Defect Mitigation Strategies Research Articles

Reduction of oxygen content in laser powder bed fusion process atmosphere – Effects on stochastic defect formation and mechanical properties

Stochastic defects in materials manufactured via laser powder bed fusion (LPBF) can severely compromise mechanical performance and are challenging to predict and detect, thus motivating the development of defect mitigation strategies. Particle oxidation is a factor well-known to generate defects by disturbing melt pool dynamics. If the particles are spatters, additional disturbances increase the likelihood of defect formation. In this study, restricting oxygen content in the process atmosphere to 50 ppm is investigated to minimize stochastic spatter-induced defects and improve the mechanical properties of Hastelloy X. Specimens were manufactured under this condition at two nominal layer thicknesses, analyzed for internal defects, and mechanically tested. Contrary to expectations, reducing the oxygen content did not prevent spatter-induced defect formation; rather, it could exacerbate the formation of more numerous and larger defects. Nevertheless, this tighter control of the process atmosphere led to significant microstructural refinement, which, when combined with sparse defects, resulted in improved fatigue performance. Despite the inherent ductility of Hastelloy X, the presence of abundant defects significantly larger than the microstructural characteristic size proved detrimental to fatigue performance. Notably, the occurrence of defects exhibited considerable variation across the build area, contributing to scatter in fatigue data. However, quantitative analysis of in-situ monitoring data enabled prediction of variability in defect content and mechanical performance.

A review of defect mitigation strategies for UMG-Si wafers

This review focuses on the challenges and potential pathways for utilizing upgraded metallurgical-grade silicon (UMG-Si) in the silicon photovoltaic industry. UMG-Si is an attractive low-cost alternative silicon feedstock, but its bulk quality is compromised due to the presence of defects and impurities. The review begins by identifying and discussing the various defects and impurities commonly found in UMG-Si wafers, drawing insights from a literature survey. The detrimental effects of these defects on solar cell performance are highlighted. Next, the review provides a summary of defect mitigation strategies that have been employed to improve the bulk quality of UMG-Si wafers. These strategies include tabula rasa, impurity gettering, and defect/impurity passivation through hydrogenation. The effectiveness of these strategies is evaluated by considering carrier lifetimes and comparing them with those of conventional silicon wafers. The review then examines the reported open-circuit voltages and efficiencies of solar cells based on UMG-Si wafers. A comparison is made between the performance of UMG-Si solar cells and those fabricated on conventional silicon. The impact of defect mitigation strategies on the performance of UMG-Si solar cells is discussed, emphasizing the improvements achieved through these strategies.

(Invited) Two-Dimensional Low-Toxicity Absorbers for Efficient and Air-Stable Indoor Photovoltaics

The toxicity and bioavailability of lead (Pb) in halide perovskites motivates the search of Pb-free perovskite-inspired materials (PIMs), which would replicate the great optoelectronic properties of the traditional Pb-based counterparts. Among them, pnictohalides employing antimony or bismuth are especially attractive due to their low toxicity and inherent air stability. Their wide bandgaps (⁓2 eV) can broaden the application scenario beyond single-junction solar cells, being specifically suitable for e.g., silicon-perovskite tandems, indoor photovoltaics (IPVs), and photocatalysis.Despite outstanding indoor power conversion efficiencies up to 60% have been theoretically predicted for PIM-based IPVs, this research is still in a very early stage. In this talk, I will highlight some of our key findings on two-dimensional Sb- and/or Bi- based two-dimensional pnictohalides for sustainable indoor light harvesting. The considerable presence of both intrinsic and surface defects in wide-bandgap PIMs is mostly responsible for the modest indoor power conversion efficiency (PCE(i)) reported so far up to ⁓5% at 1000 lux white LED illumination. I will discuss the effective defect mitigation strategies relying on compositional engineering that we proposed to significantly improve the PCE(i) up to nearly 10% (9.53%). Our extensive characterizations at both material and device level evidence the successful suppression of trap-assisted and interfacial charge recombination as the result of a reduced defect density within the PIM domains and/or at their surface.The importance of our findings for the energy research community (within and beyond halide perovskite) lies in promoting future compositional design effort to reduce the defects in the next-generation wide-bandgap absorbers for eco-friendly energy generation and consumption.

Microstructural evolution of extended defects in 25 μ m thick GaN homo-epitaxial layers

Defect origins and their propagation behavior were investigated in 25 μm thick homo-epitaxial GaN layers grown on ammono-thermal and void-assisted separation (VAS) substrates using multi-vector x-ray topography in both transmission and reflection geometries. Complex inclusions were identified and their microstructure was analyzed. Additionally, generation of threading dislocation clusters during epitaxial growth is analyzed. Various defects are delineated from the substrate vs epitaxial layers. Growth on the ammono-thermal substrate led to less defective and flatter epitaxial layers compared to the growth on the VAS substrate. Determining the origins and microstructure of defects is crucial toward developing defect mitigation strategies for reliable GaN devices.

Function-based selective and adaptive cyber-physical assembly system for increased quality in optoelectronics industry

Recent advances in smart manufacturing technologies combined with the growing emphasis on zero-defect manufacturing paradigm set a premium on defect mitigation strategies in low-volume production systems. Assemblies for high-tech, high-variety products are becoming more complex, necessitating the need for in-line inspection, prediction, and prevention mechanisms; since the state-of-art end-of-line quality gates are error-prone due to accumulation of variability and errors from heterogeneous sources, originating in upstream process stages. This paper proposes a dynamic function-oriented selective and adaptive assembly based on Cyber-Physical System (CPS) capabilities in order to meet changing product quality standards while enhancing the flexibility of the underlying strategy. A real-case study in optoelectronics industry is used to test and validate the method, highlighting the major benefits of the suggested methodology in terms of final product quality.

Preforming characteristics and defect mitigation strategies for multi-layered biaxial pillar-stitched non-crimp fabric

Preforming characteristics and defect mitigation strategies for multi-layered biaxial pillar-stitched non-crimp fabric

Reinforcement learning-based defect mitigation for quality assurance of additive manufacturing

Additive Manufacturing (AM) is a powerful technology that produces complex 3D geometries using various materials in a layer-by-layer fashion. However, quality assurance is the main challenge in AM industry due to the possible time-varying processing conditions during AM process. Notably, new defects may occur during printing, which cannot be mitigated by offline analysis tools that focus on existing defects. This challenge motivates this work to develop online learning-based methods to deal with the new defects during printing. Since AM typically fabricates a small number of customized products, this paper aims to create an online learning-based strategy to mitigate the new defects in AM process while minimizing the number of samples needed. The proposed method is based on model-free Reinforcement Learning (RL). It is called Continual G-learning since it transfers several sources of prior knowledge to reduce the needed training samples in the AM process. Offline knowledge is obtained from literature, while online knowledge is learned during printing. The proposed method develops a new algorithm for learning the optimal defect mitigation strategies proven the best performance when utilizing both knowledge sources. Numerical and real-world case studies in a fused filament fabrication (FFF) platform are performed and demonstrate the effectiveness of the proposed method.

Defect and Distortion in Powder Bed Fusion of Metal Additive Manufacturing Parts

One of the state-of-the-art technologies for metal fabrication is laser powder bed fusion, which includes the following printing techniques: selective laser melting, selective laser sintering, direct metal laser sintering, and electron beam melting. This work examines defect formation in laser powder bed fusion, predominately focusing on selective laser melting. It also explores recent research findings on defect formation and classification and analyzes various internal defects, such as porosity, lack of fusion, balling, and solidification cracking. The influence of process parameters on defect formation and the effect of defects on mechanical properties are analyzed. This review also discusses defect inspection technologies (melt pool, scan path, and slice monitoring), defect mitigation strategies (online detection, process parameters, and numerical simulation), and their applications in additive manufacturing, such as laser powder bed fusion. This review would aid manufacturers in determining the root cause of defect formation and developing inspection technologies and mitigation strategies.

A New Approach to Measuring Local Properties of Preforms Enhanced for Formability

Forming of dry engineering textiles is a quality-critical operation in composites manufacturing. There are various different defect mitigation strategies that have been developed to ensure that material will not wrinkle or fold when depositing and forming. One promising direction is the modification of textile properties in the regions where a defect is likely to form. This can be achieved by the integration of patches: additional materials, such as reactive thermally-conditioned resins, tufted or stitched yarns, thermoplastic films, locally activated binder, etc. This method is simple and effective for a certain class of forming problems. The success of the forming operation depends on the balance of properties between dry and patched materials. At present, there is no clearly established methodology for the characterisation of these formability enhancements. Patches are local and an isolated coupon often cannot be extracted from a hosting fabric. This paper discusses the feasibility of adapting the conventional bias extension test to extract the shear properties of locally enhanced material. The obtained properties are critical for modelling tools that can inform the optimum patch location and orientation. The suggested approach is practical, simple to implement and proven to provide properties to a reasonable degree of accuracy for non-linear elastic and visco-elastic patch behaviours.

Identifying and Passivating Killer Defects in Pb-Free Double Cs2AgBiBr6 Perovskite.

Pb-free double perovskites, such as Cs2AgBiBr6, are alternatives to lead halide perovskites for photovoltaic applications due to superior stability, low toxicity, and promising optoelectronic properties. However, their performance is subpar. We combine nonadiabatic molecular dynamics and real-time time-dependent density-functional theory to show that the negatively charged Br vacancy in Cs2AgBiBr6 creates an extremely detrimental donor-yielded (DY) center, which is a typical defect in six-coordinated semiconductors. Ag+ and Bi3+ form a bond by attraction through the anisotropic vacancy charge, generating a midgap state that traps holes within tens of picoseconds. Substituting Ag with indium by doping produces a weak and long In-Bi bond, lifting the defect energy level to the conduction band. Hole trapping slows down by an order or magnitude, and trap-assisted charge recombination decreases 4-fold. The simulations bring atomistic insights into defects of Pb-free double perovskites and provide a defect mitigation strategy for rational design of high-performance optoelectronic devices.

The Roll-to-Roll Deposition of 2D Nanoflake Films of Semiconducting Tmds for Large Area Solar-to-Chemical Energy Conversion

The exceptional semiconducting properties of exfoliated transition metal dichalcogenide (TMDs) nanosheets have long inspired their use in photoelectrochemical applications; in particular, photoelectrodes for solar-to-chemical energy conversion. Indeed, past demonstrations using non-exfoliated, bulk material gave solar-to-hydrogen efficiencies greater than 7%.1 In taking advantage of the exfoliable nature of these materials, nano-TMDs not only provide a new range of tunable optoelectronic properties, but also create a direct path toward ultrathin, flexible devices. However, a major challenge in commercializing TMD-based devices is their large-scale production.2 Our group has recently addressed this issue by developing methods for solution-based fabrication of nanoflake TMD thin films for large area solar energy conversion applications.3 In this presentation we highlight our results employing WSe2 for solar water splitting and report the further advancement of our preparation methods toward a continuous roll-to-roll deposition of TMD-based thin films from nanoflake dispersions using a liquid-liquid interfacial self-assembly technique.3,4 We demonstrate reproducible printing of 100mm wide TMD flake films on plastic substrates at 10 mm s-1 with nanoflake loadings of 35 mg m-2.4 Importantly we show that these large-scale films of semiconducting TMDs are robust and capable of solar-to-chemical energy conversion comparable to that of their batch-scale counterparts.4 In addition, we address the effects of processing conditions on TMD flake quality and optoelectronic device performance. We find that the type of exfoliation and related parameters have a significant impact on the defect density within the flakes, which effects the harvesting of photogenerated charge carriers. We observe this for MoS2 and WSe2-based devices, suggesting that this is a fundamental limitation of liquid exfoliated TMDs. To overcome this limitation we present distinct defect mitigation strategies that can drastically improve the solar energy conversion ability of TMD nanoflake films.5 These techniques lead to state-of -the-art performance of solution-processed WSe2 nanoflake films for photoelectrochemical H2 production with internal quantum efficiency of over 50% and 1 sun photocurrent density over 4 mA cm-2.5

Identification of Defect Generation Rules among Defects in Construction Projects Using Association Rule Mining

This study aims to identify the defect generation rules between defects, to support effective defect prevention at construction sites. Numerous studies have been performed to identify the relations between defect causes, to prevent defects in construction projects. However, identifying the inter-causal pattern does not yet guarantee an ultimate grasp of what constitutes proper defect mitigation strategies, unless the underlying defect-to-defect generation rules are thoroughly understood too. Specifically, if a defect generated in a work process is ignored without taking necessary corrective action, then additional defects could be generated in its following works as well. Thus, to minimize defect generation, this study analyzes the defects in the sequence of a construction work. To achieve this, the authors collected 9054 defect data, and association rule mining is used to analyze the rules between the defects. Consequently, 216 rules are identified, and 152 rules are classified into 3 categories along with 4 experts (71 expected rules, 22 unexpected but explainable rules, and 59 unexpected and unexplainable rules). The generation rules between the defects identified in this study are expected to be used to regularize various defect types to determine those that require priority management.

Defect reduction strategies for the manufacture of contoured laminates using vacuum BAG-only prepregs

Complex structures manufactured using low-pressure vacuum bag-only (VBO) prepreg processing are more susceptible to defects than flat laminates because of complex compaction conditions present at sharp corners. Consequently, effective defect mitigation strategies are required to produce structural parts. In this study, we investigated the relationships between laminate properties, processing conditions, mold designs, and part quality in order to develop science-based guidelines for the manufacture of complex parts. Generic laminates consisting of a central corner and two flanges were fabricated in a multipart study that considered variation in corner angle and local curvature radius, the applied pressure during layup and cure, and the prepreg material and laminate thickness. The manufactured parts were analyzed in terms of microstructural fiber bed and resin distribution, thickness variation, and void content. The results indicated that defects observed in corner laminates were influenced by both mold design and processing conditions and those optimal combinations of these factors can mitigate the defects and improve quality. POLYM. COMPOS., 2015. © 2015 Society of Plastics Engineers

Design of Phosphorus-Containing MWIR Type-II Superlattices for Infrared Photon Detectors

Type-II strained layer superlattices (SLSs) offer a broad range of design degrees of freedom to help optimize their properties as absorber layers of infrared photon detectors. We theoretically examine a new class of mid-wavelength infrared (2-5 μm bandpass) Type-II structures with two-layer InGaSb/InPSb and four-layer InAs/GaSb/InAs/InPSb SLS periods. Phosphorous-containing SLSs are a promising approach to improving infrared photon detector performance due to providing a new set of material properties, including favorable valence band offsets. P-based SLSs of four-layer type InAs/GaSb/InAs/InPSb were found to be among the best 5-μm gap SLSs that we have modeled. Among the studied designs, the lowest dark current in an ideal structure is predicted for a four-layer 23.6 A InAs/20 A GaSb/23.6 Å InAs/60 Å InP 0.62Sb0.38 SLS. Its predicted ideal dark current is about 35 times lower than an n-type HgCdTe-based photodiode absorber and six times lower than a p-type HgCdTe one for the same bandgap, temperature, and dopant concentration. We also discuss a defect mitigation strategy that involves positioning the SLS gap in an energy range that avoids defect levels and show how this applies to the aforementioned P-containing SLS.

Phase defect mitigation strategy: unveiling fiducial mark requirements on extreme ultraviolet lithography masks

For extreme ultraviolet lithography (EUVL), the fabrication of defect free multi-layered (ML) mask blanks is a challenge. ML defects are generated by substrate defects and adders during ML coating and are called phase defects (PDs). If we can accept ML blanks with a certain number of PDs, the blank yield will be drastically increased. We can use fewer PD blanks and reduce PD influence by covering them with an absorber layer. To do this, PDs should be located during ML blank defect inspection before absorber patterning. To locate PDs on blanks accurately and precisely, the fiducial marks (FMs) on ML blanks can be used for mask alignment. The defect location accuracy requirement is below 10 nm. We present the results of a feasibility study on the requirements of FMs on EUVL masking by simulations and experiments to establish a PD mitigation method with the EUV actinic blank inspection tool. Based on the results, the optimum ranges for FM lines etched into the ML are 3 to 5 μm in width and at least 100 nm in depth.