Studies are carried out on the microstructure and micro-hardness distribution of structural steel 30HN3А samples hardened by laser quenching by means of continuous radiation from a multi-channel 48 rays CO 2 laser system CLT-Yu-5. To provide the formation of a uniform structure, hardness and depth distribution in the hardened material layer a laser emitter was used with four plug-in radiating tubes arranged one into another in an octahedral configuration (patent RF № 2580350). An important role of a high uniformity of the integral heat input across the hardening zone width on the uniformity of properties of the hardened layer is demonstrated. It was found that in the hardened area a finely dispersed martensite structure was formed. The carbides contained in the initial structure of sorbite dissolve not completely during laser hardening. They are characterized by a globular form and size of 0.2…0.3 µm. The microhardness of steel in the hardened area was about 6800 MPa. The thickness variation of the hardened layer, which is characterized by the ratio between minimal, h min , and maximal, h max , depths, is equal to 0.76 at h max = 1050 µm. A reduction in microhardness in a tempering zone formed between two successive hardened bands down to the values of 5500…6000 MPa was found. The width of this tempering zone is about 1.8 mm. The decrease of microhardness in this zone is due to a dissociation of the martensite and formation of tempering troostite structure. Lamellar carbides are formed during this process. Steel in the laser hardened area has a favorable structure in terms of the strength and durability. Thus, hardening of steel by means of multi-channel CO 2 laser systems provides wide opportunities in improving of material properties and is recommended for hardening of expensive machine parts increasing their service lifetime.Keywords: multi-channel СО 2 laser, laser hardening, structural steel. Упрочнение конструкционной стали с помощью многоканального СО 2 лазераЮгов В.И. Проведены исследования микроструктуры и распределения микротвердости образцов конструкционной стали марки 30ХН3А, упрочнённых лазерной закалкой с помощью непрерывного излучения многоканального (48 лучей) СО 2 -лазера на комплексе модели ЦЛТ-Ю-5. Для обеспечения равномерной структуры, твердости и глубины упроч-ненного слоя материала использовали лазерный излучатель с излучающими трубками, скомпонованными в виде пакета, состоящего из вложенных один внутри другого четырех восьмигранников (Patent RF № 2580350). Показа-на роль высокой степени однородности интегрального тепловложения по ширине полосы упрочнения на однород-ность свойств упрочненного слоя. Установлено, что в упрочненной зоне формируется структура мартенсит с тонким строением. Карбиды, входящие в состав исходной структуры сорбита, при лазерной закалке растворяются не пол-ностью. Они имеют глобулярную форму и размер 0,2…0,3 мкм. Микротвердость стали в упрочненной зоне около 6800 МПа. Равномерность глубины упрочненного слоя, которая характеризуется отношением минимальной глуби-ны упро...
Ternary alloy CdSSe nanowires and nanoribbons were successfully grown through a one-step thermal evaporation route using Au as a catalyst. The nanostructures obtained are uniform in diameter, and have smooth surfaces. High-resolution transmission electron microscopy, energy dispersive x-ray spectra and x-ray diffraction showed that both the nanowires and the nanoribbons have high-quality single-crystalline nature, and their compositions can be determined as CdS 0.6 Se 0.4 and CdS 0.3 Se 0.7 , respectively. The mechanisms of formation of these two different nanostructures were discussed. The photoluminescence measurements showed very strong band-edge emission for both samples, which further demonstrates the single-crystal nature of the as-obtained CdSSe alloys. This finding may be extended for fabricating other composition-tunable 1D ternary alloy nanostructures.
We describe and analyze a simple and effective two-step online boosting algorithm that allows us to utilize highly effective gradient descent-based methods developed for online SVM training without the need to fine-tune the kernel parameters, and we show its efficiency by several experiments. Our method is similar to AdaBoost in that it trains additional classifiers according to the weights provided by previously trained classifiers, but unlike AdaBoost, we utilize hinge-loss rather than exponential loss and modify algorithm for the online setting, allowing for varying number of classifiers. We show that our theoretical convergence bounds are similar to those of earlier algorithms, while allowing for greater flexibility. Our approach may also easily incorporate additional nonlinearity in form of Mercer kernels, although our experiments show that this is not necessary for most situations. The pre-training of the additional classifiers in our algorithms allows for greater accuracy while reducing the times associated with usual kernel-based approaches. We compare our algorithm to other online training algorithms, and we show, that for most cases with unknown kernel parameters, our algorithm outperforms other algorithms both in runtime and convergence speed.
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