Engineering topics

Mastro, Michael A.

Publications and source records attributed to Mastro, Michael A..

6 records

DOE OSTI2024

Detecting defects that reduce breakdown voltage using machine learning and optical profilometry

Abstract Semiconductor wafer manufacturing relies on the precise control of various performance metrics to ensure the quality and reliability of integrated circuits. In particular, GaN has properties that are advantageous for high voltage and high frequency power devices; however, defects in the substrate growth and manufacturing are preventing vertical devices from performing optimally. This paper explores the application of machine learning techniques utilizing data obtained from optical profilometry as input variables to predict the probability of a wafer meeting performance metrics, specifically the breakdown voltage (V bk ). By incorporating machine learning techniques, it is possible to reliably predict performance metrics that cause devices to fail at low voltage. For diodes that fail at a higher (but still below theoretical) breakdown voltage, alternative inspection methods or a combination of several experimental techniques may be necessary.

42 ENGINEERING↗

DOE OSTI2023

Using machine learning with optical profilometry for GaN wafer screening

Abstract To improve the manufacturing process of GaN wafers, inexpensive wafer screening techniques are required to both provide feedback to the manufacturing process and prevent fabrication on low quality or defective wafers, thus reducing costs resulting from wasted processing effort. Many of the wafer scale characterization techniques—including optical profilometry—produce difficult to interpret results, while models using classical programming techniques require laborious translation of the human-generated data interpretation methodology. Alternatively, machine learning techniques are effective at producing such models if sufficient data is available. For this research project, we fabricated over 6000 vertical PiN GaN diodes across 10 wafers. Using low resolution wafer scale optical profilometry data taken before fabrication, we successfully trained four different machine learning models. All models predict device pass and fail with 70–75% accuracy, and the wafer yield can be predicted within 15% error on the majority of wafers.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Zika virus detection using antibody-immobilized disposable cover glass and AlGaN/GaN high electron mobility transistors

Zika virus detection was demonstrated using antibody-functionalized cover glasses externally connected to the gate electrode of an AlGaN/GaN high electron mobility transistor (HEMT). A pulsed bias voltage of 0.5 V was applied to an electrode on the region of the cover glass region functionalized with antibody, and the resulting changes of drain current of the HEMT were employed to determine the presence of Zika virus antigen concentration ranging from 0.1 to 100 ng/ml. The dynamic and static drain current changes as a function of Zika virus concentration were modeled with a spring-like elastic relaxation model and the Langmuir extension model, respectively. Excellent fits to the data were found with relaxation time constants of antibody and antigen molecules in the range of 11 μs and 0.66–24.4 μs, respectively, for the concentration range investigated. The ratio of antibody bound with antigen to the total available antibody on the functionalized contact window was in the range of 0.013–0.84 for the Zika antigen concentration range of 0.1–100 ng/ml. Since the HEMT is not exposed to the bio-solution, it can be used repeatedly. Here, the functionalized glass is the only disposable part in the detection system, showing the potential of this approach for hand-held, low cost sensor packages for point-of-care applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Effect of GaN surface treatment on Al 2 O 3 /n-GaN MOS capacitors

The surface preparation for depositing Al 2 O 3 for fabricating Au/Ni/Al 2 O 3 /n-GaN (0001) metal oxide semiconductor (MOS) capacitors was optimized as a step toward realization of high performance GaN MOSFETs. The GaN surface treatments studied included cleaning with piranha (H 2 O 2 :H 2 SO 4 = 1:5), (NH 4 )(2)S, and 30% HF etches. By several metrics, the MOS capacitor with the piranha-etched GaN had the best characteristics. It had the lowest capacitance-voltage hysteresis, the smoothest Al 2 O 3 surface as determined by atomic force microscopy (0.2nm surface roughness), the lowest carbon concentration (similar to 0.78%) at the Al 2 O 3 /n-GaN interface (from x-ray photoelectron spectroscopy), and the lowest oxide-trap charge (Q(T) = 1.6 x 10(11) cm(-2) eV(-1)). Its interface trap density (D-it = 3.7 x 10(12) cm(-2) eV(-1)), as measured with photon-assisted capacitance- voltage method, was the lowest from conduction band-edge to midgap. (C) 2015 American Vacuum Society.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Multicycle rapid thermal annealing optimization of Mg-implanted GaN: Evolution of surface, optical, and structural properties

The first step of a multi-cycle rapid thermal annealing process was systematically studied. The surface, structure, and optical properties of Mg implanted GaN thin films annealed at temperatures ranging from 900 to 1200 °C were investigated by Raman spectroscopy, photoluminescence, UV-visible spectroscopy, atomic force microscopy, and Nomarski microscopy. The GaN thin films are capped with two layers of in-situ metal organic chemical vapor deposition -grown AlN and annealed in 24 bar of N{sub 2} overpressure to avoid GaN decomposition. The crystal quality of the GaN improves with increasing annealing temperature as confirmed by UV-visible spectroscopy and the full widths at half maximums of the E{sub 2} and A{sub 1} (LO) Raman modes. The crystal quality of films annealed above 1100 °C exceeds the quality of the as-grown films. At 1200 °C, Mg is optically activated, which is determined by photoluminescence measurements. However, at 1200 °C, the GaN begins to decompose as evidenced by pit formation on the surface of the samples. Therefore, it was determined that the optimal temperature for the first step in a multi-cycle rapid thermal anneal process should be conducted at 1150 °C due to crystal quality and surface morphology considerations.

36 MATERIALS SCIENCE↗

NASA NTRS2006

Recent Results from Epitaxial Growth on Step Free 4H-SiC Mesas

This paper updates recent progress made in growth, characterization, and understanding of high quality homoepitaxial and heteroepitaxial films grown on step-free 4H-SiC mesas. First, we report initial achievement of step-free 4H-SiC surfaces with carbon-face surface polarity. Next, we will describe further observations of how step-free 4H-SiC thin lateral cantilever evolution is significantly impacted by crystal faceting behavior that imposes non-uniform film thickness on cantilever undersides. Finally, recent investigations of in-plane lattice constant mismatch strain relief mechanisms observed for heteroepitaxial growth of 3C-SiC as well as 2H-AlN/GaN heterofilms on step-free 4H-SiC mesas will be reviewed. In both cases, the complete elimination of atomic heterointerface steps on the mesa structure enables uniquely well-ordered misfit dislocation arrays to form near the heterointerfaces with remarkable lack of dislocations threading vertically into the heteroepilayers. In the case of 3C-SiC heterofilms, it has been proposed that dislocation half-loops nucleate at mesa edges and glide laterally along the step-free 3C/4H interfaces. In contrast, 3C-SiC and 2H-AlN/GaN heterofilms grown on 4H-SiC mesas with steps exhibit highly disordered interface misfit dislocation structure coupled with 100X greater density of dislocations threading through the thickness of the heteroepilayers. These results indicate that the presence of steps at the heteroepitaxial interface (i.e., on the initial heteroepitaxial nucleation surface) plays a highly important role in the defect structure, quality, and relaxation mechanisms of single-crystal heteroepitaxial films.

Neudeck, Philip G.↗