Journal of Vacuum Science & Technology A最新文献

{"title":"Ultrahigh density InGaN/GaN nanopyramid quantum dots for visible emissions with high quantum efficiency","authors":"Cheng Liu, Nikhil Pokharel, Qinchen Lin, Miguel A. Betancourt Ponce, Jian Sun, Dominic Lane, Thomas J. De Prinse, Nelson Tansu, Padma Gopalan, Chirag Gupta, Shubhra S. Pasayat, Luke J. Mawst","doi":"10.1116/6.0002997","DOIUrl":"https://doi.org/10.1116/6.0002997","url":null,"abstract":"In this study, the selective area epitaxy (SAE) of InGaN/GaN nanopyramid quantum dots (QDs) on a block copolymer patterned (BCP) GaN template using metalorganic chemical vapor deposition is reported. The pattern transfer process and SAE process are developed to enable a ultrahigh density of 7–9 × 1010 cm−2 QD formation with a feature size of 20–35 nm. The growth mechanism and geometrical properties of the QDs were investigated by scanning electron microscopy and cross-sectional transmission electron microscopy, showing the nanopyramid QD structure with InGaN grown on semipolar {101¯1} planes. The optical characteristics of the nanopyramid QDs were examined by microphotoluminescence measurements. We observed QD emission centered at 488 and 514 nm, depending on the growth temperature employed. These emissions were found to be longer wavelength than those from a planar quantum well structure. This can be attributed to the combined effects of higher indium incorporation along the semipolar plane and a larger InGaN thickness. Furthermore, we also found that the QD emission intensity increases as the number of InGaN layers increases without wavelength shift, indicating a constant growth rate and indium incorporation along the semipolar plane after the formation of the nanopyramid structure. The internal quantum efficiency is estimated to be over 60% by comparing the photoluminescence (PL) intensity of QDs at low temperature and room temperature. PL emission wavelength shows an 11 nm blue shift, while the full width at half maximum decreases from 68 (351 meV) to 56 nm (303 meV) from room temperature to low temperature. By employing BCP lithography and SAE technique, we successfully demonstrated that ultrahigh density, small size InGaN/GaN nanopyramid QDs with visible emission were achieved, which could be a potential active region for QD light-emitting diodes and/or lasers.","PeriodicalId":17490,"journal":{"name":"Journal of Vacuum Science & Technology A","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135479876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study of Al2124-SiC nanocomposites by an improved statistical nanoindentation methodology","authors":"Esteban Broitman, Yuri Kadin, Predrag Andric","doi":"10.1116/6.0003048","DOIUrl":"https://doi.org/10.1116/6.0003048","url":null,"abstract":"In this work, we first review the previous work done on statistical nanoindentation by different researchers, highlighting the main problems that have been found and possible proposed solutions. In the second part, we study and report the statistical nanoindentation of three model samples, in the form of a soft Al2124 matrix embedded with hard SiC particles. Three different variants were selected: (1) 25% of SiC particles with 3 μm diameter; (2) 25% of SiC particles with 0.7 μm diameter; and (3) 17% of SiC particles with 0.3 μm diameter. We propose a novel heuristic wavelet technique to filter the measurement noise from the raw nanoindentation data as an attempt to obtain a more robust statistical nanoindentation methodology. Our results have shown that, when the nanoindentation data are filtered, it is not necessary to select a priori the number of peaks (phases) to be analyzed and, in some cases, a wide number of bin-sizes can be used without affecting the results. Finally, a finite element modeling have been used to analyze the response of the nanoindenter regarding the position of the hard particle. Our model shows that it is impossible to get the whole hardness value of the hard SiC particle by the statistical nanoindentation methodology.","PeriodicalId":17490,"journal":{"name":"Journal of Vacuum Science & Technology A","volume":"45 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135819712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Materials characterization: Can artificial intelligence be used to address reproducibility challenges?","authors":"Miu Lun Lau, Abraham Burleigh, Jeff Terry, Min Long","doi":"10.1116/6.0002809","DOIUrl":"https://doi.org/10.1116/6.0002809","url":null,"abstract":"Material characterization techniques are widely used to characterize the physical and chemical properties of materials at the nanoscale and, thus, play central roles in material scientific discoveries. However, the large and complex datasets generated by these techniques often require significant human effort to interpret and extract meaningful physicochemical insights. Artificial intelligence (AI) techniques such as machine learning (ML) have the potential to improve the efficiency and accuracy of surface analysis by automating data analysis and interpretation. In this perspective paper, we review the current role of AI in surface analysis and discuss its future potential to accelerate discoveries in surface science, materials science, and interface science. We highlight several applications where AI has already been used to analyze surface analysis data, including the identification of crystal structures from XRD data, analysis of XPS spectra for surface composition, and the interpretation of TEM and SEM images for particle morphology and size. We also discuss the challenges and opportunities associated with the integration of AI into surface analysis workflows. These include the need for large and diverse datasets for training ML models, the importance of feature selection and representation, and the potential for ML to enable new insights and discoveries by identifying patterns and relationships in complex datasets. Most importantly, AI analyzed data must not just find the best mathematical description of the data, but it must find the most physical and chemically meaningful results. In addition, the need for reproducibility in scientific research has become increasingly important in recent years. The advancement of AI, including both conventional and the increasing popular deep learning, is showing promise in addressing those challenges by enabling the execution and verification of scientific progress. By training models on large experimental datasets and providing automated analysis and data interpretation, AI can help to ensure that scientific results are reproducible and reliable. Although integration of knowledge and AI models must be considered for the transparency and interpretability of models, the incorporation of AI into the data collection and processing workflow will significantly enhance the efficiency and accuracy of various surface analysis techniques and deepen our understanding at an accelerated pace.","PeriodicalId":17490,"journal":{"name":"Journal of Vacuum Science & Technology A","volume":"65 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135868479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-time artificial intelligence enhanced defect engineering in CeO2 nanostructures","authors":"Udit Kumar, Ayush Arunachalam, Corbin Feit, S. Novia Berriel, Kanad Basu, Parag Banerjee, Sudipta Seal","doi":"10.1116/6.0002912","DOIUrl":"https://doi.org/10.1116/6.0002912","url":null,"abstract":"CeO2 nanostructures have been utilized for various biomedical, sensor, and catalysis applications owing to their unique defect structure, enabling them to have regenerative oxidative properties. Defect engineering in CeO2 nanostructures has major importance, enabling them to be utilized for specific applications. Despite various synthesis methods, it is challenging to have precise and reversible control over defect structures. Against this backdrop, in the current work, we have explored machine learning (ML) enhanced defect engineering of CeO2 nanofilms. In our earlier work [J. Vac. Sci. Technol. A 39, 060405 (2021)], we have developed an atomic layer deposition process for CeO2 using in situ ellipsometry measurements. In the current work, data collected through in situ spectroscopic ellipsometry and ex situ XPS have been correlated using two ML algorithms (gradient boost and random forest regressor) to exert better control over the chemical properties. Defect structures are one of the desired properties in CeO2 nanomaterials, characterized by the Ce3+/Ce4+ oxidation state ratio leading to its regenerative properties. We have shown that the defect structure of the CeO2 nanofilms can be predicted using in situ ellipsometry data in real time using a trained ML algorithm using two different methods. The first method involves an indirect approach of thickness prediction using an ML algorithm (k-nearest neighbors) followed by Ce3+/Ce4+ estimation using an experimental calibration curve. The second method with a more direct approach involves Ce3+/Ce4+ prediction using real-time ellipsometry data (amplitude ratio ψ and phase difference Δ) using gradient boost and random forest regressor.","PeriodicalId":17490,"journal":{"name":"Journal of Vacuum Science & Technology A","volume":"16 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135934526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electron-enhanced atomic layer deposition of Ru thin films using Ru(DMBD)(CO)3 and effect of forming gas anneal","authors":"Michael A. Collings, Marcel Junige, Andrew S. Cavanagh, Victor Wang, Andrew C. Kummel, Steven M. George","doi":"10.1116/6.0002938","DOIUrl":"https://doi.org/10.1116/6.0002938","url":null,"abstract":"Ruthenium (Ru) thin films were deposited utilizing electron-enhanced atomic layer deposition (EE-ALD). Sequential exposures of Ru(DMBD)(CO)3 (DMBD = 2,3-dimethylbutadiene) and low-energy electrons at ∼125 eV were used to grow the Ru films at temperatures ≤160 °C. The electrons were obtained from a hollow cathode plasma electron source that provided an electron current of ∼200 mA over a surface area of ∼4 cm2. Low-energy electrons can desorb surface ligands derived from Ru(DMBD)(CO)3, such as CO, through electron-stimulated desorption. The desorbed surface ligands leave chemically reactive sites for subsequent Ru(DMBD)(CO)3 precursor absorption. Ru EE-ALD film growth was monitored utilizing in situ spectroscopic ellipsometry (SE). The electron exposures resulted in rapid Ru film nucleation and growth. Under saturation conditions at 160 °C, the growth rate for Ru EE-ALD was 0.2 Å/cycle. The electron efficiency factor for Ru EE-ALD was ∼21 500 electrons/deposited Ru atom. There was no film growth without electron exposures. Ru growth was observed on various substrates including silicon with native oxide and titanium. Ru growth was also obtained on insulating substrates such as 400 nm thick thermal SiO2 substrates. XPS analysis measured <1 at. % oxygen in the deposited Ru films. XRD, x-ray reflectivity, and SE were used to characterize the Ru films before and after forming gas anneal (FGA). FGA successfully removed carbon impurities from the as-deposited Ru films. The resistivity of the Ru EE-ALD films after FGA was determined to be as low as 17 μΩ cm for a film thickness of 6.7 nm. SE measurements of the imaginary part of the pseudodielectric function, 〈ɛ2〉, were utilized to characterize the as-deposited Ru films and the high purity Ru films after FGA. The low resistivity of the Ru films after FGA was consistent with a prominent Drude absorption in the ⟨ε2⟩ spectrum at ≤1 eV. Various reactive background gases such as H2, NH3, and H2O were utilized during EE-ALD to attempt to remove the carbon from the as-deposited Ru EE-ALD films.","PeriodicalId":17490,"journal":{"name":"Journal of Vacuum Science & Technology A","volume":"17 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135272586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of nitrogen pressure on the fabrication of AlCrFeCoNiCu0.5 high entropy nitride thin films via cathodic arc deposition","authors":"Tenghao Jiang, Hong Zhao, Kostadinos Tsoutas, Lixian Sun, Hongwei Liu, Yanping Liu, Fanjun Xu, Zhong Zheng, Marcela M. Bilek, Zongwen Liu","doi":"10.1116/6.0003064","DOIUrl":"https://doi.org/10.1116/6.0003064","url":null,"abstract":"In the past two decades, high entropy alloy (HEA) coatings have attracted great attention due to their superior mechanical properties, outstanding corrosion and oxidation resistance, and exceptionally high thermal stability. In comparison to HEA thin films, high entropy nitrides (HENs) exhibit higher mechanical strength and chemical inertness. In this work, AlCrFeCoNiCu0.5 HEA and HEN thin films were fabricated using a filtered cathodic arc. By regulating the deposition pressure from 0.0005 Pa (HEA thin film) to 0.05 Pa, the nitrogen concentration in each thin film was precisely controlled to tune the mechanical properties. Scanning transmission electron microscopy-energy dispersive spectroscopy revealed that the nitrogen concentration of the films was up to 21.2 at. % at the pressure of 0.05 Pa. The reduced effect of preferential sputtering increased aluminum concentration from 8.3 ± 1.5 to 12.9 ± 2.2 at. % as pressure increased up to 0.05 Pa. X-ray photoelectron spectroscopy further confirmed the formation of AlN and CrN at pressures of 0.01–0.05 Pa. The highest hardness and elastic modulus of the HEN film were 12.4 ± 0.6 and 347.3 ± 17.7 GPa, respectively, which were 84.8% and 131.4% higher than those of the HEA thin film.","PeriodicalId":17490,"journal":{"name":"Journal of Vacuum Science & Technology A","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135871480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adsorption mechanism of dimeric Ga precursors in metalorganic chemical vapor deposition of gallium nitride","authors":"Hankyu Kim, Miso Kim, Bumsang Kim, Bonggeun Shong","doi":"10.1116/6.0002966","DOIUrl":"https://doi.org/10.1116/6.0002966","url":null,"abstract":"Gallium nitride (GaN) has attracted significant interest as a next-generation semiconductor material with various potential applications. During metalorganic chemical vapor deposition (MOCVD) of GaN using trimethyl gallium (TMG) and NH3, dimeric precursors are produced by gas-phase reactions such as adduct formation or thermal decomposition. In this work, the surface adsorption reactions of monomeric and dimeric Ga molecules including TMG, [(CH3)2Ga(NH2)]2, and [(CH3)GaNH]2 on the GaN surface are investigated using density functional theory calculations. It is found that [(CH3)2Ga(NH2)]2 is the most predominant form among the various dimeric precursors under typical GaN MOCVD process conditions. Our results indicate that the dimeric [(CH3)GaNH]2 precursor, which is generated through the thermal decomposition of [(CH3)2Ga(NH2)]2, would have higher reactivity on the GaN surface. Our work provides critical insights that can inform the optimization of GaN MOCVD processes, leading to advancements in GaN-based high-performance semiconductors.","PeriodicalId":17490,"journal":{"name":"Journal of Vacuum Science & Technology A","volume":"17 19","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135863985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Electrochromic properties of NiO films prepared by atomic layer deposition","authors":"Xi Su, Zexin Tu, Liwei Ji, Hao Wu, Hongxing Xu, Chang Liu","doi":"10.1116/6.0003040","DOIUrl":"https://doi.org/10.1116/6.0003040","url":null,"abstract":"Nickel oxide (NiO) films were prepared on ITO-coated glass substrates by atomic layer deposition at different temperatures. NiO films exhibit good anodic electrochromic properties because of their polycrystalline structures. The optical modulation observed at 550 nm was around 44%, changing color from transparent to black. The largest coloration efficiency at 550 nm was calculated to be 31.7 cm2/C.","PeriodicalId":17490,"journal":{"name":"Journal of Vacuum Science & Technology A","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136067495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding ion and atom fluxes during high-power impulse magnetron sputtering deposition of NbCx films from a compound target","authors":"M. Farahani, T. Kozák, A. D. Pajdarová, A. Bahr, H. Riedl, P. Zeman","doi":"10.1116/6.0002944","DOIUrl":"https://doi.org/10.1116/6.0002944","url":null,"abstract":"A combination of time-averaged mass spectroscopy (MS), time-averaged optical emission spectroscopy (OES), and plasma transport modeling was employed to understand the transport processes of ions and atoms in high-power impulse magnetron sputtering discharges resulting in changes in the stoichiometry of NbCx films during their deposition from a stoichiometric NbC compound target at different repetition frequencies and duty cycles. Mass spectrometry showed that the fluxes of ions originating from the elements of the target increase with increasing pulse power density (and decreasing pulse length) due to an increasing electron density and, thus, electron-impact ionization probability. Due to the higher ionization energy and much lower ionization cross section of C (compared to Nb), it was found that the contribution of C+ ions to the deposition flux is practically negligible. Additionally, OES tracked the densities of ions and atoms at different distances from the target. The OES analysis revealed that the atom densities decreased as the pulse power density increased. In contrast, the ion densities exhibited an increase, which is consistent with the findings of MS. Using the data from MS, OES, and modeling, we were able to estimate the fluxes of atoms to the substrate. Our observations demonstrated a transition from C-rich toward Nb-rich flux of film-forming species with increasing pulse power density, corresponding to changes in the film composition. We further discuss the role of internal plasma processes that are responsible for this transition.","PeriodicalId":17490,"journal":{"name":"Journal of Vacuum Science & Technology A","volume":"279 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136261865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Microscopic study of submonolayer nucleation characteristics during GaN (0001) homoepitaxial growth","authors":"Peng Su, Wensen Ai, Xuejiang Chen, Lijun Liu","doi":"10.1116/6.0003115","DOIUrl":"https://doi.org/10.1116/6.0003115","url":null,"abstract":"An on-lattice kinetic Monte Carlo model is constructed to investigate microscopic nucleation behavior during the submonolayer epitaxial growth of GaN islands, where the Ga and N atoms are treated as the basic particles. The input kinetic parameters of Ga and N, including their surface diffusion energy barriers, were obtained from previous ab initio calculations. Furthermore, a simple and effective bond counting rule is applied in our kinetic Monte Carlo model, and the statistics of the GaN islands on the surface are realized via the application of the Hoshen–Kopelman algorithm. The growth temperature range covers the typical growth temperatures used in the molecular beam epitaxy of GaN. The results obtained show that triangular GaN flakes are observed and that the shapes of the GaN islands remain triangular when the growth temperature is changed. Additionally, the power law for the maximum density of islands versus the ratio of the effective diffusion to the deposition rate is obtained; the exponent of this law is −0.506 ± 0.006, indicating that these triplets represent the seeds required for further nucleation. Finally, the coexistence of the Ga-edge and N-edge types of triangular GaN islands is observed. The island formation mechanism is attributed to a local monomer density misbalance, and it is also shown that a slight variation in the Ga/N ratio in the deposition flux changes the proportion of the Ga-edge and N-edge type triangles; this represents a further indication that controllable GaN morphologies can be obtained by tuning the chemical potentials of the constituent elements.","PeriodicalId":17490,"journal":{"name":"Journal of Vacuum Science & Technology A","volume":"66 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136381538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}