Evaluating efficiencies of gas-phase chemical or AMC filters
01/01/2004
Overview There may be a temptation to equate the evaluation of AMC filter performance with particulate filter performance terms, such as HEPA and ULPA. But chemical filters are quite different, offering challenges in design and performance evaluation. Each must be tailored to the application, as this paper explains.
For any well-defined gas-phase chemical or airborne molecular contamination (AMC) problem, sound filter media design and targeted performance expectations can make chemical filters part or all of an effective solution. Where processes and tools are extremely sensitive and where the elements of contamination are less than well understood, however, the evaluation of chemical filter performance becomes complex and multidimensional.
Contrast this with the evaluation of particulate filters and the common language of "n'-nines" efficiency (i.e., 99.999 efficiency rating) [1]. It may be tempting to adopt similar ratings system for chemical filters, but because media and their contaminant environments are complex, evaluating efficiency requires an application-specific and analysis-based system.
 Ratings given for particle filters are minimum efficiencies. Conversely, ratings given for chemical filters are maximum efficiencies. |
One major difference between particulate and chemical filtration is end-of-life criteria. A particulate filter can actually increase its efficiency as it loads. Moreover, considering the various filtration mechanisms for different-sized particles, the efficiency rating of a HEPA filter, for example, will be based on the removal efficiency of the particle size most likely to pass through the filter [2]. Particles either larger or smaller will have a higher probability of removal such that the given efficiency is always the minimum efficiency of the filter (see figure). Efficiency increases as the filter loads (i.e., permeability becomes occluded) and will not reach an end-of-life condition until the increased pressure loss across the filter passes a certain tolerance.
On the other hand, a well-designed chemical filter begins life with nearly 100% efficiency for a particular contaminant, but loses efficiency over time. This is a critical consideration for chemical filter buyers. Costs and process productivity are at stake, and tool integrity could also be at risk.
The most effective approach to chemical filtration strategies identifies and defines the contaminant environment, assesses initial and end-of-life conditions for the filter, and finds the appropriate media for this set of unique operational parameters [3]. Consequently, chemical filtration usually requires a nonstandardized method of measuring efficiency. The application and its various systemic inputs must be analyzed to design an efficiency evaluation model that provides contextually applicable data. Individual filter media require unique systems to rate efficiency for each application.
Assessing contamination environments
Chemical filter media are designed to operate within defined contaminant environments. A filter designer must take into account all environmental inputs and the required output. Because each filter application has different and specific requirements, the conditions under which a filter must achieve its needed efficiency will differ by application [4].
Thus, any deviation from the definition of the contaminant environment, both inside and outside the fab, may affect filter performance and alter its efficiency. For example, a fab situated in the proximity of an interstate highway may experience high concentrations of silicon dioxide (SO2) during the rush hour commute. On the surface, it would seem that rush hour has nothing to do with contaminants inside the fab; analysis proves otherwise. Higher concentrations of SO2 are indeed tracked during rush hour periods. Similarly, agricultural activity can raise levels of other airborne contaminants on a seasonal basis.
Contaminant environments also include facility construction materials. One fab saw resist T-topping and became suspicious of its filtration system's low efficiency and shorter-than-expected filter life. A postmortem analysis of the filter showed high concentrations of dimethylformamide (DMF). This was puzzling because DMF was not used in this fab's processes. To make the matter even stranger, an independent air analysis found only small amounts of DMF in the ambient, but the analysis of a second filter confirmed the presence of DMF.
The offending DMF was discovered to be outgassing from a flooring adhesive recently used adjacent to the filter-system air intake. Air analysis found only small amounts of the compound, while the filter was filled with it. Not only does this highlight the importance of identifying contaminant sources, it shows how deviations from the identified contaminant environment can affect a chemical filter and alter the data necessary for evaluating its efficiency.
End-of-life conditions and breakthrough
As inferred by the previous examples, in such dynamic contaminant environments, evaluating efficiency requires an understanding of filter performance under a variety of conditions. These conditions will in turn affect the true cost-of-ownership.
If a certain level of increased pressure drop is the criterion for the end-of-life condition of a HEPA filter, then what performance parameters should determine the end-of-life criteria for a chemical filter? Accepting that efficiency decreases with time, and, thus, some contaminant will break through, the question involves the acceptable level of breakthrough for each contaminant type for each application: how much of any particular chemical contaminant can you live with? [5]
Efficiency percentage
If it were possible to clearly define the contaminant environment and the breakthrough and end-of life-conditions, a valid comparison chart based on filter efficiency for real-world contamination risks could be created.
Unlike particle filtration evaluation, chemical filtration evaluations are relative to the challenge concentration and the process's tolerance for contamination. For example, if the upper specification limit is 1ppb and the challenge concentration is 10ppb, then the filter did its job with 90% efficiency. If the challenge concentration increases to 100ppb, however, then the filter will need to operate at 99% efficiency to meet process requirements.
The more contaminant that goes through a chemical filter, the higher the efficiency will be. Given that the filter has a finite capacity, filter life will be short. A well-designed chemical filter may start off with an efficiency >99.9%, and this efficiency will be subject to degradation over time as individual adsorptive sites are consumed and the statistical probability of breakthrough increases.
Let's alter the previous example slightly. If you have a challenge concentration of 10ppb and an upper specification limit of 20ppb downstream, you can have a filter operating forever. It is not the efficiency that is as important as the net effect of the filter for the application.
The larger conclusion is that the process's tolerance for contamination determines filtration goals and therefore the filter's efficiency. With this perspective, should we really be evaluating the filter's effectiveness at protecting the process or the tool, when efficiency is relative to the challenge concentration and the predetermined upper specification limit?
Returning to the example for particulate filters, we see that the total number of particles adsorbed by various regimes is cumulative. In the case of chemical filtration efficiency, data given is usually based on the presence of a single contaminant. Empirical evidence would indicate that the mixed chemical contaminant types in an airstream can adversely affect the operating filter's efficiency.
Thus, to truly evaluate filter efficiency, it becomes necessary to analyze the spent media after replacing a filter. A media characterization can improve future efficiency by identifying compounds in the contaminant environment. The more comprehensive the contaminant list, the more well-tuned future media can be and the more complete the efficiency evaluation becomes.
Conclusion
In contrast to the case with HEPA filter efficiency ratings, expressing performance as a percentage may not be applicable to AMC filtration. A comprehensive analysis of process and potential contaminants is recommended. This analysis should include a summary of expected challenge (upstream) concentrations and required upper specification limit (the highest level of contamination the process can tolerate). With this data, an application-specific, analysis-based chemical filter can be built into the process in question.
References
- Recommended Practices 001.3: HEPA and ULPA Filters, Institute of Environmental Sciences, p. 8, definitions.
- A.J. Dallas, et al., "New Concerns with the Design of Filters for the Protection of Lithography Optics," SPIE, 2003.
- Ibid. The entire paper [2] is instructive on this topic.
- Ibid. See page 1.
- Ibid. To review charted data concerning "breakthrough" contamination and its potential effects on processes and tools, see tables on page 9.
Kevin Seguin is a senior applications chemist at Donaldson Co. Inc. High Purity Products; e-mail [email protected].