Toward design of synergistically active carbon-based catalysts for electrocatalytic hydrogen evolution

Replacement of precious Pt catalyst with cost-effective alternatives would be significantly beneficial for hydrogen production via electrocatalytic hydrogen evolution reaction (HER). All candidates thus far are exclusively metallic catalysts, which suffer inherent corrosion and oxidation susceptibility during acidic proton-exchange membrane electrolysis. Herein, based on theoretical predictions, we designed and synthesized nitrogen (N) and phosphorus (P) dual-doped graphene as a nonmetallic electrocatalyst for sustainable and efficient hydrogen production. The N and P heteroatoms could coactivate the adjacent C atom in the graphene matrix by affecting its valence orbital energy levels to induce a synergistically enhanced reactivity toward HER. As a result, the dual-doped graphene showed higher electrocatalytic HER activity than single-doped ones and comparable performance to some of the traditional metallic catalysts.

Dependence of deformation behavior on grain size and strain rate in an ultrahigh strength-ductile Mn-based TRIP alloy

A novel ultra-high strength TRIP (transformation induced plasticity) steel, with ~1.5. GPa strength and good ductility of ~26% has been produced. The microstructure consists of ultrafine ferrite, and a large volume fraction of austenite. The flow stress was significantly increased by a reduction in the grain size, but the effect of strain rate on the flow stress was negligible. The formation of stress induced martensite was found to increase linearly with strain, and a reduction in the grain size correlated with an increase in the stress required to form the martensite.

Subnanometer molybdenum sulfide on carbon nanotubes as a highly active and stable electrocatalyst for hydrogen evolution reaction

Electrochemically splitting water for hydrogen evolution reaction (HER) has been viewed as a promising approach to produce renewable and clean hydrogen energy. However, searching for cheap and efficient HER electrocatalysts to replace the currently used Pt-based catalysts remains an urgent task. Herein, we develop a one-step carbon nanotube (CNT) assisted synthesis strategy with CNTs' strong adsorbability to mediate the growth of subnanometer-sized MoS(x) on CNTs. The subnanometer MoS(x)-CNT hybrids achieve a low overpotential of 106 mV at 10 mA cm(-2), a small Tafel slope of 37 mV per decade, and an unprecedentedly high turnover frequency value of 18.84 s(-1) at η = 200 mV among all reported non-Pt catalysts in acidic conditions. The superior performance of the hybrid catalysts benefits from the presence of a higher number of active sites and the abundant exposure of unsaturated S atoms rooted in the subnanometer structure, demonstrating a new class of subnanometer-scale catalysts.

Re-examination of the effect of NbC precipitation on shape memory in Fe-Mn-Si-based alloys

Current literature pertaining to the shape memory effect in the Fe–Mn–Si-based system is critically discussed. It is argued that the
enhanced shape memory previously attributed to NbC precipitation is mainly due to the associated thermo-mechanical treatments.
It is concluded that the thermo-mechanical processing of the alloy is the dominant factor that determines the shape memory effect in
this alloy system.

New effective catalysts based on mesoporous nanofibrous carbon for selective oxidation of hydrogen sulfide

The systems based on granular mesoporous nanofibrous carbonaceous (NFC) materials synthesized by decomposition of hydrocarbons over nickel- containing catalysts are promising catalysts for selective oxidation of hydrogen sulfide. Sample series of nanofibrous carbon with three main types of their fiber structures and different contents of metal catalysts inherited from the catalysts for their synthesis were studied in this reaction. The correlation between NFC structure and its activity and selectivity in hydrogen sulfide oxidation was determined. The metal inherited from the initial catalysts for the synthesis of NFC influences the activity and selectivity of the resulting carbon catalysts. A particular influence is observed in the case of the catalyst withdrawn from the synthesis reactor at the stage of stationary operation of the metal catalyst (low specific carbon yields per unit weight of the catalyst). The presence of the metal phase results in an increase in the carbon catalyst activity and in a decrease in the selectivity to sulfur. NFC samples with the highest activity and selectivity are nanotubes and those with graphite planes perpendicular to the axis of the fibers. Carbon nanotubes have high selectivity, while samples obtained on copper–nickel catalysts also possess high activity. The promising NFC catalysts provide high conversion and selectivity (almost independent of the molar oxygen/hydrogen sulfide ratio) when a large excess of oxygen is contained in the reaction mixture.

Effect of second-phase particles on shape memory in Fe-Mn-Si-based alloys

The shape memory behaviour of two Fe–Mn–Si-based alloys has been investigated. One alloy was a reference alloy, and the other alloy was
similar in composition except that it contained 0.55 wt% Ti. Following solution treatment and quenching, strip samples were subjected to three types
of treatments; isothermal holding, cold rolling followed by isothermal holding, and hot rolling followed by isothermal holding. These treatments
resulted in the formation of intermetallic precipitates in the Ti-containing alloy, while the reference alloy remained precipitate-free. In comparing
the shape memory of the reference and the particle-containing alloy after identical heat treatments, it was found that the formation of precipitates
had a beneficial effect on the shape memory in all cases. In general, the larger precipitates caused a larger increase in the shape memory. The effect
of particle size on shape memory has been analysed using the current data and published results for a range of precipitate types.

Austenite stability in Fe-Mn-Si-based shape memory alloys

The stability of austenite in a number of Fe–Mn–Si-based shape memory alloys has been investigated. It was found that a grain boundary precipitate of BCC structure is formed over a wide range of alloy compositions and heat treatment temperatures. This grain boundary phase has been identified as the chi (χ) phase. Although up to 3 vol.% of the grain boundary precipitate was generated by isothermal aging in the range 500–800 °C, it was found not to markedly affect the mechanical properties or the shape memory effect. Nano-indentation indicated that the hardness and strength of the parent and precipitate phase are very similar, as are their compositions.

Oxygen reduction reaction activity of La-based perovskite oxides in alkaline medium : a thin-film rotating ring-disk electrode study

In this work, LaMO₃ and LaNi_0.5M_0.5O₃ (M = Ni, Co, Fe, Mn and Cr) perovskite oxide electrocatalysts were synthesized by a combined ethylenediaminetetraacetic acid-citrate complexation technique and subsequent calcinations at 1000 °C in air. Their powder X-ray diffraction patterns demonstrate the formation of a specific crystalline structure for each composition. The catalytic property of these materials toward the oxygen reduction reaction (ORR) was studied in alkaline potassium hydroxide solution using the rotating disk and rotating ring-disk electrode techniques. Carbon is considered to be a crucial additive component because its addition into perovskite oxide leads to optimized ORR current density. For LaMO₃ (M = Ni, Co, Fe, Mn and Cr)), in terms of the ORR current densities, the performance is enhanced in the order of LaCrO₃, LaFeO₃, LaNiO₃, LaMnO₃, and LaCoO3. For LaNi_0.5M_0.5O₃, the ORR current performance is enhanced in the order of LaNi_0.5Fe_0.5O₃, LaNi_0.5Co_0.5O₃, LaNi_0.5Cr_0.5O₃, and LaNi_0.5Mn_0.5O₃. Overall, LaCoO₃ demonstrates the best performance. Most notably, substituting half of the nickel with cobalt, iron, manganese, or chromium translates the ORR to a more positive onset potential, suggesting the beneficial catalytic effect of two transition metal cations with Mn as the most promising candidate. Koutecky–Levich analysis on the ORR current densities of all compositions indicates that the four-electron pathway is favored on these oxides, which are consistent with hydroperoxide ion formation of <2%.

Analysis of work hardening and recrystallization during the hot working of steel using a statistically based internal variable model

A mathematical model has been developed which describes the hot deformation and recrystallization behavior of austenite using a single internal variable: dislocation density. The dislocation density is incorporated into equations describing the rate of recovery and recrystallization. In each case no distinction is made between static and dynamic events, and the model is able to simulate multideformation processes. The model is statistically based and tracks individual populations of the dislocation density during the work-hardening and softening phases. After tuning using available data the model gave an accurate prediction of the stress–strain behavior and the static recrystallization kinetics for C–Mn steels. The model correctly predicted the sensitivity of the post deformation recrystallization behavior to process variables such as strain, strain rate and temperature, even though data for this were not explicitly incorporated in the tuning data set. In particular, the post dynamic recrystallization (generally termed metadynamic recrystallization) was shown to be largely independent of strain and temperature, but a strong function of strain rate, as observed in published experimental work.

Effect of alloying additions on the SFE, Neél temperature and shape memory effect in Fe–Mn–Si-based alloys

A range of Fe–Mn–Si-based shape memory alloys has been investigated to examine the interplay of composition, stacking fault probability (SFP) and Neél temperature on the shape memory effect (SME). It has been found that the SFP (inversely proportional to stacking fault energy) showed little correlation to the SME for the range of alloy compositions examined. Further, the Neél temperature was not found to exhibit a significant effect on the SME. The addition of interstitial elements, however, was found to markedly decrease the SME.

Thermo-mechanical processing and the shape memory effect in an Fe–Mn–Si-based shape memory alloy

The effect of cold rolling and annealing on the shape memory effect (SME) in an Fe–Mn–Si-based alloy has been studied. It has been found
that the SME in these alloys can be significantly increased by the appropriate thermo-mechanical processing (TMP). The optimum conditions
were found to be 15% cold rolling followed by annealing at 800 ◦C for 15 min. This produced a total strain recovery of 4.5%. TEM showed that
this processing schedule produces a microstructure of evenly spaced, and well defined stacking faults throughout the parent phase. It is shown for
the first time that samples processed in this way produce a larger fraction of martensite compared to samples in the as-austenitized condition. It
is concluded that the stacking faults induced by TMP act as nucleation sites for martensite formation during deformation. The SME is improved
primarily as a result of the increased amount of martensite that is formed in this condition.

Optimization of alloy design and hot rolling conditions for shape memory in Fe–Mn–Si-based alloys

The effect of composition and hot rolling conditions on the shape memory effect (SME) in the Fe–Mn–Si-based system has been studied to obtain improved shape memory without the need to rely on “training”. It has been found that the texture is not markedly affected by rolling conditions, and texture is therefore not a major factor in explaining variations in SME with processing conditions. Decreasing the pre-deformation temperature to below the Ms was found to have a beneficial effect on shape memory. It was found that the best SME was achieved in an alloy that had Ms just above room temperature, and had been processed by hot rolling followed by recovery annealing. Alloys of different compositions exhibited different optimum rolling temperatures for maximum shape memory performance.

Atom probe tomography of solute distributions in mg-based alloys

Atom probe tomography (APT) has been carried out on three magnesium-based alloys: M1 (Mg-1 wt pct Mn), AZ31(Mg-3 pct Al-1 pct Zn), and ME10 (Mg-1 pct Mn- 0.4 pct misch metal). The aims of this experiment were to measure the composition of the matrix and to investigate solute clustering in the matrix of the three different alloys. For AZ31, the matrix composition was variable but close to the bulk composition. For ME10 and M1, the matrix was depleted in alloying additions, with the remainder residing in precipitates. Most alloying additions were found to exhibit clustering to some extent, with misch metal having the strongest partitioning behavior to clusters. Solute clusters did not appear to affect mechanical twinning. It has been proposed that the clustering behavior of misch metal contributes to its ability to modify the recrystallization texture.