Industrial sugar beets to biofuel: Field to fuel production system and cost estimates

Specialized varieties of sugar beets (Beta vulgaris L.) may be an eligible feedstock for advanced biofuel designation under the USA Energy Independence and Security Act of 2007. These non-food industrial beets could double ethanol production per hectare compared to alternative feedstocks. A mixed-integer mathematical programming model was constructed to determine the breakeven price of ethanol produced from industrial beets, and to determine the optimal size and biorefinery location. The model, based on limited field data, evaluates Southern Plains beet production in a 3-year crop rotation, and beet harvest, transportation, and processing. The optimal strategy depends critically on several assumptions including a just-in-time harvest and delivery system that remains to be tested in field trials. Based on a wet beet to ethanol conversion rate of 110 dm³ Mg⁻¹ and capital cost of 128 M$ for a 152 dam³ y⁻¹ biorefinery, the estimated breakeven ethanol price was 507 $ m⁻³. The average breakeven production cost of corn (Zea mays L.) grain ethanol ranged from 430 to 552 $ m⁻³ based on average net corn feedstock cost of 254 and 396 $ m⁻³ in 2014 and 2013, respectively. The estimated net beet ethanol delivered cost of 207 $ m⁻³ was lower than the average net corn feedstock cost of 254–396$ m⁻³ in 2013 and 2014. If for a mature industry, the cost to process beets was equal to the cost to process corn, the beet breakeven ethanol price would be $387 m^-3 (587 $ m⁻³ gasoline equivalent).     

Material design and development: From classical thermodynamics to CALPHAD and ICME approaches

This paper presents an overview and examples of material design and development using (1) classical thermodynamics; (2) CALPHAD (calculation of phase diagrams) modeling; and (3) Integrated Computational Materials Engineering (ICME) approaches. Although the examples are given in lightweight aluminum and magnesium alloys for structural applications, the fundamental methodology and modeling principles are applicable to all materials and engineering applications. The examples in this paper have demonstrated the effectiveness and limitations of classical thermodynamics in solving specific problems (such as nucleation during solidification and solid-state precipitation in aluminum alloys). Computational thermodynamics and CALPHAD modeling, when combined with critical experimental validation, have been used to guide the selection and design of new magnesium alloys for elevated-temperature applications. The future of material design and development will be based on a holistic ICME approach. However, key challenges exist in many aspects of ICME framework, such as the lack of diffusion/mobility databases for many materials systems, limitation of current microstructural modeling capability and integration tools for simulation codes of different length scales.     

非常规蛋白基木材胶黏剂研究现状及发展前景

介绍了动物和植物型非常规蛋白资源的种类及其制备蛋白基木材胶黏剂的研究现状和存在的问题,展望了非常规蛋白胶黏剂的发展前景。     

大同市水资源开发利用状况与承载能力的思考

文中分析了大同市水资源开发利用的状况，并对水资源承载能力的有关问题进行了讨论。     

图书在版编目研究

简述了英、美等国图书在版编目的发展和中国实施在版编目的意义、作用及特点,对中国实施图书在版编目提出了设想和建议。     

The Intellectual Development of Science and Engineering Students. Part 2: Teaching to Promote Growth

As college students experience the challenges of their classes and extracurricular activities, they undergo a developmental progression in which they gradually relinquish their belief in the certainty of knowledge and the omniscience of authorities and take increasing responsibility for their own learning. At the highest developmental level normally seen in college students (which few attain before graduation), they display attitudes and thinking patterns resembling those of expert scientists and engineers, including habitually and skillfully gathering and analyzing evidence to support their judgments. This paper proposes an instructional model designed to provide a suitable balance of challenge and support to advance students to that level. The model components are (1) variety and choice of learning tasks; (2) explicit communication and explanation of expectations; (3) modeling, practice, and constructive feedback on high‐level tasks; (4) a student‐centered instructional environment; and (5) respect for students at all levels of development.