Other Materials Science and Engineering Commons^™

Cyclic Thermal Stability Of Native Oxide Solar Thermal Absorbers On Femnnialcr High Entropy Alloys For Energy Applications, Xiaoxue Gao

Dartmouth College Ph.D Dissertations

High entropy alloys (HEAs) are promising candidates for cost-effective high-temperature materials in high-efficiency power cycles. A potential application is in concentrated solar power (CSP) systems, where native oxides of cost-effective FeMnNiAlCr HEAs can also synergistically serve as a high-efficiency solar thermal absorber. However, the huge and repetitive temperature change of the CSP system in day-night cycles greatly challenges its thermal stability. In this thesis, we investigated the cyclic oxidation behavior of FeMnNiAlCr HEAs to improve the optical performance and thermal stability of their native oxides as a solar absorber for next-generation CSP systems. We found that the duplex oxide scale …

Development Of Machine Learning-Based Tool For Prediction Of Long-Term Field Performance Of Asphalt Concrete Overlays In A Hot And Humid Climate, Elise Mansour

LSU Doctoral Dissertations

The performance of pavement plays a critical role in Maintenance, Rehabilitation and Reconstruction (MR&R) for highway agencies. Reliable and accurate estimation of pavement performance can be instrumental in prioritization of the limited resources and funding for highway agencies. The latter requires robust prediction models that can handle large-scale, real-world data and can forecast pavement performance in the long run. Unfortunately, the traditional performance prediction models have raised concerns regarding their efficiency and accuracy. It is because these models were based on a limited number of explanatory variables, were not up-to-date and were designed for forecasting short-term (up to five years) …

Biofabrication Of Tissue Constructs Using Protein-In-Polysaccharide Bioinks For Muscle Regeneration, Harshavardhan B

Theses and Dissertations

Myocardial infarction (MI) and volumetric muscle loss (VML) are debilitating conditions that severely affect patient quality of life and challenge healthcare systems, particularly in diagnosis and treatment. Conventional therapies often result in long recovery periods with limited functional restoration. Advances in regenerative medicine, especially extrusion-based 3D bioprinting, offer promising potential to improve the regeneration of complex tissues by precisely depositing cells and biomaterials layer-by-layer to create tailored tissue constructs.

A critical challenge in muscle tissue regeneration is developing protein-polysaccharide bioinks that closely mimic the native muscle tissue microenvironment. In this study, two protein-inpolysaccharide bioinks (alginate-fibrinogen and methylcellulose-gelatin-alginate) were developed to …

Synergistic Approaches For Microstructural Refinement, Enhanced Mechanical And Wear Behaviour In Additively Manufactured 17-4 Ph Stainless Steel, Pradeep Kumar S

Theses and Dissertations

The surface and microstructural characteristics of additively manufactured parts play a significant role under mechanical loading. Due to its high strength, tailorable mechanical properties by heat treatment, and ease of printability, the 17-4 precipitation hardened (PH) stainless steel is gaining attention in the additive manufacturing (AM) field.

Selective Laser Melting (SLM), one of the laser-based powder bed fusion (L-PBF) processes, is capable of making fully dense metallic parts with high geometrical fidelity and greater design flexibility at high resolution. The main factors limiting the adoption of SLM are poor surface roughness, anisotropic microstructure, and the formation of micro-pores in the …

Solubility Characterization Of Organic Molecules For Aqueous Organic Redox Flow Batteries, Anthony W. Ferrell, Harkeerith K. Vij, Seamus D. Jones

College of Engineering Summer Undergraduate Research Program

The major obstacle to renewable energy sources is a lack of long-term energy storage capabilities. Energy produced during the day dissipates, leaving insufficient electricity for at night. The goal of the project is to design an Aqueous Organic Redox Flow Battery (AORFB) to act as long-term energy storage. Work has been done using machine learning to identify suitable compounds for the batteries. In this work there was no indication as to the aqueous solubility of the molecules; this controls the device’s energy storage capabilities. We used a machine learning model to determine the aqueous solubility of slightly more than 3000 …

Mechanical Properties Of Polymer Matrix Nanocomposites Reinforced With Varying Carbon Nanotube Geometries, Ethan Gaigalas, Zoe Kelemen

College of Engineering Summer Undergraduate Research Program

This study serves as part of an introduction to nanocomposite research at California Polytechnic State University, San Luis Obispo, and attempts to form an observational comparison between the performance of various CNT-Epoxy nanocomposites under drop weight testing. As a continuation of research on CNT-Epoxy nanocomposites, this study specifies three geometries of Multi-walled carbon nanotubes: straight (MWSCNTs), helical (MWHCNTs), and OH-functionalized straight (FMWSCNTs); and it compares their impact resistances to neat epoxy samples. Based on the total number of failed samples under a normalized impact energy of 0.335J/mm, it is observed that FMWSCNTs increase the impact resistance of Epoxy panels at …

Deep-Learning Based Microstructure Reconstruction And Generation, Cameron J. Maloney, Lucas Taliaferro

College of Engineering Summer Undergraduate Research Program

Characterizing the microstructural behavior of materials is crucial for understanding their properties and performance. Traditional imaging methods, such as optical microscopy and electron microscopy, are effective but costly and time-consuming. Computational approaches can reduce costs and time while expanding the accessibility of microstructural analysis through the generation of new microstructure images. Traditional computational approaches, namely descriptor-based approaches, are slow but effective in low-data scenarios. Modern approaches use machine learning (ML), which is faster but often requires a lot of data to approach the performance of descriptor-based methods. This research leverages a special data-efficient Generative Adversarial Network (GAN) architecture to artificially …

Mapping Of The Potential To Substitute Plastic In Food Packaging In Finnish Supermarkets, Taina Lahtinen, Kirsi Kataja, Jari Viitanen, Vinay Kumar, Jussi Lahtinen, Ali Harlin

Journal of Applied Packaging Research

Single-use plastics (SUP), which are extensively utilized in food packaging, are one notable cause for the constantly growing littering issue. This novel study is one of the first attempts to systemically analyze food packaging data to reveal the potential for plastic packaging material reduction or substitution by utilizing a primary packaging material summary of single items sold in Finnish supermarkets. The outcome of the study indicates considerable dissimilarities among product groups concerning used packaging materials, weight, share of plastic, and sales volume. The analysis identified sweets and ready-to-eat meals as product groups for which there is a clear need, but …

Implementation Of Machine Learning Using Deep Neural Networks To Estimate The Failure Risk Caused By Leakage In Pressure Relief Devices, Adi Yudho Wijayanto, Yossi Andreano, M. Ali Yafi Rizky, Dedi Priadi

Journal of Materials Exploration and Findings

The primary objective of deploying Pressure Relief Device (PRD) equipment is to ensure the safety of pressure vessels within a pressurized system. Over time, PRD equipment may degrade and fail to perform its intended function, which must be identified as a failure mode. To mitigate potential risks associated with this, it is recommended that an approach such as risk-based inspection (RBI) be implemented. Despite the widespread adoption of RBI, the method relies on qualitative techniques, leading to significant variations in equipment risk assessments. This study proposes a novel risk analysis method that uses deep learning-based machine learning to develop a …

Effect Of Impurities In Supercritical Co2 Environment On Steel Corrosion Behavior – An Overview, Shilla Rizqi Widianto, Johny Wahyuadi Soedarsono, Rini Riastuti, Badrul Munir

Journal of Materials Exploration and Findings

Carbon capture, utilization, and storage (CCUS) technology is one of the available technologies to reduce presence of greenhouse gasses. Implementation of CCUS technology strongly relates with the CO₂ transportation from the capturing facility to the storage in the geological reservoir. The most economical method for large-scale and long-distance CO₂ transportation is using pipeline in supercritical phase. Moreover, presence of impurities such as water, O₂, SO₂, H₂S, NO₂ may cause detrimental effect towards carbon steel pipeline. This paper intends to provide an initial information for supercritical CO₂ pipeline material selection, which …

Hollow Connecting Rod Thin Wall Austempered Ductile Iron (Twadi) For Manufacturing Light Weight Components, Ricardina Freitas Da Silva, Bambang Suharno, Rianti Dewi Sulamet-Ariobimo

Journal of Materials Exploration and Findings

Efforts made by the automotive industry to reduce energy consumption have encouraged researchers to carry out various studies. One way is to make components lighter by casting thin wall austempered ductile iron (TWADI). Reducing the weight of components such as connecting rods (conrod) will result in lower energy consumption, but provided that these components still meet standards in terms of mechanical properties and microstructure or even exceed them. In this research, design optimization was applied to conrod by making the area I-beam zero mm (hollow), with hope that it can replace conrod Vespa PX-150. While the manufacturing process is divided …

Analysis Risk Based Inspection Api 581 On Lpg Spherical Tank At Pt. Xyz, Sigit Trahmawan, Eddy Sumarno Siradj, Jaka Fajar Fatriansyah

Journal of Materials Exploration and Findings

Liquified petroleum gas (LPG) spherical tanks are pressure vessel equipment for storing fuel gas products. The high pressure along with the fuel gas inside as flammable and combustible substance means that this equipment might result major accident hazard such as explosion, fires and environmental pollution. This study is aimed calculated and mitigate risk on 500 metric ton capacity LPG spherical tank using Risk-based inspection (RBI) analysis method that makes risk as its foundation. This RBI method uses quantitative analysis referring to API 581 to determine the risk of LPG Spherical Tank by determining the probability of failure (PoF) and the …

Root Cause Analysis Of Leakage Tube Boiler: A Study Case, Lydia Kartika Basaria Sitompul, Dedi Priadi

Journal of Materials Exploration and Findings

Oil and gas industry can have catastrophic implications for human life, the environment, and the economy. This paper investigated failure analysis using root cause analysis especially for boiler tube leakage of Heat Exchanger. Identify the issue using microscopic examination and energy dispersive x-ray analysis were conducted on the tube inside and outside surface to determine root cause of the failure. The formation of a protective film in the aluminum-brass tube during the starting stage is very important for ensuring adequate film protection throughout the service life of the heat exchanger. During this stage, exposure to unpolluted water is essential. The …

Fabrication And Characterization Of Lignin–Pva Hydrogels With Tunable Network Structures, Keturah Bethel

All Dissertations

The ability to directly tune the crosslinked network structure of hydrogels is crucial for their functional applications in various fields, such as water filtration, protein separation, and tissue engineering. By controlling the crosslink density of the hydrogel, one can directly alter the mesh size – i.e., the end-to-end distance between crosslink junctions – and, subsequently, directly alter the hydrogel performance. This work discusses the fabrication and characterization of soft composites containing the biopolymer, lignin, are discussed. Precisely, physically-crosslinked composite lignin–Poly(vinyl alcohol) (PVA) hydrogels were fabricated via the freeze-thaw (F/T) pathway, whereby solutions containing specified amounts of PVA and lignin were …

Local Charge Distortion Due To Cr In Ni-Based Concentrated Alloys, Jacob Fischer

All Theses

Due to the presence of multiple elements consisting of a range of atomic radii, local lattice distortion (LLD) is commonly observed in concentrated (and high entropy) alloys. However, since these elements also have diverse electronegativities, recent works show that atoms can have a range of atomic charges. In this work, using density functional theory (DFT), we investigate electronic charge distribution in face centered cubic (FCC) Ni-based alloys and find significant charge-density distortion in HEAs. Specifically, Cr atoms have large charge density distortion that results in a wide range of bond lengths, atomic charges, and electronic density of states in Cr-containing …

Predicting The Ductility Of Tungsten Based Bcc Refractory High Entropy Alloys: A Computational Science Driven Study, Akshay Korpe

All Theses

Bcc refractory high entropy alloys (HEAs) are a relatively new category of metallic alloys that promise excellent irradiation resistance and strength retention at high temperatures but exhibit brittle behavior at room temperatures limiting their formability. Understanding the deformation mechanisms and predicting their ductility at room temperature is a topic of interest in contemporary research.

In this work, multiple independent ductility criteria for quantifying the ductility of these HEAs were studied, calculated and compared using Density Functional Theory (DFT) calculations and continuum mechanics frameworks. These ductility parameters were calculated for various W-Ta-Cr-V alloys and the trends were analyzed for each criteria …

On The Structure, Energy, And Segregation Behavior Of Grain Boundaries In Metallic Systems, Yasir Mahmood

All Dissertations

Nearly all structural metallic systems are multi-component polycrystalline aggregates; their microstructures are composed of crystalline grains that are internally joined at grain boundaries (GBs). This thesis focuses on GB structure, energy, and chemistry, as these greatly influence many material properties and processes, including boundary dynamics during processing treatments or under operating conditions.

Using atomistic simulations, we examine the impact of metastable GB structures on solute segregation. A wide range of GB geometries and metastable structures are used in our study. The Al-Mg alloy is used because it is of interest for light weighting. The atomistic simulation results are used to …

Experimental Investigation On Mechanical Properties Of Pla Reinforced By Bamboo Fiber/Montmorillonite Clay Hybrid Composites And Analysis Of Machining Characteristics, Nirmal Kumar K

Theses and Dissertations

The study presents a comprehensive investigation into the development, characterization, and machining analysis of novel bio-based polymer hybrid composites comprising Polylactic acid (PLA), bamboo powders (BP), and montmorillonite clay particles (MMT). Initially, the hybrid composites were fabricated using a solvent-free stir casting process, optimizing the weight percentages of BP and MMT to enhance mechanical and thermal properties.

Mechanical tests, including tensile, flexural, and impact tests, along with thermal analysis using thermogravimetric analysis and differential scanning calorimetry, were conducted to evaluate the performance of the composites. In the subsequent phases, advanced machining techniques were employed to analyze the machining characteristics of …

Preparation Of Β-Ni (Oh)2 Nanosheet–Modified Glassy Carbon For Pseudocapacitors, Muhammad Buchari Setia Putra, Aliyah Aliyah, Afiten Rahmin Sanjaya, Respati Kevin Pramadewandaru, Hoeil Chung, Tribidasari Anggraningrum Ivandini

Makara Journal of Science

β-Nickel hydroxide (Ni(OH)₂) nanosheet–modified glassy carbon for pseudocapacitors was successfully prepared. The nanosheets were synthesized via a conventional growth seeding method combined with hydrothermal treatment. Transmission electron microscopy (TEM) characterization indicated the hexagonal structure of the nanosheets of around 15 nm in size, and X-ray diffraction (XRD) pattern confirmed the β-phase lattice crystal. These nanosheets used to modify the glassy carbon surface, increased the electroactive surface area by around 15 times. Furthermore, electrochemical investigation of the modified glassy carbon revealed an excellent performance and a specific capacitance of 628.01 F g⁻¹ at a 1 A g^{−1 …}

Spin And Charge Transport In Metallic Ferrimagnets And Disordered Magnetic Oxides, Leopoldo A. Hernandez

Electronic Theses and Dissertations

Recent efforts have been exploring the use of thin film synthetic ferrimagnets and disordered magnetic oxides for applications in spintronic devices. Due to the antiferromagnetic exchange interaction, ferrimagnetic materials offer the ultrafast dynamics of the antiferromagnetic exchange, with a net magnetization that can be influenced externally. With two, or more, competing ferromagnet sublattices, interesting properties arise that depend on the final magnetic landscape after growth of the material and it’s inherent magnetic anisotropy energies. Properties such as magnetic compensation temperatures, and perpendicular magnetic anisotropy are attractive for applications in spintronic memory and logic devices, some already being implemented in MRAM …