MétaCan
Menu
Back to cohort
Record W2336421216

Laser Direct Deposition of Metal Matrix Diamond Composite

2016· dissertation· en· W2336421216 on OpenAlexfundno aff
Mehrdad Iravani-Tabrizipour

Bibliographic record

VenueUWSpace (University of Waterloo) · 2016
Typedissertation
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of WaterlooGovernment of Ontario
KeywordsComposite numberMaterials scienceLaserDiamondMatrix (chemical analysis)Composite materialDeposition (geology)Metal matrix compositeMetalMetallurgyOpticsGeologyPhysics
DOInot available

Abstract

fetched live from OpenAlex

Diamond, the hardest natural material known to humankind, is an ideal candidate for cutting and wear application, however implementing diamond in tooling is not without its challenges. Consequentially, these challenges cause diamond tools to be very expensive. Additionally, current diamond tools do not capitalize on the full potential of diamond material properties. The most significant challenge associated with using diamond in tooling is trying to avoid diamond graphitization at high temperatures during the tool manufacturing process. Finding an alternative way to fabricate improved performance and better priced diamond tools will revolutionize tooling industry. Laser direct deposition of diamond particles has the potential for production of higher performance and lower priced diamond tools. This is largely due to the low interaction time and high cooling rates involved with the deposition process. The process zone is exposed to high temperatures for a very short time and is followed by very high cooling rates. 
\n
\nThis research investigates the deposition of a metal matrix diamond composite on mild steel, addressing the associated issues and challenges with the deposition process. These issues include the decomposition of diamond, diamond particle wetting, chemical bonding of the diamond particles and the matrix, diamond retention capacity of the matrix, clad-substrate bonding, porosity and micro cracks, and diamond particles distribution in the deposited clad.
\n
\nA transient three dimensional temperature dependent finite element model for pre-placed laser cladding is developed in order to develop insight into the process window. The model is developed by ANSYS © finite element software. The governing equations, boundary conditions and assumptions used in the model are discussed. Additionally the effects of the direct laser deposition process parameters on the melt pool temperature, cooling rate, and exposure time to high temperatures are investigated. The influence of process parameters on the increase of the melt pool temperature during deposition of a clad is also studied.
\n
\nAn experimental study on deposition of ((Cu80Sn20)90Ti10)75+25 diamond weight percent via pre-placed laser cladding on a mild steel substrate is presented. The effects of using both a continuous wave and pulsed laser deposition are explored. The effects of process parameters on diamond decomposition, clad-substrate bonding, porosity and micro-cracks, wetting and chemical bonding of diamond particles, diamond particles distribution in the deposited clad, and the effect of dilution are investigated. The experimental results are in agreement with the trends predicted by the modeling.
\n
\nBoth the modeling and pre-placed laser deposition experiments provide an estimation of the process window for blown powder laser deposition. Extensive sets of experiments are conducted for the deposition by blown powder laser cladding. Cross sectional analysis is performed on both transverse and longitudinal cut-planes of the deposited clads. This is performed using Scanning Electron Microscope, Energy-Dispersive X-ray spectroscopy, and nano-indentation. Deposited diamond particles are characterized by Raman spectroscopy and a trend demonstrating reduced diamond graphitization is detected.
\n
\nA study of deposited diamond particles reveals that an interfacial titanium carbide layer is formed between diamond particles and the matrix. This layer is only formed when iron is not present at the vicinity of the diamond particles. In the presence of iron, it forms the interfacial layer which is surrounded by a titanium rich layer. This observation indicates that iron has higher affinity to react with diamond as opposed to titanium. It is also observed that the iron reaction with diamond results in diamond degradation and graphitization.
\n
\nA thermal analysis study of reaction of each elements of the matrix Reaction of each elements of the matrix (titanium, copper, and tin) and iron with diamond up to the temperature of 1300°C is conducted using Differential Scanning Calorimetry. This study reveals that mechanism of reaction between titanium and diamond is completely different from that of iron and diamond. It is found that reaction of titanium with diamond initiates when titanium transforms from α to β at 880-900°C. The formation of a titanium carbide layer starts at this temperature by diffusing titanium into the surface of diamond particles which results in nucleation of titanium carbide on the diamond surface. As this layer grows, the diffusion of titanium into the surface of the diamond becomes more difficult, thus the growth of the titanium carbide layer slows down until stops completely at a certain thickness. Graphitization of diamond does not occur. When the thickness of the titanium carbide layer reaches its maximum, it becomes brittle in a way that can be separated from the diamond particle. The reaction of iron-diamond initiates before transformation of ferrite to austenite begins (below 900°C). It starts via diffusion of detached carbon atoms from the diamond into the iron particles and continues until the melting of the solution at around 1150°C. The melting causes higher levels of diamond decomposition and higher solution of carbon in iron. This results in extreme degradation of diamond particles. Although the solubility of carbon in iron is limited, detaching of carbon atoms from diamond continues past the solubility limit, resulting in super saturation of iron matrix and presence of large graphite inclusions in the iron matrix. On the other hand, iron diffuses into the decomposed diamond particles accelerating the decomposition. This results in a significant carbon atoms detachment from the diamond particles. As a result, high fraction of the remaining carbon atoms decompose to graphite or react with the iron. In fact, not only does the iron react with the diamond, but it also acts as a catalyzer for diamond graphitization. The DSC study reveals that copper and tin neither react nor wet the diamond particles.
\n
\nIt is found that diamond-laser interaction before reaching the melt-pool plays an important role in diamond graphitization. Therefore, the effect of process parameters on the diamond-laser interaction are studied and optimized to obtain the minimum laser-diamond interaction as well as minimum temperature rise in diamond particles before joining the molten pool. Experimental analysis indicates that the temperature rise of diamond particles passing the laser beam is only partially responsible for diamond graphitization. Diamond reaction with oxygen at the elevated temperatures due to laser interaction is determined to be the major element of diamond graphitization. A specialized nozzle is designed to provide better protection of the powder stream against the penetration of oxygen. The nozzle design accomplishes this by providing an annular inert gas stream which surrounds the powder stream. Employing this specialized nozzle in conjunction with optimized deposition process parameters significantly reduces diamond graphitization.
\n
\nOptimum process parameters which can minimize the dilution are determined by experimental analysis. Using these parameters, diamond degradation in the deposition is drastically reduced. In an attempt to further eliminate the dilution of deposition by iron, as well as decrease the effective input energy into the process zone an intermediate layer with the composition of Cu-20Sn weight percent is added. The intermediate layer has a thickness of approximately 0.5 mm and is deposited directly on the mild steel substrate. Deposition of the metal matrix-diamond particles on the intermediate layer results in elimination of dilution and almost no graphitization. An interfacial titanium carbide layer with a thickness in the range of 150-350 nm is observed. 
\n
\nThe substrates with and without the intermediate layer are pre-heated to 700°C prior to performing the deposition. The pre-heating decreases the required effective input energy by approximately 16.7 to 17.5 percent for the substrate without intermediate layer and around 15 percent for the substrate with intermediate layer. The preheating has no effect on presence of iron in the deposition on the substrates with the intermediate layer, since without pre-heating, the presence of iron in the deposit is already negligible; however it reduces the dilution in the deposition on the substrates when no intermediate layer is present.
\n 
\nEffects of process parameters on dilution, clad substrate bonding, and aspect ratio are studied. Using experimental analysis, an equation is developed to calculate the aspect ratio from the process parameters. Furthermore, for minimizing dilution, obtaining strong clad-substrate bonding, and obtaining acceptable aspect ratio a set of inequalities (constraints) to be satisfied by process parameters is determined. From these constraints the process window is obtained.
\n
\nIn summary, through theoretical and experimental studies, this research develops a practical and reliable metal matrix diamond composite fabrication technology using laser deposition technique. The new fabrication technology can be used in developing high performance tools and highly wear resistance surfaces.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.217
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.226
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueUWSpace (University of Waterloo)Same topicDiamond and Carbon-based Materials ResearchFrench-language works237,207