high accuracy of trust evaluation under different granular demands through efficient data fusion; (ii) DFTE performs excellently in participation rate and data reliability. 相似文献
8.
Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (Tg) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (nd) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high nd (1.7 or more) and low Tg (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses. 相似文献
9.
《Ceramics International》2022,48(9):12281-12290
Following the rapid growth of lightning technology, the development of red-emitting phosphors is effective for improving color temperature and color rendering index for w-LEDs devices. Herein, a single phased garnet phosphor with cation and polyhedron substitution modification was firstly prepared. For Mg3Gd2Ge3O12: Bi3+, Eu3+, the intensity has been remarkably improved by about 16% compared to the one without Bi3+ sensitization. The energy transfer mechanism is identified in this work. Based on cation and polyhedron substitution strategies, novel phosphors with different compositions were obtained and further modified the PL properties. With Lu3+ substitution, the bond lengths between Bi3+ ion and anion ligands are decreased and the site symmetry has been strengthened, which leads to a 21 nm blue shift when Lu3+ totally replaced Gd3+ ions. In addition, Lu3+ and [SiO4] substitution strategies both effectively increased symmetric rigid structure, which leads to a significant improvement in thermal stability, indicating the samples own great potential in optical applications This work provides a new insight to synthesis red-emitting phosphors for warm white-LEDs. 相似文献
10.
In this paper, we strive to propose a self-interpretable framework, termed PrimitiveTree, that incorporates deep visual primitives condensed from deep features with a conventional decision tree, bridging the gap between deep features extracted from deep neural networks (DNNs) and trees’ transparent decision-making processes. Specifically, we utilize a codebook, which embeds the continuous deep features into a finite discrete space (deep visual primitives) to distill the most common semantic information. The decision tree adopts the spatial location information and the mapped primitives to present the decision-making process of the deep features in a tree hierarchy. Moreover, the trained interpretable PrimitiveTree can inversely explain the constituents of the deep features, highlighting the most critical and semantic-rich image patches attributing to the final predictions of the given DNN. Extensive experiments and visualization results validate the effectiveness and interpretability of our method. 相似文献