AM Bench 2022 Macroscale Tensile Challenge at Different Orientations (CHAL-AMB2022-04-MaTTO) and Summary of Predictions.

The additive manufacturing benchmarking challenge described in this work was aimed at the prediction of average stress-strain properties for tensile specimens that were excised from blocks of non-heat-treated IN625 manufactured by laser powder bed fusion. Two different laser scan strategies were considered: an X-only raster and an XY raster, which involved a 90° rotation in the scan direction between subsequent layers. To measure anisotropy, multiple tensile orientations with respect to the build direction were investigated (e.g., parallel, perpendicular, and intervals in between). Benchmark participants were provided grain structure information via electron backscatter diffraction measurements, as well as the stress-strain response for tensile specimens manufactured parallel to the build direction and produced by the XY scan strategy. Then, participants were asked to predict tensile properties, like the ultimate tensile strength, for the remaining specimens and orientations. Interestingly, the measured mechanical properties did not vary linearly as a function of tensile orientation. Moreover, specimens manufactured with the XY scan strategy exhibited greater yield strength than those corresponding to the X-only scan strategy, regardless of orientation. The benchmark data has been made publicly available for anyone that is interested [1]. For the modeling aspect of the challenge, five teams participated in this benchmark. While most of the models incorporated a crystal plasticity framework, one team chose to use a more semi-empirical approach, and to great success. However, no team excelled at all the predictions, and all teams were seemingly challenged with the predictions associated with the X-only scan strategy.

Rural Research Network to engage rural and minority community members in translational research.

Background: To address the high prevalence of health disparities and lack of research opportunities among rural and minority communities, the University of Arkansas for Medical Sciences (UAMS) developed the Rural Research Network in January 2020. Aim: The aim of this report is to describe our process and progress in developing a rural research network. The Rural Research Network provides a platform to expand research participation opportunities to rural Arkansans, many of whom are older adults, low-income individuals, and underrepresented minority populations. Methods: The Rural Research Network leverages existing UAMS Regional Programs family medicine residency clinics within an academic medical center. Results: Since the inception of the Rural Research Network, research infrastructure and processes have been built within the regional sites. Twelve diverse studies have been implemented with recruitment and data collection from 9248 participants, and 32 manuscripts have been published with residents and faculty from the regional sites. Most studies were able to recruit Black/African American participants at or above a representative sample. Conclusions: As the Rural Research Network matures, the types of research will expand in parallel with the health priorities of Arkansas. Relevance to Patients: The Rural Research Network demonstrates how Cancer Institutes and sites funded by a Clinical and Translational Science Award can collaborate to expand research capacity and increase opportunities for research among rural and minority communities.

Assessing the influence of non-uniform gas speed on the melt pool depth in laser powder bed fusion additive manufacturing.

Purpose: This paper aims to investigate the influence of non-uniform gas speed across the build area on the melt pool depth during laser powder bed fusion. The study focuses on whether a non-uniform gas speed is a source of process variation within an individual build. Design/methodology/approach: Parts with many single-track laser scans were printed and characterized in different locations across the build area coupled with corresponding gas speed profile measurements. Cross-sectional melt pool depth, width, and area are compared against build location/gas speed profiles, scan direction, and laser scan speed. Findings: The study shows that the melt pool depth of single-track laser scans produced on parts are highly variable. Despite this, trends were found showing a reduction in melt pool depth for slow laser scan speeds on the build platform near the inlet nozzle and when the laser scans are parallel to the gas flow direction. Originality/value: A unique dataset of single-track laser scan cross-sectional melt pool measurements and gas speed measurements was generated to assess process variation associated with non-uniform gas speed. Additionally, a novel sample design was used to increase the number of single-track tests per part, which is widely applicable to studying process variation across the build area.

Additive Manufacturing Benchmark 2022 Subcontinuum Mesoscale Tensile Challenge (CHAL-AMB2022-04-MeTT) and Summary of Predictions.

This additive manufacturing benchmarking challenge asked the modelling community to predict the stress-strain behavior and fracture location and pathway of an individual meso-scale (gauge dimensions of approximately 200 µm thickness, 200 µm width, 1mm length) tension specimen that was excised from a wafer of nickel allow IN625 manufactured by laser powder bed fusion (L-PBF). The data used for the challenge questions and answers are provided in a public dataset (https://data.nist.gov/od/id/mds2-2587). Testing models against the data is still possible, although a good-faith blinded prediction should be attempted before reading this article, as the results are contained herein. The uniaxial tension test was pin loaded, conducted at quasi-static strain rates under displacement control, and strain was measured via non-contact methods (digital image correlation). The predictions are challenging since the number of grains contained in the thickness of the specimen are sub-continuum. In addition, pores can be heterogeneously distributed by the L-PBF process, as opposed to intentionally seeded defects. The challenge provided information on chemical composition, grain and subgrain structure (surface-based measurements via electron backscatter diffraction and scanning electron microscopy) and pore structure (volume-based measurements via X-Ray computed tomography) along the entire gauge length for the tension specimen. During the challenge, prediction responses were collected from six different groups. Prediction accuracy compared to the measurements varied, with elastic modulus and strain at ultimate tensile strength consistently over-predicted, while most other values were a mix of over- and under-predicted. Overall, no one model performed best at all predictions. Failure-related properties proved quite challenging to predict, likely in part due to the data provided as well as the inherent difficulty in predicting fracture. Future directions and areas of improvement are discussed in the context of improving model maturity and measurement uncertainty.

Mathematical Modeling Finds Disparate Interferon Production Rates Drive Strain-Specific Immunodynamics during Deadly Influenza Infection.

The timing and magnitude of the immune response (i.e., the immunodynamics) associated with the early innate immune response to viral infection display distinct trends across influenza A virus subtypes in vivo. Evidence shows that the timing of the type-I interferon response and the overall magnitude of immune cell infiltration are both correlated with more severe outcomes. However, the mechanisms driving the distinct immunodynamics between infections of different virus strains (strain-specific immunodynamics) remain unclear. Here, computational modeling and strain-specific immunologic data are used to identify the immune interactions that differ in mice infected with low-pathogenic H1N1 or high-pathogenic H5N1 influenza viruses. Computational exploration of free parameters between strains suggests that the production rate of interferon is the major driver of strain-specific immune responses observed in vivo, and points towards the relationship between the viral load and lung epithelial interferon production as the main source of variance between infection outcomes. A greater understanding of the contributors to strain-specific immunodynamics can be utilized in future efforts aimed at treatment development to improve clinical outcomes of high-pathogenic viral strains.

Laser spot size and scaling laws for laser beam additive manufacturing.

Laser powder bed fusion (L-PBF) additive manufacturing (AM) requires the careful selection of laser process parameters for each feedstock material and machine, which is a laborious process. Scaling laws based on the laser power, speed, and spot size; melt pool geometry; and thermophysical properties can potentially reduce this effort by transferring knowledge from one material and/or laser system to another. Laser spot size is one critical parameter that is less well studied for scaling laws compared to laser power and scan speed. Consequently, single track laser scans were generated with a spot size (D4σ) range of 50 µm to 322 µm and melt pool aspect ratio (depth over spot radius) range from 0.1 to 7.0. These were characterized by in-situ thermography, cross-sectioning, and optical microscopy. Scaling laws from literature were applied and evaluated based on melt pool depth predictions. Scaling laws that contain a minimum of three dimensionless parameters and account for changing absorption between conduction and keyhole mode provide the most accurate melt pool depth predictions (< 35 % difference from experiments), which is comparable to thermal simulation results from literature for a select number of cases.

Multicellular spatial model of RNA virus replication and interferon responses reveals factors controlling plaque growth dynamics.

Respiratory viruses present major public health challenges, as evidenced by the 1918 Spanish Flu, the 1957 H2N2, 1968 H3N2, and 2009 H1N1 influenza pandemics, and the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Severe RNA virus respiratory infections often correlate with high viral load and excessive inflammation. Understanding the dynamics of the innate immune response and its manifestations at the cell and tissue levels is vital to understanding the mechanisms of immunopathology and to developing strain-independent treatments. Here, we present a novel spatialized multicellular computational model of RNA virus infection and the type-I interferon-mediated antiviral response that it induces within lung epithelial cells. The model is built using the CompuCell3D multicellular simulation environment and is parameterized using data from influenza virus-infected cell cultures. Consistent with experimental observations, it exhibits either linear radial growth of viral plaques or arrested plaque growth depending on the local concentration of type I interferons. The model suggests that modifying the activity of signaling molecules in the JAK/STAT pathway or altering the ratio of the diffusion lengths of interferon and virus in the cell culture could lead to plaque growth arrest. The dependence of plaque growth arrest on diffusion lengths highlights the importance of developing validated spatial models of cytokine signaling and the need for in vitro measurement of these diffusion coefficients. Sensitivity analyses under conditions leading to continuous or arrested plaque growth found that plaque growth is more sensitive to variations of most parameters and more likely to have identifiable model parameters when conditions lead to plaque arrest. This result suggests that cytokine assay measurements may be most informative under conditions leading to arrested plaque growth. The model is easy to extend to include SARS-CoV-2-specific mechanisms or to use as a component in models linking epithelial cell signaling to systemic immune models.

The effects of particle size distribution on the rheological properties of the powder and the mechanical properties of additively manufactured 17-4 PH stainless steel.

It is well known that changes in the starting powder can have a significant impact on the laser powder bed fusion process and subsequent part performance. Relationships between the powder particle size distribution and powder performance such as flowability and spreadability are generally known; however, links to part performance are not fully established. This study attempts to more precisely isolate the effect of particle size by using three customized batches of 17-4 PH stainless steel powders with small shifts in particle size distributions having non-intersecting cumulative size distributions, designated as Fine, Medium, and Coarse. It is found that the Fine powder has the worst overall powder performance with poor flow and raking during spreading while the Coarse powder has the best overall flow. Despite these differences in powder performance, the microstructures (i.e., porosity, grain size, phase, and crystallographic texture) of the built parts using the same process parameters are largely the same. Furthermore, the Medium powder produced parts with the highest mechanical properties (i.e., hardness and tensile strength) while the Fine and Coarse powders produced parts with effectively identical mechanical properties. Parts with good static mechanical properties can be produced from powders with a wide range of powder performance.

Iterative community-driven development of a SARS-CoV-2 tissue simulator.

The 2019 novel coronavirus, SARS-CoV-2, is a pathogen of critical significance to international public health. Knowledge of the interplay between molecular-scale virus-receptor interactions, single-cell viral replication, intracellular-scale viral transport, and emergent tissue-scale viral propagation is limited. Moreover, little is known about immune system-virus-tissue interactions and how these can result in low-level (asymptomatic) infections in some cases and acute respiratory distress syndrome (ARDS) in others, particularly with respect to presentation in different age groups or pre-existing inflammatory risk factors. Given the nonlinear interactions within and among each of these processes, multiscale simulation models can shed light on the emergent dynamics that lead to divergent outcomes, identify actionable "choke points" for pharmacologic interventions, screen potential therapies, and identify potential biomarkers that differentiate patient outcomes. Given the complexity of the problem and the acute need for an actionable model to guide therapy discovery and optimization, we introduce and iteratively refine a prototype of a multiscale model of SARS-CoV-2 dynamics in lung tissue. The first prototype model was built and shared internationally as open source code and an online interactive model in under 12 hours, and community domain expertise is driving regular refinements. In a sustained community effort, this consortium is integrating data and expertise across virology, immunology, mathematical biology, quantitative systems physiology, cloud and high performance computing, and other domains to accelerate our response to this critical threat to international health. More broadly, this effort is creating a reusable, modular framework for studying viral replication and immune response in tissues, which can also potentially be adapted to related problems in immunology and immunotherapy.

Demonstration of a laser powder bed fusion combinatorial sample for high-throughput microstructure and indentation characterization.

High-throughput experiments that use combinatorial samples with rapid measurements can be used to provide process-structure-property information at reduced time, cost, and effort. Developing these tools and methods is essential in additive manufacturing where new process-structure-property information is required on a frequent basis as advances are made in feedstock materials, additive machines, and post-processing. Here we demonstrate the design and use of combinatorial samples produced on a commercial laser powder bed fusion system to study 60 distinct process conditions of nickel superalloy 625: five laser powers and four laser scan speeds in three different conditions. Combinatorial samples were characterized using optical and electron microscopy, x-ray diffraction, and indentation to estimate the porosity, grain size, crystallographic texture, secondary phase precipitation, and hardness. Indentation and porosity results were compared against a regular sample. The smaller-sized regions (3 mm × 4 mm) in the combinatorial sample have a lower hardness compared to a larger regular sample (20 mm × 20 mm) with similar porosity (< 0.03 %). Despite this difference, meaningful trends were identified with the combinatorial sample for grain size, crystallographic texture, and porosity versus laser power and scan speed as well as trends with hardness versus stress-relief condition.

Measurements of melt pool geometry and cooling rates of individual laser traces on IN625 bare plates.

The complex physical nature of the laser powder bed fusion (LPBF) process warrants use of multiphysics computational simulations to predict or design optimal operating parameters or resultant part qualities such as microstructure or defect concentration. Many of these simulations rely on tuning based on characteristics of the laser-induced melt pool, such as the melt pool geometry (length, width, and depth). Additionally, many of numerous interacting variables that make LPBF process so complex can be reduced and controlled by performing simple, single track experiments on bare (no powder) substrates, yet still produce important and applicable physical results. The 2018 Additive Manufacturing Benchmark (AM Bench) tests and measurements were designed for this application. This paper describes the experiment design for the tests conducted using LPBF on bare metal surfaces, and the measurement results for the melt pool geometry and melt pool cooling rate performed on two LPBF systems. Several factors, such as accurate laser spot size, were determined after the 2018 AM Bench conference, with results of those additional tests reported here.

Probing nanoscale damage gradients in ion-irradiated metals using spherical nanoindentation.

We discuss and demonstrate the application of recently developed spherical nanoindentation stress-strain protocols in characterizing the mechanical behavior of tungsten polycrystalline samples with ion-irradiated surfaces. It is demonstrated that a simple variation of the indenter size (radius) can provide valuable insights into heterogeneous characteristics of the radiation-induced-damage zone. We have also studied the effect of irradiation for the different grain orientations in the same sample.

High throughput exploration of process-property linkages in Al-6061 using instrumented spherical microindentation and microstructurally graded samples.

Recent spherical nanoindentation protocols have proven robust at capturing the local elastic-plastic response of polycrystalline metal samples at length scales much smaller than the grain size. In this work, we extend these protocols to length scales that include multiple grains to recover microindentation stress-strain curves. These new protocols are first established in this paper and then demonstrated for Al-6061 by comparing the measured indentation stress-strain curves with the corresponding measurements from uniaxial tension tests. More specifically, the scaling factors between the uniaxial yield strength and the indentation yield strength was determined to be about 1.9, which is significantly lower than the value of 2.8 used commonly in literature. The reasons for this difference are discussed. Second, the benefits of these new protocols in facilitating high throughput exploration of process-property relationships are demonstrated through a simple case study.