Analysis of steelmaking kinetics from IMPHOS pilot plant data

It is widely accepted that understanding the kinetics of steelmaking is a complex task, and reliable and validated kinetics models are required for developing successful steelmaking process models. Therefore, as an initial attempt, this paper analyses the applicability of first order kinetics to explain the steelmaking reaction kinetics using the published data in the IMproving Phosphorus Refining research report. The process data for 20 heats in a 6?tonne pilot plant were analysed for the removal of carbon, silicon, manganese and phosphorus using first order kinetics with static and dynamic equilibrium conditions. It was observed that the removal behaviour of silicon closely followed a first order kinetics relationship, while that of carbon only approximately followed a first order kinetics relationship. The removal of manganese did not show a good degree of fit with first order kinetics using static equilibrium condition, but a clear improvement was observed when calculated using dynamic equilibrium condition. In contrast, the kinetics of phosphorus oxidation did not follow any first order relationship.     

Isoricinoleic acid inSemecarpus kurzii seed oil

Seed oil ofSemecarpus kurzii was found to contain 10.5% of 9-hydroxy-cis-12-enoic (isoricinoleic) acid along with the usual fatty acids. The identification of the hydroxy acid was made on the basis of chromatographic, spectroscopic and chemical methods, with isoricinoleic acid used as the reference standard.     

Chemical investigation of Acacia seed oils

The seed oils of Acacia mollissima, A. torta, A. lenticularis and A. nilotica are found to contain 6.2, 5.3, 4.7 and 3.1%, respectively, cor-onaric acid in addition to other fatty acids. The structure of coronaric acid was established by chemical and physical methods using Chrysanthemum coronarium seed oil and its derived coronaric acid as the reference sample.     

Thermomechanically Triggered Two‐Stage Pattern Switching of 2D Lattices for Adaptive Structures

Pattern switching (or transformation) widely exists in the activities of various creatures and plays an important role in designing adaptive structures in modern materials. Utilizing the glass transition behavior in amorphous polymers, thermomechanically triggered two‐stage pattern switching of 2D lattices is achieved, where components made of an amorphous polymer and a flexible elastomer are interconnected in predesigned layouts. Upon loading at room temperature, the elastomer is far more flexible than the amorphous polymer and the lattice switches into one pattern. With temperature increasing, the modulus of the amorphous polymer decreases due to glass transition. Under the proper choice of amorphous polymer whose storage modulus can decrease to below the modulus of the elastomer, a change in the relative stiffness can be achieved and can switch the overall pattern from one to another while maintaining the external load. Both the experimental and computational studies are carried out to investigate the switching mechanism. Several periodic structures are fabricated to demonstrate several switched patterns. Particularly, a proof‐of‐concept smart window design is fabricated to explore the potential engineering applications.     

On channel estimation in cell-free massive MIMO for spatially correlated channels with correlated shadowing under Rician fading

This work addresses channel estimation (CE) in the uplink phase for a cell-free massive multiple-input multiple-output system operating under the time division duplex protocol. Considering that, channels are spatially correlated under the Rician fading model, where the investigated model is composed of two components: deterministic and nondeterministic, with the deterministic component describing the line-of-sight paths and the nondeterministic component describing the non-line-of-sight paths. Additionally, we dealt with correlated shadow fading that represents the most realistic situation. On the other hand, this work introduces a dynamic cooperation cluster framework in which the user is not served with the whole network ( i.e., all access points [APs]) but only the APs that present the best channel conditions regarding that user. In other words, this work proposes partial CE for each user because only APs with the best channel conditions are allowed to compute channel estimates. Consequently, we proposed partial channel estimators that perform the CE process with low complexity, namely, a partial minimum mean square error estimator and a partial element-wise minimum mean square error estimator. In addition, a simple pilot assignment technique is proposed in order to reduce interference signals so that each user experiences low interference from other users. Furthermore, the computational complexity required by each estimator is derived, where it is represented by the number of complex multiplications that each estimator requires in each consistency block. Theoretical and simulated results are provided, where the performance of each estimator is evaluated and analyzed using the normalized mean-square error metric.