Part Number: TMP118
We're running a long-term drift test on your TMP118 temperature sensors and want to be sure we're stressing the right variables. Could you share what actually drives the accuracy drift you'd expect over the part's life, and how much each factor contributes? Specifically:
- Elapsed time / thermal exposure (i.e., is drift primarily an Arrhenius, temperature-driven aging effect?)
- Number of measurements (conversions) taken
- Time in a moist/humid environment
- Mechanical stress or vibration
Are any of these dominant relative to the others? And if you have characterization data or an app note on long-term stability, that would be a big help.
One specific area we'd like to dig into: we're extrapolating the datasheet long-term drift spec (0.024°C after 3000 h at 125°C) down to our ~37°C use condition, and the result is dominated by the activation energy (Ea) used in the Arrhenius fit. A few questions on that:
- What activation energy (eV) does TI use for TMP118 long-term drift extrapolation, and which drift/failure mechanism does it correspond to?
- Was that Ea derived from drift data at multiple stress temperatures, or is it an assumed default? If assumed, what value and rationale?
- Do you have drift data at more than one stress temperature? That's what would let us fit Ea directly rather than rely on a default.
- Can you share the underlying HTOL/reliability qual report with the drift vs. time vs. temperature dataset, including the unit-to-unit distribution (not just typical)?
- Since 125°C sits above the ~105°C point where SNOA994 notes a plain Arrhenius fit starts to break down, do you recommend a specific Ea (or a different model) for extrapolating from 125°C to ~37°C?
