Multiblob coarse-graining for mixtures of long polymers and soft colloids

Soft nanocomposites represent both a theoretical and an experimental challenge due to the high number of the microscopic constituents that strongly influence the behaviour of the systems. An effective theoretical description of such systems invokes a reduction of the degrees of freedom to be analysed, hence requiring the introduction of an efficient, quantitative, coarse-grained description. We here report on a novel coarse graining approach based on a set of transferable potentials that quantitatively reproduces properties of mixtures of linear and star-shaped homopolymeric nanocomposites. By renormalizing groups of monomers into a single effective potential between a $f$-functional star polymer and an homopolymer of length $N_0$, and through a scaling argument, it will be shown how a substantial reduction of the to degrees of freedom allows for a full quantitative description of the system. Our methodology is tested upon full monomer simulations for systems of different molecular weight, proving its full predictive potential

Temperature dependence of surface stress across an order-disorder transition: p(1x2)O/W(110)

Strain relaxations of a p(1x2) ordered oxygen layer on W(110) are measured as a function of temperature across the disordering transition using low-energy electron diffraction. The measured strains approach values of 0.027 in the [1-10] and -0.053 in the [001] direction. On the basis of the measured strain relaxations, we give quantitative information on temperature-dependent surface stress using the results of ab initio calculations. From the surface formation energy for different strains, determined by first-principles calculations, we estimate that surface stress changes from -1.1 for the ordered phase to -0.2N/m for the disordered one along [1-10], and from 5.1 to 3.4 N/m along [001]. Moreover, our observation that the strains scale inversely with domain size confirms that the strain relaxation takes place at the domain boundaries.Comment: 8 pages, 5 figure

A methodology based on benchmarking to learn across megaprojects: the case of nuclear decommissioning

Purpose: The literature lacks a single and universally accepted definition of major and megaprojects: usually, these projects are described as projects with a budget above $1 billion and a high level of innovation, complexity & uniqueness both in terms of physical infrastructure and stakeholder network. Moreover, they often provide fewer benefits than what were originally expected and are affected by delays and cost overruns. Despite this techno-economic magnitude, it is still extremely hard to gather lessons learned from these projects in a systematic way. This paper presents an innovative methodology based on benchmarking to investigate good and bad practices and learn from a portfolio of unique megaprojects. Design/methodology/approach: The methodology combines quantitative & qualitative cross-comparison of case studies and statistical analysis into an iterative process. Findings: Indeed, benchmarking offers significant potential to identify good and bad practices and improve the performance of project selection, planning and delivery. Research limitations/implications: The methodology is exemplified in this paper using the case of Nuclear Decommissioning Projects and Programmes (NDPs). Originality/value: Indeed, due to their characteristics, NDPs can be addressed as megaprojects, and are a relevant example for the application of the methodology presented here that collects and investigates the characteristics that mostly impact the performance of (mega)projects, through a continuous learning process

Futureproofing Complex Infrastructure Projects Using Real Options

Existing project performance measures in the infrastructure sector focus on construction performance (time, cost, quality) and pay less attention to lifecycle performance. The consequence of this shortsighted perspective is that decisions taken early lead to poorer solutions. Infrastructure that should last centuries quickly becomes inadequate, leading to costly reconfigurations. Real options reasoning can help managers to overcome this issue by unlocking lifecycle performance thinking in complex infrastructure projects. Real options reasoning enables managers to explore the value of flexibility by employing futureproofing strategies during the development process. From analysis of interviews with experts in healthcare infrastructure, we observed that projects that led to obsolescence were developed using tight design briefs and were focused on capital targets, and decision-makers were less invested in the concept of futureproofing. On the other hand, projects that were futureproofed followed a loosely-defined design brief and shifted focus towards whole-life targets. We make five recommendations for futureproofed infrastructure

Project financing in nuclear new build, why not? The legal and regulatory barriers

This paper investigates the legal barriers to apply project finance for building nuclear power plants. Countries such as the UK, Turkey and emerging economies (i.e. Malaysia and Indonesia) are increasingly seeking to attract private investors for nuclear projects using project finance. This is an innovative approach, and until now the only cases registered are Hinckley Point C in the UK and Akkuyu in Turkey. This paper scrutinises the mismatches between the requirements of project finance and nuclear law. Nuclear law introduces specific requirements affecting the security interest of private lenders, hindering the bankability of nuclear projects on a non-recourse basis. The paper emphasises that the performance-based regulatory approach is more compatible with project finance compared to the prescriptive based one. Furthermore, the paper examines the gaps between nuclear and holistic energy law, looking at the financing of energy infrastructures. Improving nuclear law enables to apply project finance to nuclear power plants, facilitating their deployment. Consequently, nuclear law plays a central role in promoting sustainable energy mixes characterised by reduced carbon emissions

Evaluation of colestilan in chronic kidney disease dialysis patients with hyperphosphataemia and dyslipidaemia: a randomized, placebo-controlled, multiple fixed-dose trial

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Talking about Futureproofing: Real Options Reasoning in Complex Infrastructure Projects

Complex infrastructure projects often attract criticism regarding their short- and long-term performance. An effective development process requires thinking about both present and future requirements. We employed the lens of real options reasoning to investigate the power of verbal theorizing, without the aid of analytical modeling, to add flexibility in the development process. Drawing on 32 semi-structured interviews with decision-makers involved in health estate projects, we examined if and how informal talks in the development process can lead to futureproof outcomes. Our findings synthesize and conceptualize relevant insights on iterative design thinking, affordability, bounded rationality, and motivational gaps as causal mechanisms for futureproofing talks and thus real options reasoning. This article contributes to the planning and project studies literature dealing with futureproofing complex infrastructure projects