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Ammonia and greenhouse gas emissions from slurry storage : A review
Storage of slurry is an important emission source for ammonia (NH3), nitrous oxide (N2O), methane (CH4), carbon dioxide (CO2) and hydrogen sulfide (H2S) from livestock production. Therefore, this study collected published emission data from stored cattle and pig slurry to determine baseline emission values and emission changes due to slurry treatment and coverage of stores. Emission data were collected from 120 papers yielding 711 records of measurements conducted at farm-, pilot- and laboratory-scale. The emission data reported in a multitude of units were standardized and compiled in a database. Descriptive statistics of the data from untreated slurry stored uncovered revealed a large variability in emissions for all gases. To determine baseline emissions, average values based on a weighting of the emission data according to the season and the duration of the emission measurements were constructed using the data from farm-scale and pilot-scale studies. Baseline emissions for cattle and pig slurry stored uncovered were calculated. When possible, it was further distinguished between storage in tanks without slurry treatment and storage in lagoons which implies solid-liquid separation and biological treatment. The baseline emissions on an area or volume basis are: for NH3: 0.12 g m−2 h-1 and 0.15 g m−2 h-1 for cattle and pig slurry stored in lagoons, and 0.08 g m−2 h-1 and 0.24 g m−2 h-1 for cattle and pig slurry stored in tanks; for N2O: 0.0003 g m−2 h-1 for cattle slurry stored in lagoons, and 0.002 g m−2 h-1 for both slurry types stored in tanks; for CH4: 0.95 g m-3 h-1 and 3.5 g m-3 h-1 for cattle and pig slurry stored in lagoons, and 0.58 g m-3 h-1 and 0.68 g m-3 h-1 for cattle and pig slurry stored in tanks; for CO2: 6.6 g m−2 h-1 and 0.3 g m−2 h-1 for cattle and pig slurry stored in lagoons, and 8.0 g m−2 h-1 for both slurry types stored in tanks; for H2S: 0.04 g m−2 h-1 and 0.01 g m−2 h-1 for cattle and pig slurry stored in lagoons. Related to total ammoniacal nitrogen (TAN), baseline emissions for tanks are 16% and 15% of TAN for cattle and pig slurry, respectively. Emissions of N2O and CH4 relative to nitrogen (N) and volatile solids (VS) are 0.13% of N and 0.10% of N and 2.9% of VS and 4.7% of VS for cattle and pig slurry, respectively. Total greenhouse gas emissions from slurry stores are dominated by CH4. The records on slurry treatment using acidification show a reduction of NH3 and CH4 emissions during storage while an increase occurs for N2O and a minor change for CO2 as compared to untreated slurry. Solid-liquid separation causes higher losses for NH3 and a reduction in CH4, N2O and CO2 emissions. Anaerobically digested slurry shows higher emissions during storage for NH3 while losses tend to be lower for CH4 and little changes occur for N2O and CO2 compared to untreated slurry. All cover types are found to be efficient for emission mitigation of NH3 from stores. The N2O emissions increase in many cases due to coverage. Lower CH4 emissions occur for impermeable covers as compared to uncovered slurry storage while for permeable covers the effect is unclear or emissions tend to increase. Limited and inconsistent data regarding emission changes with covering stores are available for CO2 and H2S. The compiled data provide a basis for improving emission inventories and highlight the need for further research to reduce uncertainty and fill data gaps regarding emissions from slurry storage.
Experimental and numerical characterization of imperfect additively manufactured lattices based on triply periodic minimal surfaces
Lattices based on triply periodic minimal surfaces (TPMS) are attracting increasing interest in seminal industries such as bone tissue engineering due to their excellent structure-property relationships. However, the potential can only be exploited if their structural integrity is ensured. This requires a fundamental understanding of the impact of imperfections that arise during additive manufacturing. Therefore, in the present study, the structure-property relationships of eight TPMS lattices, including their imperfections, are investigated experimentally and numerically. In particular, the focus is on biomimetic network TPMS lattices of the type Schoen I-WP and Gyroid, which are fabricated by laser powder bed fusion from the biocompatible alloy Ti-42Nb. The experimental studies include computed tomography measurements and compression tests. The results highlight the importance of process-related imperfections on the mechanical performance of TPMS lattices. In the numerical work, firstly the as-built morphology is artificially reconstructed before finite element analyses are performed. Here, the reconstruction procedure previously developed by the same authors is used and validated on a larger experimental matrix before more advanced calculations are conducted. Specifically, the reconstruction reduces the numerical overestimation of stiffness from up to 341% to a maximum of 26% and that of yield strength from 66% to 12%. Given a high simulation accuracy and flexibility, the presented procedure can become a key factor in the future design process of TPMS lattices.
Laser powder bed fusion of a superelastic Cu-Al-Mn shape memory alloy
Dense and crack-free specimens of the shape memory alloy Cu71.6Al17Mn11.4 (at.%) were produced via laser powder bed fusion across a wide range of process parameters. The microstructure, viz. grain size, can be directly tailored within the process and with it the transformation temperatures (TTs) shifted to higher values by raising the energy input. The microstructure, and the superelastic behavior of additively manufactured samples were assessed by a detailed comparison with induction melted material. The precipitation of the α phase, which inhibit the martensitic transformation, were not observed in the additively manufactured samples owing to the high intrinsic cooling rates during the fabrication process. Fine columnar grains with a strong [001]-texture along the building direction lead to an enhanced yield strength compared to the coarse-grained cast samples. A maximum recoverable strain of 2.86% was observed after 5% compressive loading. The first results of our approach imply that laser powder bed fusion is a promising technique to directly produce individually designed Cu-Al-Mn shape memory parts with a pronounced superelasticity at room temperature.
Controlled synthesis of mussel-inspired Ag nanoparticle coatings with demonstrated in vitro and in vivo antibacterial properties
The in-situ formation of silver nanoparticles (AgNPs) via dopamine-reduction of Ag+ has been widely utilized for titanium implants to introduce antibacterial properties. In previous studies, the preparation of AgNPs has focused on controlling the feeding concentrations, while the pH of the reaction solution was ignored. Herein, we systematically determined the influence of various pH (4, 7, 10) and Ag+ concentrations (0.01, 0.1 mg/mL) on the AgNPs formation, followed by the evaluation of the antibacterial properties in vitro and in vivo. The results revealed that an alkaline environment was favourable for AgNP formation and resulted in more particles. Although the AgNPs bearing Ti had lower biocompatibilities, it was significantly improved after 7 days of mineralization in simulated body fluid. The outstanding antibacterial property of the AgNPs was well maintained after one day and seven days of implantation. Moreover, 3D micro-CT modelling showed that the pH 10/0.1 group exhibited remarkable osteogenesis, which may be due to their strong antibacterial properties and ability to promote mineralization. Therefore, we have demonstrated that the solution pH was as important as the feeding Ag+ concentration in determining AgNP formation, and it has paved the way for developing various AgNP-loaded surfaces that could meet different antibacterial needs.
The impact of chemical short-range order on the thermophysical properties of medium- and high-entropy alloys
The unusual behavior observed in the coefficient of thermal expansion and specific heat capacity of CrFeNi, CoCrNi, and CoCrFeNi medium/high-entropy alloys is commonly referred to as the K-state effect. It is shown to be independent of the Curie temperature, as demonstrated by temperature-dependent magnetic moment measurements. CoCrFeNi alloy is chosen for detailed characterization; potential reasons for the K-state effect such as texture, recrystallization, and second-phase precipitation are ruled out. An examination of the electronic structure indicates the formation of a pseudo-gap in the Density of States, which suggests a specific chemical interaction between Ni and Cr atoms upon alloying. Hybrid Monte Carlo/Molecular Dynamic (MC/MD) simulations indicate the presence of non-negligible chemical short-range order (CSRO). Local lattice distortions are shown to be negligible, although deviations around Cr and Ni elements from those expected in a fully disordered structure are experimentally observed by X-ray absorption spectroscopy. The determined bonding distances are in good agreement with MC/MD calculations. A mechanism is proposed to explain the anomalies and calorimetric experiments and their results are used to validate the mechanism.
Machine learning for additive manufacturing: Predicting materials characteristics and their uncertainty
Additive manufacturing (AM) is known for versatile fabrication of complex parts, while also allowing the synthesis of materials with desired microstructures and resulting properties. These benefits come at a cost: process control to manufacture parts within given specifications is very challenging due to the relevance of a large number of processing parameters. Efficient predictive machine learning (ML) models trained on small datasets, can minimize this cost. They also allow to assess the quality of the dataset inclusive of uncertainty. This is important in order for additively manufactured parts to meet property specifications not only on average, but also within a given variance or uncertainty. Here, we demonstrate this strategy by developing a heteroscedastic Gaussian process (HGP) model, from a dataset based on laser powder bed fusion of a glass-forming alloy at varying processing parameters. Using amorphicity as the microstructural descriptor, we train the model on our Zr52.5Cu17.9Ni14.6Al10Ti5 (at.%) alloy dataset. The HGP model not only accurately predicts the mean value of amorphicity, but also provides the respective uncertainty. The quantification of the aleatoric and epistemic uncertainty contributions allows to assess intrinsic inaccuracies of the dataset, as well as identify underlying physical phenomena. This HGP model approach enables to systematically improve ML-driven AM processes.
Temperature-dependent dynamic compressive properties and failure mechanisms of the additively manufactured CoCrFeMnNi high entropy alloy
CoCrFeMnNi high entropy alloy (HEA) parts were fabricated by laser powder bed fusion (LPBF), and their dynamic compressive properties at different temperatures as well as the resulting microstructures were analyzed. The HEAs showed an unprecedented strength-ductility combination, especially at a cryogenic temperature of 77 K and a high strain rate of 3000 s−1. Under this testing condition, the yield strength (YS) of the HEAs amounted to 665 MPa. Regardless of the testing temperature, the deformation mechanism of all investigated HEAs was dominated by a synergistic effect consisting of deformation twinning and dislocation pile-up around twins. The fraction of twin boundaries and dislocation density within the deformed microstructure of the HEA correlated with the test temperature. At 77 K, the formation of nanotwins together with dislocation slip prevailed and contributed to pronounced twin-twin and twin-dislocation interactions which effectively restricted the dislocation movement and, hence, contributed to a higher YS as well as strain hardening rate in comparison to that of the HEAs at room temperature of 298 K. The LPBF-fabricated HEAs showed unpronounced thermal softening even at a high testing temperature of 1073 K. Continuous dynamic recrystallization was restricted in the HEA because of its inherent sluggish dislocation kinetics and low stacking fault energy.
A novel approach to fabricate load-bearing Ti6Al4V-Barium titanate piezoelectric bone scaffolds by coupling electron beam melting and field-assisted sintering
A critical-size bone defect in load-bearing areas is a challenging clinical problem in orthopaedic surgery. Titanium alloy (Ti6Al4V) scaffolds have advantages because of their biomechanical stability but lack electrical activity, which hinders their further use. This work is focused on the fabrication of Ti6Al4V-Barium Titanate (BaTiO3) bulk composite scaffolds to combine the biomechanical stability of Ti6Al4V with electrical activity through BaTiO3. For the first time, a hollow cylindrical Ti6Al4V is additively manufactured by electron beam melting and combined with piezoelectric BaTiO3 powder for joint processing in field-assisted sintering. Scanning electron microscope images on the interface of the Ti6Al4V-BaTiO3 composite scaffold showed that after sintering, the Ti6Al4V lattice structure bounded with BaTiO3 matrix without its major deformation. The Ti6Al4V-BaTiO3 scaffold had average piezoelectric constants of (0.63 ± 0.12) pC/N directly after sintering due to partial dipole alignment of the BaTiO3 tetragonal phase, which increased to (4.92 ± 0.75) pC/N after a successful corona poling. Moreover, the nanoindentation values of Ti6Al4V exhibited an average hardness and Young's modulus of (5.9 ± 0.9) GPa and (130 ± 14) GPa, and BaTiO3 showed (4.0 ± 0.6) GPa and (106 ± 10) GPa, respectively. It reveals that the Ti6Al4V is the harder and stiffer part in the Ti6Al4V-BaTiO3 composite scaffold. Such a scaffold has the potential to treat critical-size bone defects in load-bearing areas and guide tissue regeneration by physical stimulation.
Thermal annealing to influence the vapor sensing behavior of co-continuous poly(lactic acid)/polystyrene/multiwalled carbon nanotube composites
With the main purpose of being used as vapor leakage detector, the volatile organic compound (VOC) vapor sensing properties of conductive polymer blend composites were studied. Poly(lactic acid)/polystyrene/multi-walled carbon nanotube (PLA/PS/MWCNT) based conductive polymer composites (CPCs) in which the polymer components exhibit different interactions with the vapors, were prepared by melt mixing. CPCs with a blend composition of 50/50 wt% resulted in the finest co-continuous structure and selective MWCNT localization in PLA. Therefore, these composites were selected for sensor tests. Thermal annealing was applied aiming to maintain the blend structure but improving the sensing reversibility of CPC sensors towards high vapor concentrations. Different sensing protocols were applied using acetone (good solvent for PS and PLA) and cyclohexane (good solvent for PS but poor solvent for PLA) vapors. Increasing acetone vapor concentration resulted in increased relative resistance change (Rrel) of CPCs. Saturated cyclohexane vapor resulted in lower response than nearly saturated acetone vapor. The thermal annealing at 150 °C did not change the blend morphology but increased the PLA crystallinity, making the CPC sensors more resistant to vapor stimulation, resulting in lower Rrel but better reversibility after vapor exposure.
Transparent model concrete with tunable rheology for investigating flow and particle-migration during transport in pipes
The article describes the adaption and properties of a model concrete for detailed flow studies. To adapt the yield stress and plastic viscosity of the model concrete to the corresponding rheological properties of real concrete, the model concrete is made of a mixture of glass beads and a non-Newtonian fluid. The refractive index of the non-Newtonian fluid is adjusted to the refractive index of the glass beads by the addition of a further constituent. The rheological properties of the model concrete are characterised by measurements in concrete rheometers. Finally, the first exemplary results from experiments with the model concrete are presented, which give incipient impressions of the complex internal dynamics in flowing concrete.