A CO2-stable reduction-tolerant Nd-containing dual phase membrane for oxyfuel CO2 capture

We report a novel CO2-stable reduction-tolerant dual-phase oxygen transport membrane 40 wt% Nd0.6Sr0.4FeO3-delta-60 wt% Ce0.9Nd0.1O2-delta (40NSFO-60CNO), which was successfully developed by a facile one-pot EDTA-citric sol-gel method. The microstructure of the crystalline 40NSFO-60CNO phase was investigated by combined in situ X-ray diffraction (XRD), scanning electron microscopy (SEM), back scattered SEM (BSEM), and energy dispersive X-ray spectroscopy (EDXS) analyses. Oxygen permeation and long-time stability under CO2 and CH4 atmospheres were investigated. A stable oxygen flux of 0.21 cm(3) min(-1) cm(-2) at 950 degrees C with undiluted CO2 as sweep gas is found which is increased to 0.48 cm(3) min(-1) cm(-2) if the air side is coated with a porous La0.6Sr0.4CoO3-delta (LSC) layer. All the experimental results demonstrate that the 40NSFO-60CNO not only shows good reversibility of the oxygen permeation fluxes upon temperature cycling, but also good phase stability in a CO2 atmosphere and under the harsh conditions of partial oxidation of methane to synthesis gas up to 950 degrees C.Sino-German Centre for Science Promotion/GZ 676, GZ911National Science Fund for Distinguished Young Scholars of China/2122562

A novel CO2-stable dual phase membrane with high oxygen permeability

By cobalt-doping of the mixed conducting phase PSFC, a good combination of high CO2 stability and high oxygen permeability is obtained for the 60 wt% Ce0.9Pr0.1O2-delta d -40 wt% Pr0.6Sr0.4Fe0.5Co0.5O3-delta (CP-PSFC) dual phase membrane, which suggests that CP-PSFC is a promising membrane for industrial applications in the oxyfuel process for CO2 capture

What indeed can GPT models do in chemistry? A comprehensive benchmark on eight tasks

Large Language Models (LLMs) with strong abilities in natural language processing tasks have emerged and have been rapidly applied in various kinds of areas such as science, finance and software engineering. However, the capability of LLMs to advance the field of chemistry remains unclear. In this paper,we establish a comprehensive benchmark containing 8 practical chemistry tasks, including 1) name prediction, 2) property prediction, 3) yield prediction, 4) reaction prediction, 5) retrosynthesis (prediction of reactants from products), 6)text-based molecule design, 7) molecule captioning, and 8) reagent selection. Our analysis draws on widely recognized datasets including BBBP, Tox21, PubChem, USPTO, and ChEBI, facilitating a broad exploration of the capacities of LLMs within the context of practical chemistry. Three GPT models (GPT-4, GPT-3.5,and Davinci-003) are evaluated for each chemistry task in zero-shot and few-shot in-context learning settings with carefully selected demonstration examples and specially crafted prompts. The key results of our investigation are 1) GPT-4 outperforms the other two models among the three evaluated; 2) GPT models exhibit less competitive performance in tasks demanding precise understanding of molecular SMILES representation, such as reaction prediction and retrosynthesis;3) GPT models demonstrate strong capabilities in text-related explanation tasks such as molecule captioning; and 4) GPT models exhibit comparable or better performance to classical machine learning models when applied to chemical problems that can be transformed into classification or ranking tasks, such as property prediction, and yield prediction

A Review of Spatter in Laser Powder Bed Fusion Additive Manufacturing: In Situ Detection, Generation, Effects, and Countermeasures

Spatter is an inherent, unpreventable, and undesired phenomenon in laser powder bed fusion (L-PBF) additive manufacturing. Spatter behavior has an intrinsic correlation with the forming quality in L-PBF because it leads to metallurgical defects and the degradation of mechanical properties. This impact becomes more severe in the fabrication of large-sized parts during the multi-laser L-PBF process. Therefore, investigations of spatter generation and countermeasures have become more urgent. Although much research has provided insights into the melt pool, microstructure, and mechanical property, reviews of spatter in L-PBF are still limited. This work reviews the literature on the in situ detection, generation, effects, and countermeasures of spatter in L-PBF. It is expected to pave the way towards a novel generation of highly efficient and intelligent L-PBF systems

Effects of extreme drought on plant nutrient uptake and resorption in rhizomatous vs bunch grass dominated grasslands

Both the dominance and the mass ratio hypotheses predict that plant internal nutrient cycling in ecosystems is determined by the dominant species within plant communities. We tested this hypothesis under conditions of extreme drought by assessing plant nutrient (N, P and K) uptake and resorption in response to experimentally imposed precipitation reductions in two semiarid grasslands of northern China. These two communities shared similar environmental conditions, but had different dominant species-one was dominated by a rhizomatous grass (Leymus chinensis) and the other by a bunchgrass (Stipa grandis). Results showed that responses of N to drought differed between the two communities with drought decreasing green leaf N concentration and resorption in the community dominated by the rhizomatous grass, but not in the bunchgrass-dominated community. In contrast, negative effects of drought on green leaf P and K concentrations and their resorption efficiencies were consistent across the two communities. Additionally, in each community, the effects of extreme drought on soil N, P and K supply did not change synchronously with that on green leaf N, P and K concentrations, and senesced leaf N, P and K concentrations showed no response to extreme drought. Consistent with the dominance/mass ratio hypothesis, our findings suggest that differences in dominant species and their growth form (i.e., rhizomatous vs bunch grass) play an important nutrient-specific role in mediating plant internal nutrient cycling across communities within a single region

Analysis of the bullwhip effect in two parallel supply chains with interacting price-sensitive demands

This paper offers insights into how the bullwhip effect in two parallel supply chains with interacting price-sensitive demands is affected in contrast to the situation of a single product in a serial supply chain. In particular, this research studies two parallel supply chains, each consisting of a manufacturer and a retailer, and the external demand for a single product depends on its price and the other\u27s price in a situation in which each price follows a first-order autoregressive process. In this paper, we propose an analytical framework that incorporates two parallel supply chains, and we explore their interactions to determine the bullwhip effect. We identify the conditions under which the bullwhip effect is amplified or lessened with interacting price-sensitive demands relative to the situation without interaction

Multiobjective optimization for multiperiod reverse logistics network design

In recent years, the ever-rising return streams for repair service have forced the electronics manufacturers to expand their reverse logistics capacities. However, most existing papers on the reverse logistics network design neglected the time sensitivity of the return flows. Moreover, most of these investigations were primarily concerned with the single objective problems of either minimizing the total cost or maximizing the profit. In this paper, we propose a biobjective mixed-integer linear programming model for the multiperiod design problem of a reverse logistics network for repair service. A multiperiod setting is taken into account to make the reverse logistics network flexible to accommodate the gradual changes in the capacity of the facilities and the network configuration. To solve the NP-hard problem with biobjective, we develop a hybrid evolutionary algorithm that combines nondominated sorting genetic algorithm II (NSGA-II) with a local search method. We compare the hybrid evolutionary algorithm with NSGA-II and ϵ-constraint method using numerical examples. The comparison results indicate that the hybrid evolutionary algorithm outperforms the NSGA-II in most cases. The ϵ-constraint method performs best for the small instances, but it cannot solve large instances within reasonable time. Finally, an extensive parametric analysis is conducted and several managerial insights are derived

Novel Cobalt-Free, Noble Metal-Free Oxygen-Permeable 40Pr_0.6Sr_0.4FeO₃-delta-60Ce_0.9Pr_0.1O₂-delta, Dual-Phase Membrane

A novel cobalt-free and noble metal-free dual-phase oxygen-transporting membrane with a composition of 40 wt % Pr0.6Sr0.4FeO3-delta-60 wt % Ce0.9Pr0.1O2-delta (40PSFO-60CPO) has been successfully developed via an in situ one-pot one-step glycine-nitrate combustion process. In situ XRD demonstrated that the 40PSFO-60CPO dual-phase membrane shows a good phase stability not only in air but also in SO vol % CO2/50 vol % N2 atmosphere. When using pure He or pure CO2 as sweep gases, at 950 degrees C steady oxygen permeation fluxes of 0.26 cm3 min-1 cm-2 and 0.18 cm3 min-1 cm-2 are obtained through the 40PSFO-60CPO dual-phase membrane. The partial oxidation of methane (POM) to syngas was also successfully investigated in the 40PSFO-60CPO dual-phase membrane reactor. Methane conversion was found to be higher than 99.0% with 97.0% CO selectivity and 4.4 cm3 min-1 cm-2 oxygen permeation flux in steady state at 950 degrees C. Our dual-phase membrane - without any noble metals such as Ag, Pd or easily reducible metals oxides of Co or Ni - exhibits high oxygen permeation fluxes as well as good phase stability at high temperatures. Furthermore, the dual-phase membrane shows a good chemical stability under the harsh conditions of the POM reaction and in a CO2 atmosphere at high temperatures. Accession Number: WOS:00030509260002

Rapid glycine-nitrate combustion synthesis of the CO₂-stable dual phase membrane 40Mn_1.5Co_1.5O_4−δ–60Ce_0.9Pr_0.1O_2−δ for CO₂ capture via an oxy-fuel process

A rapid one-pot combustion synthesis method based on glycine–nitrate, has been applied to prepare a novel oxygen transporting dual phase CO2-stable membrane of the composition 40 wt% Mn1.5Co1.5O4−δ–60 wt% Ce0.9Pr0.1O2−δ (40MCO–60CPO). After sintering at 1300 °C in air for 10 h, the 40MCO–60CPO membranes were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), back scattered SEM (BSEM), and energy dispersive X-ray spectroscopy (EDXS), showing that the 40MCO–60CPO composite represents a micro-scale mixture of mainly the two phases MCO and CPO, but small amounts of MnO2 and (MnCo)(MnCo)2O4−δ were detected in the sintered membranes as well. The oxygen permeation fluxes through the 40MCO–60CPO dual phase membrane were measured at elevated temperatures (900–1000 °C) with one side of the membrane exposed to synthetic air and the other side to a CO2/He sweep gas stream. A stable oxygen permeation flux of 0.48 mL cm−2 min−1 was obtained for a 0.3 mm thick membrane under an air/CO2 oxygen partial pressure gradient at 1000 °C. It was also found that 40MCO–60CPO dual phase membranes are stable for more than 60 h even when pure CO2 was used as the sweep gas, which recommends 40MCO–60CPO membranes as promising candidates for 4-end membrane operation in an oxy-fuel power plant. -------------------------------------------------------------------------------

Codoping Strategy To Improve Stability and Permeability of Ba0.6Sr0.4FeO3-delta-Based Perovskite Membranes

To improve the stability and oxygen permeability of Ba0.6Sr0.4FeO3-delta (BSF)-based perovskite membranes, an Mg and Zr codoping strategy is proposed. The characterization by X-ray diffraction, Mossbauer spectroscopy and oxygen permeation measurements revealed that single-element Mg doping could improve the oxygen permeability of BSF-based membranes. However, in situ XRD measurements indicated that the single-element Mg doping exhibits a poor thermal stability at low oxygen partial pressure. Single-element Zr doping could improve the structure stability of BSF-based perovskites but lead to a serious decrease of oxygen permeability. Compared with the BSF-based perovskites doped by either Mg or Zr alone, Mg and Zr codoped perovskite Ba0.6Sr0.4Fe0.8Mg0.15Zr0.05O3-delta showed a better stability than single-element Mg doping and exhibited a higher oxygen permeability than single-element Zr doping. For the Mg and Zr codoped BSF, the oxygen permeation flux reached 0.78 mL min(-1) cm(-2) at 950 degrees C under an air/He oxygen partial pressure gradient