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Controlling Martensitic Transformation Characteristics in Defect-Free NiTi Shape Memory Alloys Fabricated Using Laser Powder Bed Fusion
Get PDFLaser powder bed fusion is a promising additive manufacturing technique for the fabrication of NiTi shape memory alloy parts with complex geometries that are otherwise difficult to fabricate through traditional processing methods. The technique is particularly attractive for the biomedical applications of NiTi SMAs, such as stents, implants, and dental and surgical devices, where primarily the superelastic effect is exploited. However, few additively manufactured NiTi parts have been reported to exhibit superelasticity under tension in the as-printed condition.
Laser powder bed fusion was utilized to fabricate fully dense, near-equiatomic (Ni������.���Ti������.���), Ni-rich NiTi (Ni������.���Ti������.��� and Ni������.���Ti������.���) shape memory alloy parts which exhibited tensile ductility up to 16%, shape memory strain of 6%, and tensile superelasticity up to 6%, almost twice the maximum reported value in the literature. The selection of optimum processing parameters that yielded fully dense parts was guided by a process optimization framework based on a computationally inexpensive analytical model used to predict the melt pool dimensions based on single-track experiments. This framework allowed for constructing printability maps for the present NiTi shape memory alloys and revealed that fully dense parts could be printed over a wide range of process parameters. By controlling the process parameters, in particular laser power, laser scan speed, and volumetric energy density, in the processing space that result in fully dense parts, it was demonstrated systematically that the composition of the printed parts could be precisely changed by controlling the evaporation of Ni. The flexibility of parameter selection to print defect-free NiTi SMAs and composition control by preferential evaporation of Ni opens the possibility to print functional NiTi parts or devices without post-processing. Crystallographic texture analysis demonstrated that the as-printed NiTi parts had a strong preferential texture for superelasticity, a factor that needs to be carefully considered when complex shaped parts are to be subjected to combined loadings. Transmission electron microscopy investigations revealed the presence of nano-sized oxide particles and Ni-rich precipitates in the as-printed parts of Ni������.���Ti������.��� and Ni������.���Ti������.�����, which play a role in the improved superelasticity by suppressing inelastic accommodation mechanisms for martensitic transformation
A Dataset for Training and Testing Rendering Methods
Get PDFThorough physically-based rendering is a computationally taxing and time-consuming process. High-quality rendering requires a significant amount of memory and time to calculate the trajectories and colors of each ray that goes into a pixel, especially as scenes become more complex and more computations are required for clear renders. Each ray used to calculate the color of a pixel requires a large number of calculations to accurately represent the red-green-blue value, taking into account not only the material of the object the ray hits but the surrounding objects and lighting. In a bid to implement this process, Monte Carlo Rendering was developed as an algorithm to flexibly and realistically render an image from a three dimensional scene. This is a common method of rendering now, but it leaves significant flaws in the image if used to truly speed up the process due to the use of random sampling to determine which rays are created and approximate the pixel values. These flaws appear similar to TV static and are called noise. To keep this faster use of the algorithm while continuing to produce high-quality renders, denoising algorithms were developed to take the noisy images rendered by the Monte Carlo algorithm and scrub the noise to recreate a clean version of the render. To be efficient, these denoising algorithms need to be able to avoid using enough memory and time to fully offset the time saved by the low-sample rendering method. This is very difficult, as the accuracy in a render originally came from careful and thorough calculations for each pixel, and so these algorithms are forced to develop an alternate method to fill in the gaps using the approximations done in the noisy image. As this occurred, denoising algorithms evolved to use increasingly elaborate neural networks to negate issues in accuracy and clarity found in previous methods. These neural networks, though essential to faster and cheaper rendering, require extensive training from currently limited datasets. This research aims to expand the pool of data available to test denoising algorithms on renders created from three dimensional scenes as well as test its effectiveness in training current denoising algorithms in conjunction with the current data. The accuracy of the final tests were measured using the mean square error and the peak signal-to-noise ratio, both commonly utilized to objectively evaluate the difference in the control image and the output of the algorithm. It was found that the new data, when used in combination with the current datasets, was effective in improving the results of these algorithms. This supports the idea that larger, and more importantly more diverse, data with distinct characteristics is beneficial for creating increasingly effective denoising algorithms. This is especially true as renderers become more efficient and methods of expressing sundry real world visual phenomena become more accurate. With those improvements, more robust denoising neural networks will be necessary to create professional appearing renders. An extended dataset will allow for neural networks to be trained as accurately as possible to quickly and accurately create renders that can be used for high importance products, such as frames of final versions of movies for animation studios
From Barriers to Bridgemakers: Building Capacity to Recognize Talent in Black and Brown Students From Urban and Rural School Settings
No full textAfter several decades of documented advocacy for unidentified Black and Brown1 gifted students, their historical exclusion in gifted programming and the opportunity loss that comes with lack of access persists. Despite a push for using local norms rather than national norms for gifted identification to account for contextual differences that might affect achievement such as poverty and teacher quality, as well as utilizing portfolios that showcase student work instead of relying solely on Eurocentric normed assessments, there remains a significant disparity in the identification rates of Black and Brown K-12 students compared to their White peers. This disparity persists even when accounting for proportionality. Consequently, these students often find themselves placed in general education classrooms that fail to address their specific needs, both academically and socio emotionally, placing them at further risk. Because White, middle-class women act as the majority of the gatekeepers for gifted services, scholars have suggested taking teacher referrals out of the identification process or having teachers interrogate their Whiteness in order to eliminate the deficit orientations and biases/prejudice they may harbor against Black and Brown students, thereby increasing identification. However, this type of action addresses a symptom rather than the sickness itself. The purpose of these studies is to systematically interrogate the construct of giftedness, particularly in relationship to Black and Brown students, with a practical aim to help illuminate areas for talent development to exist within teachers, schools, districts, and the wider communities that support them. Using Bronfenbrenner���s ecological systems theory to uncover the micro, meso, exo, and macro level interactions that perpetuate their historical exclusion and lack of access to gifted services, these studies will provide stakeholders with new ways to build capacity for talent development in spaces that before acted as barriers to achievement for Black and Brown students.
1 For the purposes of this work, ���Black and Brown��� refers to African American students and those from a Latinx or Hispanic background
An Index of Salinity and Boron Tolerance of Common Native and Introduced Plant Species in Texas
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Deep Phosphorus Banding in Winter Wheat: A risk management tool for the Southern Great Plains
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Mechanistic Investigation of the Ortho C-H Activation of Pyridine by a (PBP)IR Complex and Synthesis of Novel PAlP Complexes
No full textGroup 13 elements have recently attracted interest as new central donors in ligand pincer scaffolds. As central donors, boron and aluminum have unique properties, such as strong ��-donicity, reversed polarization with metal centers, and Lewis acidity. Our group has previously developed a boron pincer complex capable of acting as a Lewis acidic directing group for ortho-selective C-H activation of pyridine.
In Chapter II, we continued an exploration of this boron pincer complex with a full mechanistic study on the C-H activation of pyridine with supporting DFT calculations. We have determined the rate-limiting step, benzene elimination, generated a Lewis acidic boryl intermediate. Immediate regioselective activation of pyridine by this boryl intermediate demonstrated this intermediate was responsible for the high degree of ortho-selectivity. Activation of pyridine initially formed a cis-isomer that quickly isomerized into the thermodynamically preferred trans-isomer through a pathway that does not involve ligand dissociation from the metal center.
In Chapter III, a substrate scope analysis of this complex indicated N(sp2) sites and electron-poor C-H bonds were preferred for forming stable, major C-H activation that was identifiable. Substrates with alternative Lewis basic sites, such as N(sp3), O, or S, were incapable of utilizing that basic site to stabilize a C-H activated complex via coordination to B. It was determined that viable C-H activation sites neighboring electronegative atoms or atoms with electron-withdrawing substituents were preferred for activation. While substituents on substrates were tolerated, sufficiently bulky substituents prevented the formation of stable, C-H activated products.
In Chapter IV, new aluminum-based pincer scaffolds were designed with a pyrrole-based backbone. These pincer scaffolds were metallated with Ir and Rh to form a series of new (PAlP)M complexes. NMR spectroscopy, X-ray diffraction analysis, and DFT calculations were utilized to characterize these new complexes. With Al-M bonds that are amongst the shortest known for Rh and Ir, these interactions had Al-M interactions that were classified as Z-type. These complexes were observed to interexchange ligands between the Al and M centers