Abstract: Global environmental problems have urged the need for developing sustainable technologies. However, new technologies that enter the market have often higher economic costs and potentially higher environmental impacts than conventional technologies. This can be explained by learning effects: a production process that is performed for the first time runs less smooth than a production process that has been in operation for years. To obtain a fair estimation of the potential of a new technology, learning effects need to be included. A review on the current literature on learning effects was conducted in order to provide guidelines on how to include learning effects in prospective technology assessment. Based on the results of this review, five recommendations have been formulated and an integration of learning effects in the structure of prospective technology assessment has been proposed. These five recommendations include the combined use of learning effects on the component level and on the end product level; the combined use of learning effects on the technical, economic and environmental level; the combined use of extrapolated values and expert estimates; the combined use of learning-by-doing and learning-by-searching effects and; a tier-based method, including quality criteria, to calculate the learning effect. These five complementary strategies could lead to a clearer perspective on the environmental impact and cost structure of the new technology and a fairer comparison base with conventional technologies, potentially resulting in a faster adoption and a shorter time-to-market for sustainable technologies.

Abstract: Companies dealing with chemical products have to cope with large amounts of waste and environmental risk due to the use and production of toxic substances. Against this background, increasing attention is being paid to green chemistry and the translation of this concept into biobased chemicals. Given the multitude of economic, environmental and societal impacts that the production and use of biobased chemicals have on sustainability, assessment approaches need to be developed that allow for measurement and comparison of these impacts. To evaluate sustainability in the context of policy and decision-making, indicators are generally accepted means. However, sustainability indicators currently predominantly exist for low-value applications in the bioeconomy, like bioenergy and biofuels. In this paper, a review of the state-of-the-art sustainability indicators for biobased chemicals is conducted and a gap analysis is performed to identify indicator development needs. Based on the analysis, a clear hierarchy within the concept of sustainability is found where the environmental aspect dominates over economic and social indicators. All one-dimensional indicator-sets account for environmental impacts (50%), whereas two-dimensional sets complement the environmental issues with economic indicators (34%). Moreover, even the sets encompassing all three sustainability dimensions (16%) do not account for the dynamics and interlinkages between the environment, economy and society. Using results from the literature review, an indicator list is presented that captures all indicators currently used within sustainability assessment of biobased chemicals. Finally, a framework is proposed for future indicator selection using a stakeholder survey to obtain a prioritized list of sustainability indicators for biobased chemicals.

Abstract: Multi-objective optimization is an important decision-making tool for energy processes, as multiple targets need to be achieved. These objectives are usually conflicting since a single solution cannot be optimal for all objectives, resulting in a set of Pareto-optimal solutions. Multiple indicators might be available to describe a sustainability objective, such as the environmental impact which is commonly evaluated by performing a life cycle assessment. In this study, Pareto aggregation is proposed as a method which employs a novel multi-objective optimization-based approach as an alternative to the classically used aggregation in life cycle assessment. This method identifies conflicting environmental indicators and performs an aggregation among those that require a trade-off. An environmental-economic optimization of a second-generation bioethanol plant is used to illustrate and evaluate the proposed method. Process parameters from a biochemical conversion pathway flowsheet simulation model are chosen as optimization variables. To reduce the computational time, surrogate models, based on artificial neural networks, are used. Out of the eighteen ReCiPe Midpoint environmental indicators, five were identified as conflicting, resulting in an aggregated environmental objective, which was then traded off with the economic objective function, chosen as the levelized cost of ethanol. Comparison with the widely used single-score EcoIndicator99 showed that the Pareto aggregation method can reduce most of the environmental indicators by up to 6.5%. This research provides an insight on non-redundant objective functions, aiming at reducing the dimensionality of multi-objective optimization problems, while taking into consideration decision-makers’ preferences.

Abstract: Sodium ion batteries (NIBs) are one of the versatile technologies for lowcost rechargeable batteries. O3-type layered sodium transition metal oxides (NaMO2, M = transition metal ions) are one of the most promising positive electrode materials considering their capacity. However, the use of O3 phases is limited due to their low redox voltage and associated multiple phase transitions which are detrimental for long cycling. Herein, a simple strategy is proposed to successfully combat these issues. It consists of the introduction of a larger, nontransition metal ion Sn4+ in NaMO2 to prepare a series of NaNi0.5Mn0.5−y SnyO2 (y = 0–0.5) compositions with attractive electrochemical performances, namely for y = 0.5, which shows a single-phase transition from O3 ⇔ P3 at the very end of the oxidation process. Na-ion NaNi0.5Sn0.5O2/C coin cells are shown to deliver an average cell voltage of 3.1 V with an excellent capacity retention as compared to an average stepwise voltage of ≈2.8 V and limited capacity retention for the pure NaNi0.5Mn0.5O2 phase. This study potentially shows the way to manipulate the O3 NaMO2 for facilitating their practical use in NIBs.

Abstract: A robust and easy to handle 3D porous platinum structure was created via replicating the 3D channel system
of an ordered mesoporous silica material using atomic layer deposition (ALD) over micrometer distances.
After ALD of Pt in the silica material, the host template was digested using hydrogen fluoride (HF). A fully
connected ordered Pt nanostructure was obtained with morphology and sizes corresponding to that of
the pores of the host matrix, as revealed with high-resolution scanning transmission electron
microscopy and electron tomography. The Pt nanostructure consisted of hexagonal Pt rods originating
from the straight mesopores (11 nm) of the host structure and linking features resulting from Pt
replication of the interconnecting mesopore segments (2–4 nm) present in the silica host structure.
Electron tomography of partial replicas, made by incomplete infilling of Zeotile-4 material with Pt,
provided insight in the connectivity and formation mechanism of the Pt nanostructure by ALD. The Pt
replica was evaluated for its potential use as electrocatalyst for the hydrogen evolution reaction, one of
the half-reactions of water electrolysis, and as microelectrode for biomedical sensing. The Pt replica
showed high activity for the hydrogen evolution reaction and electrochemical characterization revealed
a large impedance improvement in comparison with reference Pt electrodes.