Search

Next-generation high-performance structural materials are required for lightweight design strategies and advanced energy applications. Maraging steels, combining a martensite matrix with nanoprecipitates, are a class of high-strength materials with the potential for matching these demands. Their outstanding strength originates from semi-coherent precipitates, which unavoidably exhibit a heterogeneous distribution that creates large coherency strains, which in turn may promote crack initiation under load. Here we report a counterintuitive strategy for the design of ultrastrong steel alloys by high-density nanoprecipitation with minimal lattice misfit. We found that these highly dispersed, fully coherent precipitates (that is, the crystal lattice of the precipitates is almost the same as that of the surrounding matrix), showing very low lattice misfit with the matrix and high anti-phase boundary energy, strengthen alloys without sacrificing ductility. Such low lattice misfit (0.03 ± 0.04 per cent) decreases the nucleation barrier for precipitation, thus enabling and stabilizing nanoprecipitates with an extremely high number density (more than 10 24 per cubic metre) and small size (about 2.7 ± 0.2 nanometres). The minimized elastic misfit strain around the particles does not contribute much to the dislocation interaction, which is typically needed for strength increase. Instead, our strengthening mechanism exploits the chemical ordering effect that creates backstresses (the forces opposing deformation) when precipitates are cut by dislocations. We create a class of steels, strengthened by Ni(Al,Fe) precipitates, with a strength of up to 2.2 gigapascals and good ductility (about 8.2 per cent). The chemical composition of the precipitates enables a substantial reduction in cost compared to conventional maraging steels owing to the replacement of the essential but high-cost alloying elements cobalt and titanium with inexpensive and lightweight aluminium. Strengthening of this class of steel alloy is based on minimal lattice misfit to achieve maximal precipitate dispersion and high cutting stress (the stress required for dislocations to cut through coherent precipitates and thus produce plastic deformation), and we envisage that this lattice misfit design concept may be applied to many other metallic alloys.

Recent literature on material flow analysis has been focused on quantitative characterization of past material flows. Fewer analyses exist on past and prospective quantification of stocks of materials in-use. Some of these analyses explore the composition of products' stocks, but a focus on the characterization of material stocks and its relation with service delivery is often neglected. We propose the use of the methods of human demography to characterize material stocks, defined herein as stock demographics, exploring the insights that this approach could provide for the sustainable management of materials. We exemplify an application of stock demographics by characterizing the composition and service delivery of iron, steel, and aluminum stocks of cars in Great Britain, 2002-2012. The results show that in this period the stock has become heavier, it is traveling less, and it is idle for more time. The visualization of material stocks' dynamics demonstrates the pace of product replacement as a function of its usefulness and enables the formulation of policy interventions and the exploration of future trends.

Many steel-based cities in China were established between the 1950s and 1960s. After more than half a century of development and boom, these cities are starting to decline and industrial transformation is urgently needed. This paper focuses on evaluating the transformation capability of resource-based cities building an evaluation model. Using Text Mining and the Document Explorer technique as a way of extracting text features, the 200 most frequently used words are derived from 100 publications related to steel- and other resource-based cities. The Expert Evaluation Method (EEM) and Analytic Hierarchy Process (AHP) techniques are then applied to select 53 indicators, determine their weights and establish an index system for evaluating the transformation capability of the pillar industry of China's steel-based cities. Using real data and expert reviews, the improved Fuzzy Relation Matrix (FRM) method is applied to two case studies in China, namely Panzhihua and Daye, and the evaluation model is developed using Fuzzy Comprehensive Evaluation (FCE). The cities' abilities to carry out industrial transformation are evaluated with concerns expressed for the case of Daye. The findings have policy implications for the potential and required industrial transformation in the two selected cities and other resource-based towns.

As the world's largest CO(2) emitter and steel producer, China has set the ambitious goal of establishing a circular economy which aims at reconciling economic development with environmental protection and sustainable resource use. This work applies dynamic material flow analysis to forecast production, recycling, and iron ore consumption in the Chinese steel cycle until 2100 by using steel services in terms of in-use stock per capita as driver of future development. The whole cycle is modeled to determine possible responses of the steel industry in light of the circular economy concept. If per-capita stock saturates at 8-12 tons as evidence from industrialized countries suggests, consumption may peak between 2015 and 2020, whereupon it is likely to drop by up to 40% until 2050. A slower growing in-use stock could mitigate this peak and hence reduce overcapacity in primary production. Old scrap supply will increase substantially and it could replace up to 80% of iron ore as resource for steel making by 2050. This would require advanced recycling technologies as manufacturers of machinery and transportation equipment would have to shift to secondary steel as well as new capacities in secondary production which could, however, make redundant already existing integrated steel plants.

Carbon Border Tax Adjustments (BTAs) are a politically popular strategy for avoiding competitive disadvantage problems when a country implements a unilateral climate change policy. A BTA taxes carbon embodied in imported goods in order to protect domestic industry and motivate other countries to implement climate change policy. To estimate the effectiveness of a BTA, is it is necessary to know which products are covered, where they were originally produced and ultimately exported from, and how the covered amount compares to total production in foreign countries. Using a scrap-adjusted, mixed-unit input-output model in conjunction with a multiregional input-output model, this analysis evaluates the effectiveness of BTAs for the case study of U.S. steel imports. Most imported steel by mass is embedded in finished products (60%), and 30% of that steel is produced in a different country than the one from which the final good is exported. Given the magnitudes involved and complexities of global supply chains, a BTA that protects domestic industry will be a challenge to implement. We propose a logistically feasible BTA structure that minimizes the information burden while still accounting for these complexities. However, the amount of steel imported to the U.S. is negligible (5%) compared to foreign production in BTA-eligible countries and is unlikely to motivate affected countries to impose an emissions reduction policy.

Many companies are now good at managing costs and wringing out manufacturing efficiencies. The TQM movement and the disciplines of Six Sigma have seen to that. But the discipline so often brought to the cost side of the business equation is found far less commonly on the revenue side. The authors describe how a global manufacturer of industrial equipment, which they call Acme Incorporated, recently applied Six Sigma to one major revenue related activity--the price-setting process. It seemed to Acme's executives that pricing closely resembled many manufacturing processes. So, with the help of a Six Sigma black belt from manufacturing, a manager from Acme's pricing division recruited a team to carry out the five Six Sigma steps: Define what constitutes a defect. At Acme, a defect was an item sold at an unauthorized price. Gather data and prepare it for analysis. That involved mapping out the existing pricing-agreement process. Analyze the data. The team identified the ways in which people failed to carry out or assert effective control at each stage. Recommend modifications to the existing process. The team sought to decrease the number of unapproved prices without creating an onerous approval apparatus. Create controls. This step enabled Acme to sustain and extend the improvements in its pricing procedures. As a result of the changes, Acme earned dollar 6 million in additional revenue on one product line alone in the six months following implementation--money that went straight to the bottom line. At the same time, the company removed much of the organizational friction that had long bedeviled its pricing process. Other companies can benefit from Acme's experience as they look for ways to exercise price control without alienating customers.