Fast analysis of small organic contamination at the surface represents a major set of common microelectronics and semiconductor issues. Infrared (IR) microspectroscopy the workhorse for organic contamination is often limited to ~50µm and larger. Many labs move these samples from IR to Raman micro spectroscopy which should achieve higher spatial resolution down to 1µm using high NA objectives but routinely fails to achieve the chemical specificity of these organic contaminants. We will discuss a new IR method that provides organic contamination identification <1µm resolution. We provide this analysis via an automated routine, where optical images including brightfield, cross-polarized or fluorescence images can be used to automatically identify the contamination, provide its approximate shape and size, and identify its X&Y location on the sample, for measurement. The measured spectra is searched to provide a match against stored library spectra to identify the contamination.

Failure analysis of small contamination at the surface and sub-surface interface represents a major set of common microelectronics and semiconductor issues. The application of O-PTIR spectroscopy analyses provides flexibility to sample preparation and improves sensitivity to very small levels of contamination even below <1 micron in layers or particles on or just below the surface. The detection of this contamination can be limited if only bright field imaging is used to contrast the region of interest (ROI) and the surrounding structure. Adding fluorescence microscopy is an additional imaging technique that adds another layer of chemical specificity and provides locations of unseen ROI’s for additional IR and Raman spectral analysis.

This paper describes a new infrared (IR) technique that offers sub-micron spatial resolution with a pump-probe scheme that can offer simultaneous collection of IR and Raman spectra at the same spatial resolution. The technique uses a single beam to collect both IR and Raman spectra using a technique called Optical Photothermal Infrared (O-PTIR). The O-PTIR technique provides constant spatial resolution over the entire mid-IR range due to the use of a fixed wavelength probe beam at 532 nm. The paper provides examples that highlight the advantages of the novel technique for addressing challenges that are commonly observed in the failure and contamination analysis community.

This paper discusses the use of optical photothermal infrared (O-PTIR) spectroscopy combined with Raman analysis. The new technique overcomes many of the limitations of conventional FTIR and Raman spectroscopy when used alone. It is based on an infrared-visible pump-probe system that incorporates a wavelength-tunable IR laser that emits a pulsed beam that is combined colinearly with the output of a 532-nm green laser. As the paper explains, infrared radiation is partially absorbed by the test target when the wavelength of the laser resonates with the vibrational mode of the material. This excitation process causes the area under the infrared spot to heat up, in turn, causing local expansion along with changes in the refractive indices. These photothermal effects cycle on and off in synch with the pulsed IR beam and the amplitudes of the on-off states are captured by the co-located visible beam and plotted as a function of wavelength over the tunable range of the IR laser. The diffraction limited spot size of the visible beam is approximately 416 nm, corresponding to a spatial resolution of about 1 μm, which is 30 times more precise than conventional FTIR. In addition, by measuring photothermal effects in localized regions, it is possible to identify chemicals in quantities of matter as small as 0.4 pg. By comparison, the sensitivity of transmission mode FTIR is significantly less at around 100 pg.

Rapid identification of organic contamination in the semi and semi related industry is a major concern for research and manufacturing. Organic contamination can affect a system or subsystem’s performance and cause premature failure of the product. As an example, in February 2019 the Taiwan Semiconductor Manufacturing Company (TMSC), a major semiconductor manufacturer, reported that a photoresist it used included a specific element which was abnormally treated, creating a foreign polymer in the photoresist resulting in an estimated loss of $550M [1].

Failure analysis of organics at the microscopic scale is an increasingly important requirement, with traditional analytical tools such as FTIR and Raman microscopy, having significant limitations in either spatial resolution or data quality. We introduce here a new method of obtaining Infrared microspectroscopic information, at the submicron level in reflection (far-field) mode, called Optical-Photothermal Infrared (O-PTIR) spectroscopy, that can also generate simultaneous Raman spectra, from the same spot, at the same time and with the same spatial resolution. This novel combination of these two correlative techniques can be considered to be complimentary and confirmatory, in which the IR confirms the Raman result and vice-versa, to yield more accurate and therefore more confident organic unknowns analysis.

Continuous development in the semiconductor process technology has led to the fabrication of devices with nanometer scale feature resolution. Resonance enhanced atomic force microscopy infrared (AFM-IR) is a novel technique with potential to overcome some limitations of existing tools. This manuscript illustrates chemical characterization of the nanoscale skin and polyester contaminant on silicon wafer using resonance enhanced AFM-IR spectroscopy. Resonance enhanced AFM-IR offers superior sensitivity for nanoscale organic contaminants. To demonstrate this capability, AFM-IR spectra were obtained from contaminants on silicon wafers, and the spectra correlated with a high confidence to a standard transmission FTIR spectral database. In addition, a newly developed high speed spectral acquisition scheme, which augments the reliability of nanoscale defect characterization by reducing the overall data acquisition time and enabling users to perform repeated measurements for statistical analysis, is established.