Aspen Aerogels (ASPN) Operating Expenses (2013 - 2026)
Aspen Aerogels' Operating Expenses was $32.05 million in Q2 2026, up 5.2% from $30.47 million a year earlier and up 27.6% from the prior quarter.
Aspen Aerogels (ASPN) Operating Expenses (2013 - 2026) Analysis & Trends
On a trailing twelve-month basis, Aspen Aerogels' Operating Expenses was $128.76 million through Jun 30, 2026, down 69.1% year-over-year; for FY2025, it came in at $424.23 million, up 230.5% from FY2024.
- Operating Expenses has now increased for five consecutive years, with a five-year compound annual growth rate of 63.6% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $128.36 million in FY2024 (+21.0%), $106.12 million in FY2023 (+26.0%), $84.22 million in FY2022 (+66.7%) and $50.54 million in FY2021 (+39.7%).
- Quarterly Operating Expenses has moved between $14.57 million (Q3 2021) and $322.15 million (Q1 2025) over five years.
- Compared with a year earlier, Operating Expenses was higher in five of the last eight quarters, with growth averaging 105.4%.
- The best year-over-year quarter for Operating Expenses over five years was Q1 2025 (growth of 885.0%); the worst was Q1 2026 (a decline of 92.2%).
- Per Business Quant data, ASPN's Operating Expenses in the three quarters before Q2 2026 was $25.11 million (Q1 2026), $47.46 million (Q4 2025) and $24.15 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Linde | 235.27 Bn | 218.38 Bn | 4.43 Bn | 928.00 Mn |
| 2 | Corning | 106.79 Bn | 99.92 Bn | 1.63 Bn | 907.00 Mn |
| 3 | Sherwin Williams | 83.92 Bn | 82.96 Bn | 3.34 Bn | 2.10 Bn |
| 4 | Air Products & Chemicals | 68.64 Bn | 66.53 Bn | 1.04 Bn | 3.15 Bn |
| 5 | LyondellBasell Industries | 42.22 Bn | 31.84 Bn | 2.04 Bn | 7.63 Bn |
| 6 | Nutrien | 33.30 Bn | 30.16 Bn | 3.25 Bn | 235.00 Mn |
| 7 | Ppg Industries | 25.14 Bn | 17.94 Bn | 1.81 Bn | 1.15 Bn |
| 8 | International Flavors & Fragrances | 23.95 Bn | 21.65 Bn | 853.00 Mn | 613.00 Mn |
| 9 | Dow | 22.98 Bn | 7.98 Bn | 2.17 Bn | 1.25 Bn |
| 10 | Aspen Aerogels | 452.29 Mn | -180.90 Mn | 3.26 Mn | 32.05 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 32.05 Mn |
| Mar 31, 2026 | 25.11 Mn |
| Dec 31, 2025 | 47.46 Mn |
| Sep 30, 2025 | 24.15 Mn |
| Jun 30, 2025 | 30.47 Mn |
| Mar 31, 2025 | 322.15 Mn |
| Dec 31, 2024 | 32.42 Mn |
| Sep 30, 2024 | 31.64 Mn |
| Jun 30, 2024 | 31.59 Mn |
| Mar 31, 2024 | 32.71 Mn |
| Dec 31, 2023 | 28.24 Mn |
| Sep 30, 2023 | 28.44 Mn |
| Jun 30, 2023 | 25.45 Mn |
| Mar 31, 2023 | 23.99 Mn |
| Dec 31, 2022 | 24.00 Mn |
| Sep 30, 2022 | 21.95 Mn |
| Jun 30, 2022 | 21.44 Mn |
| Mar 31, 2022 | 16.84 Mn |
| Dec 31, 2021 | 14.65 Mn |
| Sep 30, 2021 | 14.57 Mn |
Aspen Aerogels Operating Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=operating-expenses&ticker=ASPN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ASPN", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=ASPN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();