Precipitation during intrinsic heat treatment in laser additive manufacturing

Laser additive manufacturing (LAM) involves layer-by-layer production of components based on a computer-aided design file (CAD) by repetitive melting of metallic powder with a focused laser beam. The inherent geometrical freedom of this technique enables the production of complex and highly customized components. However, post-processing, including heat treatment, of these components remains critical with problems associated with cracking or non-uniform quenching. The layer-by-layer manufacturing process results in a peak-like time-temperature profile experienced during LAM. This intrinsic heat treatment (IHT) can trigger precipitation reactions in certain alloys. There is potential in exploiting IHT to achieve desired microstructure and mechanical properties, hence, removing the need for post-process heat treatment. This in-process heat treatment approach would be similar to current industrial practices, for example, thermomechanical treatment. Utilization of IHT to achieve desired microstructures and mechanical properties requires a fundamental understanding of the precipitation progress during IHT and development of adapted alloys and process parameters. This work aims at identifying important features of the IHT and develop a fundamental understanding of how these affect the precipitation progress. Simple, model Al-Sc alloys were selected for this study based on the fast precipitation kinetics and availability of CALPHAD databases. Use of high purity (>99 wt.%) Al alloys presented the first challenge in this work, as high conductivity metals are considered difficult to process in LAM. A predictive process parameters optimization routine was developed using analytical models to predict the melt pool depth and statistical design of experiments techniques. The predictive approach was further expanded for use in in-situ alloying during LAM using mixtures of elemental powders. After suitable process parameters for processing of the model alloys were identified, thin-walled structures were made by depositing single tracks on top of one another using directed energy deposition (DED), a type of LAM technique. Manufacturing of thin-walled samples allowed achieving different cooling rates within a single sample. Si, which has a three-fold effect in promoting precipitation: higher driving force, lower interface energy, and higher diffusivity, was used to trigger IHT induced precipitation in the model Al-Sc alloys. Process parameters were modified to be able to reach ~90% of the peak hardness for the model alloy without the need for any post-process ageing treatment. Additional samples were produced using laser powder bed fusion (LPBF), another LAM technique. Higher cooling rates are achieved during LPBF as compared to DED, preventing any IHT induced precipitation during LPBF processing. The samples were isothermally heat-treated at different temperatures and the precipitation progress was experimentally measured using in-situ small-angle X-ray scattering (SAXS) and ex-situ atom probe tomography (APT). The experimental measurements were used to develop a Kampmann-Wagner based precipitate model. Application of the precipitation model to peak-like time-temperature profiles gave important insights on the effect of various aspects of IHT on the in-process precipitation progress during LAM processing. This thesis shows the tremendous potential of using IHT during LAM processes as a replacement for post-process ageing heat treatments and presents the alloy and process design approaches which can be used to advance the precipitation progress during IHT

On strong-scaling and open-source tools for analyzing atom probe tomography data

The development of strong-scaling computational tools for high-throughput methods with an open-source code and transparent metadata standards has successfully transformed many computational materials science communities. While such tools are mature already in the condensed-matter physics community, the situation is still very different for many experimentalists. Atom probe tomography (APT) is one example. This microscopy and microanalysis technique has matured into a versatile nano-analytical characterization tool with applications that range from materials science to geology and possibly beyond. Here, data science tools are required for extracting chemo-structural spatial correlations from the reconstructed point cloud. For APT and other high-end analysis techniques, post-processing is mostly executed with proprietary software tools, which are opaque in their execution and have often limited performance. Software development by members of the scientific community has improved the situation but compared to the sophistication in the field of computational materials science several gaps remain. This is particularly the case for open-source tools that support scientific computing hardware, tools which enable high-throughput workflows, and open well-documented metadata standards to align experimental research better with the fair data stewardship principles. To this end, we introduce paraprobe, an open-source tool for scientific computing and high-throughput studying of point cloud data, here exemplified with APT. We show how to quantify uncertainties while applying several computational geometry, spatial statistics, and clustering tasks for post-processing APT datasets as large as two billion ions. These tools work well in concert with Python and HDF5 to enable several orders of magnitude performance gain, automation, and reproducibility

Designing an Fe-Ni-Ti maraging steel tailor-made for laser additive manufacturing

Laser additive manufacturing (LAM) offers high flexibility in the production of customized and geometrically complex parts. The technique receives great interest from industry and academia but faces substantial challenges regarding processability and insufficient mechanical properties of LAM-produced material. One reason is that currently mainly conventional alloys are being used in LAM, which were developed for different processes such as casting. Since these alloys are not optimized for the specific process conditions encountered in LAM such as fast cooling and cyclic re-heating, they cannot be expected to perform ideally in such processes regarding processability and resulting mechanical properties. Here we present the development of a new, simple ternary Fe-Ni-Ti maraging-type alloy tailor-made for LAM. We used compositionally graded samples to screen Ti compositions from 0 to 21 at. % and efficiently identify promising microstructures and mechanical properties. Under LAM solidification conditions the desired mainly martensitic microstructure needed for a maraging steel formed at Ti compositions ranging from 0 to 7 at. %. Within this composition range, the intended microstructure is formed and additionally some unique process conditions of LAM such as cyclic re-heating can be exploited. Specifically, in-situ phase transformations can be controlled during LAM, via the thermal history. At higher Ti compositions two different eutectic microstructures with different primary phases were found that show a high hardness of up to 700 HV

Tethering of Chemotherapeutic Drug/Imaging Agent to Bile Acid-Phospholipid Increases the Efficacy and Bioavailability with Reduced Hepatotoxicity

Weakly basic drugs display poor solubility and tend to precipitate in the stomach’s acidic environment causing reduced oral bioavailability. Tracing of these orally delivered therapeutic agents using molecular probes is challenged due to their poor absorption in the gastrointestinal tract (GIT). Therefore, we designed a gastric pH stable bile acid derived amphiphile where Tamoxifen (as a model anticancer drug) is conjugated to lithocholic acid derived phospholipid (LCA-Tam-PC). <i>In vitro</i> studies suggested the selective nature of LCA-Tam-PC for cancer cells over normal cells as compared to the parent drug. Fluorescent labeled version of the conjugate (LCA-Tam-NBD-PC) displayed an increased intracellular uptake compared to Tamoxifen. We then investigated the antitumor potential, toxicity, and median survival in 4T1 tumor bearing BALB/c mice upon LCA-Tam-PC treatment. Our studies confirmed a significant reduction in the tumor volume, tumor weight, and reduced hepatotoxicity with a significant increase in median survival on LCA-Tam-PC treatment as compared to the parent drug. Pharmacokinetic and biodistribution studies using LCA-Tam-NBD-PC witnessed the enhanced gut absorption, blood circulation, and tumor site accumulation of phospholipid–drug conjugate leading to improved antitumor activity. Therefore, our studies revealed that conjugation of chemotherapeutic/imaging agents to bile acid phospholipid can provide a new platform for oral delivery and tracing of chemotherapeutic drugs