Simulation of Microstructural Evolution of Selective Laser Melting of Metal Powders

Selective Laser Melting (SLM) is an Additive Manufacturing (AM) process used to create 3D objects by laser melting pre-deposited powdered feedstock. During SLM, powdered material is fused layer upon layer, the scanning laser melts regions of the powder bed that corresponds to the geometry of the final component. During SLM the component undergoes rapid temperature cycles and steep temperature gradients. These processing conditions generate a specific microstructure for SLM components. Understanding the mechanism by which these generated microstructures evolve can assist in controlling and optimising the process. The present research develops a two dimensional Cellular Automata – Finite Element (CA-FE) coupled model in order to predict the microstructure formed during the melting process of a powdered AA-2024 feedstock using the AM process SLM. The presented CA model is coupled with a detailed thermal FE model which computes the heat flow characteristics of the SLM process. The developed model takes into account the powder-to-liquid-to-solid transformation, tracks the interaction between several melt pools within a melted track, and several tracks within various layers. It was found that the simulated temperature profiles as well as the predicted microstructures bared a close resemblance with manufactured AA-2024 SLM samples. The developed model predicts the final microstructure obtained from components manufactured via SLM, as well as is capable of predicting melt pool cooling and solidification rates, the type of microstructure obtained, the size of the melt pool and heat affected zone, level of porosity and the growth competition present in microstructures of components manufactured via SLM. The developed models are an important part in understanding the SLM process, and can be used as a tool to further improve consistency of part properties and further enhance their properties

Investigation into the material properties of wooden composite structures with in-situ fibre reinforcement using additive manufacturing

In contrast to subtractive manufacturing techniques, additive manufacturing processes are known for their high efficiency in regards to utilisation of feedstock. However the various polymer, metallic and composite feedstocks used within additive manufacturing are mainly derived from energy consuming, inefficient methods, often originating from non-sustainable sources. This work explores the mechanical properties of additively manufactured composite structures fabricated from recycled sustainable wood waste with the aim of enhancing mechanical properties through glass fibre reinforcement. In the first instance, samples were formed by pouring formulation of wood waste (wood flour) and thermosetting binder (urea formaldehyde), with and without glass fibres, into a mould. The same formulations were used to additively manufacture samples via a layered deposition technique. Samples manufactured using each technique were cured and subsequently tested for their mechanical properties. Additively manufactured samples had superior mechanical properties, with up to 73% increase in tensile strength compared to moulded composites due to a densification of feedstock/paste and fibre in-situ directional alignment

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Correlation of Energy Density and Manufacturing Variables of AA6061 through Laser Powder Bed Fusion and Its Effect on the Densification Mechanism

Aluminum alloy processing via additive manufacturing (AM) technologies has increased in usage during the last decade. AM now enables manufacturing complex geometries not previously achieved through traditional manufacturing. Aluminum is usually processed using laser powder bed fusion (LPBF) technologies, which are used to manufacture metallic components of high geometrical complexity and dimensional accuracy and good mechanical, electrical, and chemical properties, which is why this technology is quite popular at industrial levels. To further develop quality control systems and new aluminum alloys using LPBF, there is a need to establish a predictive relationship between the parameters of the material. A study was carried out to investigate the relationship between energy density and process parameters such as laser power, scan speed, hatch spacing, scan pattern, and laser focus and its influence on the densification mechanism in additively manufactured components with aluminum alloys. AA6061 was selected due to its wide usage in different industries, given its low density and high mechanical performance. Relative density was analyzed using the Archimedes principle, and the quality and morphology of the AA6061 powder were analyzed through metallographic analysis. The process parameter selection was performed according to the best results obtained according to the laser power and energy density factors. The best manufactured samples had an energy density between 30 and 40 J/mm3, with relative densities above 99%

Corrosion Resistance Measurement of 316L Stainless Steel Manufactured by Selective Laser Melting

Selective laser melting (SLM) technology is ushering in a new era of advanced industrial production of metal components. It is of great importance to understand the relationship between the surface features and electrochemical properties of manufactured parts. This work studied the influence of surface orientation on the corrosion resistance of 316L stainless-steel (SS) components manufactured with SLM. The corrosion resistance of the samples was measured using linear polarization resistance (LPR) and electromechanical noise (EN) techniques under three different environments, H2O, 3.5 wt.% NaCl, and 20% H2SO4, analyzing the horizontal (XY) and vertical (XZ) planes. The microstructure and morphology of the samples were obtained by optical (OM) and scanning electron microscopy (SEM). The obtained microstructure showed the grains growing up from the fusion line to the melt pool center and, via SEM-EDS, the presence of irregular and spherical pores was observed. The highest corrosion rate was identified in the H2SO4 solution in the XZ plane with 2.4 × 10−2 mm/year and the XY plane with 1.31 × 10−3 mm/year. The EN technique along with the skewness factor were used to determine the type of corrosion that the material developed. Localized corrosion was observed in the NaCl electrolyte, for the XY and XZ planes (−1.65 and −0.012 skewness factors, respectively), attacking mainly the subgrains of the microstructure and, in some cases, the pores, caused by Cl ions. H2O and H2SO4 solutions presented a uniform corrosion mechanism for the two observed orientations. The morphology identified by SEM was correlated with the results obtained from the electrochemical techniques

Mechanical Properties of AISI 316L Lattice Structures via Laser Powder Bed Fusion as a Function of Unit Cell Features

The growth of additive manufacturing processes has enabled the production of complex and smart structures. These fabrication techniques have led research efforts to focus on the application of cellular materials, which are known for their thermal and mechanical benefits. Herein, we studied the mechanical behavior of stainless-steel (AISI 316L) lattice structures both experimentally and computationally. The lattice architectures were body-centered cubic, hexagonal vertex centroid, and tetrahedron in two cell sizes and at two different rotation angles. A preliminary computational study assessed the deformation behavior of porous cylindrical samples under compression. After the simulation results, selected samples were manufactured via laser powder bed fusion. The results showed the effects of the pore architecture, unit cell size, and orientation on the reduction in the mechanical properties. The relative densities between 23% and 69% showed a decrease in the bulk material stiffness up to 93%. Furthermore, the different rotation angles resulted in a similar porosity level but different stiffnesses. The simulation analysis and experimental results indicate that the variation in the strut position with respect to the force affected the deformation mechanism. The tetrahedron unit cell showed the smallest variation in the elastic modulus and off-axis displacements due to the cell orientation. This study collected computational and experimental data for tuning the mechanical properties of lattice structures by changing the geometry, size, and orientation of the unit cell

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease