Donor-donor binding in In2O3: Engineering shallow donor levels

Using first-principles band structure methods, we investigate the interactions between different donors in In2O3. Through the formation energy and transition energy level calculations, we find that an oxygen-vacancy creates a deep donor level, while an indium-interstitial or a tin-dopant induces a shallow donor level. The coupling between these donor levels gives rise to even shallower donor levels and leads to a significant reduction in their formation energies. Based on the analysis of the PBE0-corrected band structure and the molecular-orbital bonding diagram, we demonstrate these effects of donor-donor binding. In addition, total energy calculations show that these defect pairs tend to be more stable with respect to the isolated defects due to their negative binding energies. Thus, we may design shallow donor levels to enhance the electrical conductivity via the donor donor binding.

Mechanism for Giycinebetaine to Improve Plant Salt Resistance and Its Research Advances in Genetic Engineering

The paper systematically discusses the mechanism for glycinebetaine to improve plant salt resistance and its research advances in genetic engineering at home and abroad as well as summarizing the research progresses about the key enzymes and their genetic engineering in glycinebetaine biosynthesis. It suggests that on the basis of further understanding the mechanism for glycinebetaine to improve plant salt resistance,the transformation of the genes relating to glycinebetaine biosynthesis should be carried out in major crops so that new plant varieties resistant to salt can be obtained.

A novel neural/symbolic hybrid approach to heuristically optimized fuel allocation and automated revision of heuristics in nuclear engineering

FUELCON is an expert system for optimized refueling design in nuclear engineering. This task is crucial for keeping down operating costs at a plant without compromising safety. FUELCON proposes sets of alternative configurations of allocation of fuel assemblies that are each positioned in the planar grid of a horizontal section of a reactor core. Results are simulated, and an expert user can also use FUELCON to revise rulesets and improve on his or her heuristics. The successful completion of FUELCON led this research team into undertaking a panoply of sequel projects, of which we provide a meta-architectural comparative formal discussion. In this paper, we demonstrate a novel adaptive technique that learns the optimal allocation heuristic for the various cores. The algorithm is a hybrid of a fine-grained neural network and symbolic computation components. This hybrid architecture is sensitive enough to learn the particular characteristics of the ‘in-core fuel management problem’ at hand, and is powerful enough to use this information fully to automatically revise heuristics, thus improving upon those provided by a human expert.

Scale of production and choice of technique in the engineering industries in developing countries

This article examines the relationship between scale of production, optimal choice of technique and costs for three engineering industries: nuts and bolts, iron founding and machine tools. In all three industries costs of production fell as the scale of output increased. This was associated with switches of technique and the spread of fixed costs over a larger number of units. The capital-output ratio fell and labour productivity increased with increases in scale while, in most cases, the capital-labour ratio increased. The implications of these findings are briefly discussed.