Abstract: Three-dimensional (3D) computational fluid dynamics (CFD) simulations were performed to study solids flow dynamics and solids back-mixing behavior in a screw reactor (designed for thermal conversion of dry biomass particles) based on the Eulerian-Eulerian method. Simulation results were compared against experimental data with respect to filling degree and mean residence time of particles. The mean deviations for filling degree and for mean residence time between simulation and experiment were about 0.01 and 11.4 s, respectively, which shows that the model is reasonably accurate in predicting solids flow behavior in the screw reactor. The solids flow dynamics inside the reactor were discussed. The solids residence time distribution (RTD) was calculated and the degree of solids back-mixing in the forward transportation direction of the reactor was analyzed. It was found that solids being flung over the shaft and solids back-leakage, resulting from the low solids forward transportation velocity at the clearance between the flight and the bottom shell of the screw reactor, were responsible for solids back-mixing. The degree of solids back-mixing can be reduced at higher screw rotating speeds when keeping inlet mass flow rate of solids constant. (C) 2019 Elsevier Ltd. All rights reserved.

Abstract: We present a decision-support system that guides heritage guardians in selecting mitigation actions to improve the indoor air quality and thus the preservation conditions of indoor collections in heritage buildings. This contribution shows that it is feasible to build a decision support system dedicated to preventive conservation when the following barriers are overcome: 1) simultaneous measurement of a wide range of environmental parameters in order to detect a larger number of undesired situations; 2) development of an algorithm to perform reproducible indoor air quality assessments; and 3) transformation of the air quality assessment into a graph that can be read intuitively without causing a wide variation of interpretations among stakeholders. An important aspect of the decision support system is that it reduces several sources of uncertainty that hamper reliable indoor air quality assessments. The possibilities of such a system are illustrated with a measurement campaign in a church where a heating system has been installed and used for the first time.

Abstract: Colloidal nanocrystals combine size- and facet-dependent properties with solution processing. They offer thus a compelling suite of materials for technological applications. Their size- and facet-tunable features are studied in synthesis; however, to exploit their features in optoelectronic devices, it will be essential to translate control over size and facets from the colloid all the way to the film. Larger-diameter colloidal quantum dots (CQDs) offer the attractive possibility of harvesting infrared (IR) solar energy beyond absorption of silicon photovoltaics. These CQDs exhibit facets (nonpolar (100)) undisplayed in small-diameter CQDs; and the materials chemistry of smaller nanocrystals fails consequently to translate to materials for the short-wavelength IR regime. A new colloidal management strategy targeting the passivation of both (100) and (111) facets is demonstrated using distinct choices of cations and anions. The approach leads to narrow-bandgap CQDs with impressive colloidal stability and photoluminescence quantum yield. Photophysical studies confirm a reduction both in Stokes shift (approximate to 47 meV) and Urbach tail (approximate to 29 meV). This approach provides a approximate to 50% increase in the power conversion efficiency of IR photovoltaics compared to controls, and a approximate to 70% external quantum efficiency at their excitonic peak.

Abstract: The aged Ni-rich NiTi shape memory alloys (SMAs) exhibit the multi-stage martensitic transformation (MMT), which has important influences on functional properties and practical applications of the NiTi SMAs. A hidden single-stage martensitic transformation from B2 parent phase to B19' martensite phase is found in an aged Ni51Ti49 alloy, which happens concurrently with a commonly observed two-stage martensitic transformation B2-R-B19' (R: martensite phase) and actually composes one stage of a multi-stage martensitic transformation (MMT) together with the two-stage one. B2-B19' martensitic transformation occurs in the NiTi matrix containing Ni4Ti3 precipitates with relatively large inter-particle space, while B2-R-B19' transformation takes place in the NiTi matrix with Ni4Ti3 precipitates having relatively small inter-particle space. (C) 2019 Elsevier B.V. All rights reserved.

Abstract: The use of fossil-based products induces a large environmental burden. To lighten this burden, green technologies are required that can replace their fossil-based counterparts. To enable the development of economically viable green technologies, an optimization towards both economic and environmental objectives is required. To perform this multi-objective optimization (MOO), the environmental techno-economic assessment (ETEA) methodology is extended towards a MOO-extended ETEA. The development of this MOO-extended ETEA is the main objective of this manuscript. As an example of a green technology, the concept of microalgae biorefineries is used as a case study to illustrate the MOO-extended ETEA. According to the results, all optimal value chains include open pond cultivation, a membrane for medium recycling and spray drying. The optimal economic value chain uses Nannochloropsis sp. in a one-stage cultivation to produce fish larvae feed, while the optimal environmental design uses Dunaliella salina or Haematococcus pluvialis to produce carotenoids and fertilizer or energy products, by means of anaerobic digestion or gasification. The crucial parameters for both environmental and economic feasibility are the content, price and reference impact of the main end product, the growth parameters and the biomass and carotenoid recovery efficiency alongside the different process steps. By identifying the economic and environmentally optimal algal-based value chain and the crucial drivers, the MOO-extended ETEA provides insights on how algae-based value chains can be developed in the most economic and environmentally-friendly way. For example, the inclusion of a medium recycling step to lower the water and salt consumption is required in all Pareto-optimal scenarios. Another major insight is the requirement of high-value products such as carotenoids or specialty food to obtain and economically and environmentally feasible algal-based value chain. Due to the modular nature of the MOO-extended ETEA, multiple processes can be included or excluded from the superstructure. Although this case study is limited to current microalgae biorefinery technologies, the MOO-extended ETEA can also be used to assess the economic and environmental effect of more innovative technologies. This way, the MOO-extended ETEA provides a methodology to assess the economic and environmental potential of innovative green technologies and shorten their time-to-market.

Abstract: Identifying priority areas is an essential step in developing management strategies to reduce pesticide loads in surface water. A spatially explicit model-based approach was developed to detect priority areas for diffuse pesticide pollution at catchment scale. The method uses available datasets and considers different pesticide pathways in the environment post-application. The approach was applied in a catchment area in SE Flanders (Belgium) as a case study. Calculated risk areas were obtained using detailed landscape data and combining pesticide emissions and hydrological connectivity. The risk areas obtained were further compared with an alternative observation-based method, developed specifically for this study site that includes long-term field observations and local expert knowledge. Both methods equally classified 50% of the areas. The impact of crop rotation on the calculated risk was analysed. High-risk areas were identified and added to a cumulative map over all five years to evaluate temporal variations. The model-based approach was used for the initial identification of risk areas at the study site. The tool helps to prioritise zones and detect particular fields to target landscape mitigation measures to reduce diffuse pesticide pollution reaching surface water bodies.

Abstract: While titanium-based metal-organic frameworks (MOFs) have been widely studied for their (photo) catalytic potential, only a few Ti-IV MOFs have been reported owing to the high reactivity of the employed titanium precursors. The synthesis of COK-47 is now presented, the first Ti carboxylate MOF based on sheets of (TiO6)-O-IV octahedra, which can be synthesized with a range of different linkers. COK-47 can be synthesized as an inherently defective nanoparticulate material, rendering it a highly efficient catalyst for the oxidation of thiophenes. Its structure was determined by continuous rotation electron diffraction and studied in depth by X-ray total scattering, EXAFS, and solid-state NMR. Furthermore, its photoactivity was investigated by electron paramagnetic resonance and demonstrated by catalytic photodegradation of rhodamine 6G.

Abstract: Solar energy plays an important role in solving serious environmental
problems and meeting the high energy demand. However, the lack of suitable
materials hinders further progress of this technology. Here, we present the largest
inorganic solar cell material search till date using density functional theory (DFT) and
machine-learning approaches. We calculated the spectroscopic limited maximum
efficiency (SLME) using the Tran−Blaha-modified Becke−Johnson potential for 5097
nonmetallic materials and identified 1997 candidates with an SLME higher than 10%,
including 934 candidates with a suitable convex-hull stability and an effective carrier
mass. Screening for two-dimensional-layered cases, we found 58 potential materials
and performed G0W0 calculations on a subset to estimate the prediction uncertainty. As the above DFT methods are still computationally expensive, we developed a high accuracy machine-learning model to prescreen efficient materials and applied it to over a million materials. Our results provide a general framework and universal strategy for the design of high-efficiency solar
cell materials. The data and tools are publicly distributed at: https://www.ctcms.nist.gov/~knc6/JVASP.html, https://www.
ctcms.nist.gov/jarvisml/, https://jarvis.nist.gov/, and https://github.com/usnistgov/jarvis.

Abstract: Hydrodynamic flow in two-dimensional electron systems has so far been probed only by dc transport and scanning gate microscopy measurements. In this work we discuss theoretically signatures of the hydrodynamic regime in near-field optical microscopy. We analyze the dispersion of acoustic plasmon modes in two-dimensional electron liquids using a nonlocal conductivity that takes into account the effects of (momentumconserving) electron-electron collisions, (momentum-relaxing) electron-phonon and electron-impurity collisions, and many-body interactions beyond the celebrated random phase approximation. We derive the dispersion and, most importantly, the damping of acoustic plasmon modes and their coupling to a near-field probe, identifying key experimental signatures of the crossover between collisionless and hydrodynamic regimes.

Abstract: The installation of urban green infrastructure, particularly green walls, has proven to be an effective strategy for the mitigation of particulate matter (PM) pollution and the urban heat island effect. For the interaction between vegetation, PM and the local microclimate, wind flow is the main driving force. In order to investigate these interactions in detail, it is important to know how air flows through vegetation. This study proposes a method based on the DarcyForchheimer equation, where vegetation is considered as a porous medium and several plant species and the effects of plant morphological characteristics are examined both experimentally and using computer simulations. Results showed that the DarcyForchheimer model is a simple and robust way to describe air flow through vegetation regardless of its morphology. This research provides a new vision on studying aerodynamic properties of vegetation in relation to their morphology and provides opportunities for model the interaction between vegetation and its environment.

Abstract: In the present work, multiphysics modeling was used to investigate the feasibility of a photocatalysis-based outdoor air purifying solution that could be used in high polluted streets, especially street canyons. The article focuses on the use of a semi-active photocatalysis in the surfaces of the street as a solution to remove anthropogenic pollutants from the air. The solution is based on lamellae arranged horizontally on the wall of the street, coated with a photocatalyst (TiO2), lightened with UV light, with a dimension of 8 cm × 48 cm × 1 m. Fans were used in the system to create airflow. A high purification percentage was obtained. An artificial neural network (ANN) was used to predict the optimal purification method based on previous simulations, to design purification strategies considering the energy cost. The ANN was used to forecast the amount of purified with a feed-forward neural network and a backpropagation algorithm to train the model.

Abstract: Plasma-liquid systems have attracted increasing attention in recent years, owing to their high potential in material processing and nanoscience, environmental remediation, sterilization, biomedicine, and food applications. Due to the multidisciplinary character of this scientific field and due to its broad range of established and promising applications, an updated overview is required, addressing the various applications of plasma-liquid systems till now. In the present review, after a brief historical introduction on this important research field, the authors aimed to bring together a wide range of applications of plasma-liquid systems, including nanomaterial processing, water analytical chemistry, water purification, plasma sterilization, plasma medicine, food preservation and agricultural processing, power transformers for high voltage switching, and polymer solution treatment. Although the general understanding of plasma-liquid interactions and their applications has grown significantly in recent decades, it is aimed here to give an updated overview on the possible applications of plasma-liquid systems. This review can be used as a guide for researchers from different fields to gain insight in the history and state-of-the-art of plasma-liquid interactions and to obtain an overview on the acquired knowledge in this field up to now.

Abstract: As landfill mining (LFM) gains public attention, systematic assessment of its economic potential is deemed necessary. The aim of this review is to critically analyze the usefulness and validity of previous economic assessments of LFM. Following the life cycle costing (LCC) framework, (i) the employed methods based on goal and scope, technical parameters and data inventory, and modelling choices were contrasted with respect to (ii) the synthesized main findings based on net profitability and economic performance drivers. Results showed that the selected studies (n=15) are mostly case study-specific and concluded that LFM has a weak economic potential, hinting at the importance of favorable market and regulation settings. However, several method issues are apparent as costs and revenues are accounted at different levels of aggregation, scope and scale-from process to sub-process level, from private to societal economics, and from laboratory to pilot-scale, respectively. Moreover, despite the inherent large uncertainties, more than half of the studies did not perform any uncertainty or sensitivity analyses posing validity issues. Consequently, this also limits the usefulness of results as individual case studies and as a collective, towards a generic understanding of LFM economics. Irrespective of case study-specific or generic aims, this review recommends that future assessments should be learning-oriented. That is, uncovering granular information about what builds up the net profitability of LFM, to be able to systematically determine promising paths for the development of cost-efficient projects.