A Novel Method for the Preparation of Fibrous CeO2–ZrO2–Y2O3 Compacts for Thermochemical Cycles

Zirconium-Yttrium-co-doped ceria (Ce0.85Zr0.13Y0.02O1.99) compacts consisting of fibers with diameters in the range of 8–10 µm have been successfully prepared by direct infiltration of commercial YSZ fibers with a cerium oxide matrix and subsequent sintering. The resulting chemically homogeneous fiber-compacts are sinter-resistant up to 1923 K and retain a high porosity of around 58 vol% and a permeability of 1.6–3.3 × 10−10 m² at a pressure gradient of 100–500 kPa. The fiber-compacts show a high potential for the application in thermochemical redox cycling due its fast redox kinetics. The first evaluation of redox kinetics shows that the relaxation time of oxidation is five times faster than that of dense samples of the same composition. The improved gas exchange due to the high porosity also allows higher reduction rates, which enable higher hydrogen yields in thermochemical water-splitting redox cycles. The presented cost-effective fiber-compact preparation method is considered very promising for manufacturing large-scale functional components for solar-thermal high-temperature reactors.

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NiCo2O4 bricks as anode materials with high lithium storage property

MRS Advances ◽

10.1557/adv.2019.169 ◽

2019 ◽

Vol 4 (33-34) ◽

pp. 1861-1868 ◽

Cited By ~ 1

Author(s):

Hui Wang ◽

Youning Gong ◽

Delong Li ◽

Qiang Fu ◽

Chunxu Pan

Keyword(s):

Lithium Ion Battery ◽

Anode Material ◽

Current Density ◽

Large Scale ◽

Lithium Ion ◽

Cost Effective ◽

Reversible Capacity ◽

High Rate ◽

High Porosity ◽

Lithium Storage

ABSTRACTIn this study, a novel brick-like NiCo2O4 material was synthesized via a facile hydrothermal method. The as-prepared NiCo2O4 material possessed high porosity with the BET specific surface area of 58.33 m2/g, and its pore size distribution was in a range of 5-15 nm with a dominant pore diameter of 10.7 nm. The electrochemical performance of the NiCo2O4 was further investigated as anode material for lithium-ion battery. The NiCo2O4 anode possessed a high lithium storage capacity up to 2353.0 mAh/g at the current density of 100 mA/g. Even at the high rate of 1 A/g, a reversible capacity of ∼600 mAh/g was still retained, and an average discharge capacity of ∼1145 mAh/g could be recovered when the current density was reduced back to 150 mA/g. Due to the simple and cost-effective process, the NiCo2O4 bricks anode material shows great potential for further large-scale applications on the area of lithium-ion battery.

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PVB/PEG-Based Feedstocks for Injection Molding of Alumina Microreactor Components

Materials ◽

10.3390/ma12081219 ◽

2019 ◽

Vol 12 (8) ◽

pp. 1219 ◽

Cited By ~ 2

Author(s):

Anna Julia Medesi ◽

Dorit Nötzel ◽

Thomas Hanemann

Keyword(s):

Injection Molding ◽

Large Scale ◽

Metal Oxide Nanoparticles ◽

Reaction Medium ◽

Cost Effective ◽

Polyvinyl Butyral ◽

Shear Stresses ◽

Scale Production ◽

Ceramic Injection Molding ◽

Functional Components

The ceramic injection molding (CIM) process is a cost-effective powder-based near net shape manufacturing process for large-scale production of complex-shaped ceramic functional components. This paper presents the rheological analysis of environmentally friendly CIM feedstock formulations based on the binder components polyvinyl butyral (PVB) and polyethylene gycol (PEG). The prepared PVB/PEG-based alumina molding compounds were investigated with respect to their PVB:PEG ratios as well as to their powder filling degrees in the range between 50 and 64 vol.%. Corresponding viscosities and shear stresses were determined for increasing shear rates to show the effects of increased PEG content and solid loadings on them. Two single reactor components were injection molded and subsequently joined in their green state for fabrication of an alumina microreactor. The intended purpose of the alumina microreactors is their potential application as wear-resistant and hydrothermal stable multifunctional devices (µ-mixer, µ-reactor, µ-analyzer) for continuous hydrothermal synthesis (CHTS) of metal oxide nanoparticles in supercritical water (sc-H2O) as the reaction medium.

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Electrospun Nanomaterials for Energy Applications: Recent Advances

Applied Sciences ◽

10.3390/app9061049 ◽

2019 ◽

Vol 9 (6) ◽

pp. 1049 ◽

Cited By ~ 13

Author(s):

Saveria Santangelo

Keyword(s):

Large Scale ◽

Three Dimensional ◽

Cost Effective ◽

Water Desalination ◽

High Porosity ◽

Capacitive Deionization ◽

Fiber Networks ◽

Energy Applications ◽

Recent Advances ◽

Highly Porous

Electrospinning is a simple, versatile, cost-effective, and scalable technique for the growth of highly porous nanofibers. These nanostructures, featured by high aspect ratio, may exhibit a large variety of different sizes, morphologies, composition, and physicochemical properties. By proper post-spinning heat treatment(s), self-standing fibrous mats can also be produced. Large surface area and high porosity make electrospun nanomaterials (both fibers and three-dimensional fiber networks) particularly suitable to numerous energy-related applications. Relevant results and recent advances achieved by their use in rechargeable lithium- and sodium-ion batteries, redox flow batteries, metal-air batteries, supercapacitors, reactors for water desalination via capacitive deionization and for hydrogen production by water splitting, as well as nanogenerators for energy harvesting, and textiles for energy saving will be presented and the future prospects for the large-scale application of electrospun nanomaterials will be discussed.

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Sequence-Selective Recognition of Extended-Spectrum β-Lactamase GES-2 by a Competitive, Peptide Nucleic Acid-Based Multiplex PCR Assay

Antimicrobial Agents and Chemotherapy ◽

10.1128/aac.48.9.3402-3406.2004 ◽

2004 ◽

Vol 48 (9) ◽

pp. 3402-3406 ◽

Cited By ~ 6

Author(s):

Gerhard F. Weldhagen

Keyword(s):

Nucleic Acid ◽

Multiplex Pcr ◽

Peptide Nucleic Acid ◽

Large Scale ◽

Cost Effective ◽

Coding Region ◽

Screening Programs ◽

Extended Spectrum ◽

Multiplex Pcr Assay ◽

Novel Method

ABSTRACT Extended-spectrum β-lactamases (ESBLs) in Pseudomonas aeruginosa, such as GES-2, which compromises the efficacy of imipenem, tend to be geographically restricted. The CC-to-AA base pair substitution at positions 493 and 494 of the bla GES-2-coding region distinguishes this ESBL from bla GES-1 and the bla IBC-type genes, making it an ideal target for the development of a novel sequence-specific, peptide nucleic acid (PNA)-based multiplex PCR detection method. By using two primer pairs in conjunction with a PNA probe, this method provided an accurate means of identification of bla GES-2 compared to standard PCR and gene sequencing techniques when it was used to test 100 P. aeruginosa clinical isolates as well as previously published, well-described control strains encompassing all presently known genes in the bla GES-IBC ESBL family. This novel method has the potential to be used in large-scale, cost-effective screening programs for specific or geographically restricted ESBLs.

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A novel method of microsatellite genotyping-by-sequencing using individual combinatorial barcoding

Royal Society Open Science ◽

10.1098/rsos.150565 ◽

2016 ◽

Vol 3 (1) ◽

pp. 150565 ◽

Cited By ~ 33

Author(s):

Salla Vartia ◽

José L. Villanueva-Cañas ◽

John Finarelli ◽

Edward D. Farrell ◽

Patrick C. Collins ◽

...

Keyword(s):

Large Scale ◽

Genotyping By Sequencing ◽

Cost Effective ◽

Universal Primers ◽

Microsatellite Data ◽

Experimental Conditions ◽

Genetic Studies ◽

Scale Population ◽

Novel Method ◽

Generation Sequencing

This study examines the potential of next-generation sequencing based ‘genotyping-by-sequencing’ (GBS) of microsatellite loci for rapid and cost-effective genotyping in large-scale population genetic studies. The recovery of individual genotypes from large sequence pools was achieved by PCR-incorporated combinatorial barcoding using universal primers. Three experimental conditions were employed to explore the possibility of using this approach with existing and novel multiplex marker panels and weighted amplicon mixture. The GBS approach was validated against microsatellite data generated by capillary electrophoresis. GBS allows access to the underlying nucleotide sequences that can reveal homoplasy, even in large datasets and facilitates cross laboratory transfer. GBS of microsatellites, using individual combinatorial barcoding, is potentially faster and cheaper than current microsatellite approaches and offers better and more data.

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Lasy-Seq: a high-throughput library preparation method for RNA-Seq and its application in the analysis of plant responses to fluctuating temperatures

10.1101/463596 ◽

2018 ◽

Author(s):

Mari Kamitani ◽

Makoto Kashima ◽

Ayumi Tezuka ◽

Atsushi J. Nagano

Keyword(s):

High Throughput ◽

Large Scale ◽

Preparation Method ◽

Low Cost ◽

Cost Effective ◽

Plant Responses ◽

Library Preparation ◽

Rna Seq ◽

Temperature Responses ◽

Library Preparation Method

AbstractRNA-Seq is a whole-transcriptome analysis method used to research biological mechanisms and functions; its use in large-scale experiments is limited by costs and labour. In this study, we established a high-throughput and cost effective RNA-Seq library preparation method that did not require mRNA enrichment. The method adds unique index sequences to samples during reverse transcription (RT) that is conducted at a higher temperature (≥62°C) to suppress RT of A-rich sequences in rRNA, and then pools all samples into a single tube. Both single-read and paired end sequencing of libraries is enabled. We found that the pooled RT products contained large amounts of RNA, mainly rRNA, and caused over-estimations of the quantity of DNA, resulting in unstable tagmentation results. Degradation of RNA before tagmentation was necessary for the stable preparation of libraries. We named this protocol low-cost and easy RNA-Seq (Lasy-Seq), and used it to investigate temperature responses in Arabidopsis thaliana. We analysed how sub-ambient temperatures (10–30°C) affected the plant transcriptomes, using time-courses of RNA-Seq from plants grown in randomly fluctuating temperature conditions. Our results suggest that there are diverse mechanisms behind plant temperature responses at different time scales.

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Enzymatic Synthesis of 15N-L-aspartic Acid Using Recombinant Aspartase from Escherichia Coli K12

Revista de Chimie ◽

10.37358/rc.08.11.2004 ◽

2008 ◽

Vol 59 (11) ◽

Cited By ~ 1

Author(s):

Iulia Lupan ◽

Sergiu Chira ◽

Maria Chiriac ◽

Nicolae Palibroda ◽

Octavian Popescu

Keyword(s):

Amino Acids ◽

Aspartic Acid ◽

Enzymatic Synthesis ◽

Large Scale ◽

Recombinant Dna ◽

Industrial Enzymes ◽

Recombinant Dna Technology ◽

Bacterial Fermentation ◽

Natural Protein ◽

Novel Method

Amino acids are obtained by bacterial fermentation, extraction from natural protein or enzymatic synthesis from specific substrates. With the introduction of recombinant DNA technology, it has become possible to apply more rational approaches to enzymatic synthesis of amino acids. Aspartase (L-aspartate ammonia-lyase) catalyzes the reversible deamination of L-aspartic acid to yield fumaric acid and ammonia. It is one of the most important industrial enzymes used to produce L-aspartic acid on a large scale. Here we described a novel method for [15N] L-aspartic synthesis from fumarate and ammonia (15NH4Cl) using a recombinant aspartase.

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Efficient Schedule of Energy-Constrained UAV Using Crowdsourced Buses in Last-Mile Parcel Delivery

Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies ◽

10.1145/3448079 ◽

2021 ◽

Vol 5 (1) ◽

pp. 1-23

Author(s):

Yan Pan ◽

Shining Li ◽

Qianwu Chen ◽

Nan Zhang ◽

Tao Cheng ◽

...

Keyword(s):

Traffic Congestion ◽

Large Scale ◽

Load Capacity ◽

Scheduling Algorithm ◽

Cost Effective ◽

Promising Alternative ◽

Logistics Industry ◽

Last Mile ◽

Delivery Scheduling ◽

Schedule Approach

Stimulated by the dramatical service demand in the logistics industry, logistics trucks employed in last-mile parcel delivery bring critical public concerns, such as heavy cost burden, traffic congestion and air pollution. Unmanned Aerial Vehicles (UAVs) are a promising alternative tool in last-mile delivery, which is however limited by insufficient flight range and load capacity. This paper presents an innovative energy-limited logistics UAV schedule approach using crowdsourced buses. Specifically, when one UAV delivers a parcel, it first lands on a crowdsourced social bus to parcel destination, gets recharged by the wireless recharger deployed on the bus, and then flies from the bus to the parcel destination. This novel approach not only increases the delivery range and load capacity of battery-limited UAVs, but is also much more cost-effective and environment-friendly than traditional methods. New challenges therefore emerge as the buses with spatiotemporal mobility become the bottleneck during delivery. By landing on buses, an Energy-Neutral Flight Principle and a delivery scheduling algorithm are proposed for the UAVs. Using the Energy-Neutral Flight Principle, each UAV can plan a flying path without depleting energy given buses with uncertain velocities. Besides, the delivery scheduling algorithm optimizes the delivery time and number of delivered parcels given warehouse location, logistics UAVs, parcel locations and buses. Comprehensive evaluations using a large-scale bus dataset demonstrate the superiority of the innovative logistics UAV schedule approach.

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Multi-Country Scale Assessment of Available Energy Recovery Potential Using Micro-Hydropower in Drinking, Pressurised Irrigation and Wastewater Networks, Covering Part of the EU

Water ◽

10.3390/w13070899 ◽

2021 ◽

Vol 13 (7) ◽

pp. 899

Author(s):

Djordje Mitrovic ◽

Miguel Crespo Chacón ◽

Aida Mérida García ◽

Jorge García Morillo ◽

Juan Antonio Rodríguez Diaz ◽

...

Keyword(s):

Drinking Water ◽

Northern Ireland ◽

Energy Recovery ◽

Large Scale ◽

Significant Proportion ◽

Value Added ◽

Cost Effective ◽

Net Energy ◽

Water Networks ◽

Scale Assessment

Studies have shown micro-hydropower (MHP) opportunities for energy recovery and CO2 reductions in the water sector. This paper conducts a large-scale assessment of this potential using a dataset amassed across six EU countries (Ireland, Northern Ireland, Scotland, Wales, Spain, and Portugal) for the drinking water, irrigation, and wastewater sectors. Extrapolating the collected data, the total annual MHP potential was estimated between 482.3 and 821.6 GWh, depending on the assumptions, divided among Ireland (15.5–32.2 GWh), Scotland (17.8–139.7 GWh), Northern Ireland (5.9–8.2 GWh), Wales (10.2–8.1 GWh), Spain (375.3–539.9 GWh), and Portugal (57.6–93.5 GWh) and distributed across the drinking water (43–67%), irrigation (51–30%), and wastewater (6–3%) sectors. The findings demonstrated reductions in energy consumption in water networks between 1.7 and 13.0%. Forty-five percent of the energy estimated from the analysed sites was associated with just 3% of their number, having a power output capacity >15 kW. This demonstrated that a significant proportion of energy could be exploited at a small number of sites, with a valuable contribution to net energy efficiency gains and CO2 emission reductions. This also demonstrates cost-effective, value-added, multi-country benefits to policy makers, establishing the case to incentivise MHP in water networks to help achieve the desired CO2 emissions reductions targets.

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Modeling Fused Filament Fabrication using Artificial Neural Networks

Production Engineering ◽

10.1007/s11740-021-01020-y ◽

2021 ◽

Author(s):

Paul Oehlmann ◽

Paul Osswald ◽

Juan Camilo Blanco ◽

Martin Friedrich ◽

Dominik Rietzel ◽

...

Keyword(s):

Real Time ◽

Large Scale ◽

Cost Effective ◽

Print Quality ◽

Ann Model ◽

Production Environment ◽

Fused Filament Fabrication ◽

Artificial Neural ◽

Using Data ◽

Artificial Neural Network Ann

AbstractWith industries pushing towards digitalized production, adaption to expectations and increasing requirements for modern applications, has brought additive manufacturing (AM) to the forefront of Industry 4.0. In fact, AM is a main accelerator for digital production with its possibilities in structural design, such as topology optimization, production flexibility, customization, product development, to name a few. Fused Filament Fabrication (FFF) is a widespread and practical tool for rapid prototyping that also demonstrates the importance of AM technologies through its accessibility to the general public by creating cost effective desktop solutions. An increasing integration of systems in an intelligent production environment also enables the generation of large-scale data to be used for process monitoring and process control. Deep learning as a form of artificial intelligence (AI) and more specifically, a method of machine learning (ML) is ideal for handling big data. This study uses a trained artificial neural network (ANN) model as a digital shadow to predict the force within the nozzle of an FFF printer using filament speed and nozzle temperatures as input data. After the ANN model was tested using data from a theoretical model it was implemented to predict the behavior using real-time printer data. For this purpose, an FFF printer was equipped with sensors that collect real time printer data during the printing process. The ANN model reflected the kinematics of melting and flow predicted by models currently available for various speeds of printing. The model allows for a deeper understanding of the influencing process parameters which ultimately results in the determination of the optimum combination of process speed and print quality.

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