RESEARCH: CANCER
FOLDING PROJECT #15405 PROFILE
PROJECT TEAM
Manager(s): Adrija DuttaInstitution: UIUC
WORK UNIT INFO
Atoms: 127,408Core: 0x24
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
PFAS are harmful chemicals found in water that can make people sick. This project looks at how PFAS react with other molecules to find better ways to clean up contaminated water.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
PFAS are contaminants in water that are toxic and can cause several adverse health effects.
We are studying interactions between polymer molecules and PFAS ions and expect these studies to benefit PFAS remediation efforts..
RELATED TERMS GLOSSARY AI BETA
PFAS
Per- and polyfluoroalkyl substances
PFAS are a group of man-made chemicals that are very persistent in the environment and can accumulate in living organisms. They are known to have harmful effects on human health, including liver damage, immune system suppression, and developmental problems.
contaminants
Substances that pollute or contaminate a substance or environment.
Contaminants are substances that are present in an environment where they don't belong and can cause harm to living things. This can include chemicals, pollutants, or biological agents.
toxic
Poisonous or harmful to living organisms.
Toxic substances can cause damage or death to living things. The level of toxicity depends on the substance and the amount of exposure.
remediation
The process of removing or neutralizing pollutants from contaminated environments.
Remediation involves cleaning up polluted areas to make them safe for humans and the environment. This can involve physical removal of contaminants, chemical treatment, or biological processes.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Tuesday, 14 April 2026 06:31:40|
Rank Project |
Model Name Folding@Home Identifier |
Make Brand |
GPU Model |
PPD Average |
Points WU Average |
WUs Day Average |
WU Time Average |
|---|---|---|---|---|---|---|---|
| 1 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 12,244,917 | 71,656 | 170.88 | 0 hrs 8 mins |
| 2 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 11,941,473 | 395,200 | 30.22 | 0 hrs 48 mins |
| 3 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 9,712,608 | 422,264 | 23.00 | 1 hrs 3 mins |
| 4 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 8,030,072 | 71,656 | 112.06 | 0 hrs 13 mins |
| 5 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 8,023,308 | 390,288 | 20.56 | 1 hrs 10 mins |
| 6 | Radeon RX 7900XT/XTX/GRE Navi 31 [Radeon RX 7900XT/XTX/GRE] |
AMD | Navi 31 | 6,967,493 | 140,905 | 49.45 | 0 hrs 29 mins |
| 7 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 6,943,049 | 71,656 | 96.89 | 0 hrs 15 mins |
| 8 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 6,188,350 | 360,594 | 17.16 | 1 hrs 24 mins |
| 9 | TITAN V GV100 [TITAN V] M 12288 |
Nvidia | GV100 | 6,056,872 | 71,656 | 84.53 | 0 hrs 17 mins |
| 10 | Radeon RX 6950 XT Navi 21 [Radeon RX 6950 XT] |
AMD | Navi 21 | 5,728,176 | 71,656 | 79.94 | 0 hrs 18 mins |
| 11 | RTX A4000 GA104GL [RTX A4000] |
Nvidia | GA104GL | 5,194,289 | 71,656 | 72.49 | 0 hrs 20 mins |
| 12 | Radeon RX 9070(XT) Navi 48 [Radeon RX 9070(XT)] |
AMD | Navi 48 | 5,180,088 | 71,656 | 72.29 | 0 hrs 20 mins |
| 13 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 4,964,782 | 70,360 | 70.56 | 0 hrs 20 mins |
| 14 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 4,924,572 | 334,671 | 14.71 | 1 hrs 38 mins |
| 15 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 4,006,561 | 84,740 | 47.28 | 0 hrs 30 mins |
| 16 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 4,004,076 | 310,174 | 12.91 | 1 hrs 52 mins |
| 17 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 3,921,159 | 71,656 | 54.72 | 0 hrs 26 mins |
| 18 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 Super] |
Nvidia | TU106 | 3,857,170 | 71,656 | 53.83 | 0 hrs 27 mins |
| 19 | GeForce RTX 4060 AD107 [GeForce RTX 4060] |
Nvidia | AD107 | 3,815,950 | 99,394 | 38.39 | 0 hrs 38 mins |
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|||||||
| 20 | GeForce RTX 2060 TU106 [Geforce RTX 2060] |
Nvidia | TU106 | 2,617,631 | 159,897 | 16.37 | 1 hrs 28 mins |
| 21 | GeForce RTX 2070 Mobile / Max-Q Refresh TU106M [GeForce RTX 2070 Mobile / Max-Q Refresh] |
Nvidia | TU106M | 2,179,900 | 241,845 | 9.01 | 2 hrs 40 mins |
| 22 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,885,352 | 243,729 | 7.74 | 3 hrs 6 mins |
| 23 | P104-100 GP104 [P104-100] |
Nvidia | GP104 | 1,690,839 | 71,656 | 23.60 | 1 hrs 1 mins |
| 24 | Radeon RX 6600(XT/M) Navi 23 XT-XL [Radeon RX 6600(XT/M)] |
AMD | Navi 23 XT-XL | 1,670,773 | 220,009 | 7.59 | 3 hrs 10 mins |
| 25 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,599,993 | 71,656 | 22.33 | 1 hrs 4 mins |
| 26 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,048,850 | 71,656 | 14.64 | 1 hrs 38 mins |
| 27 | GeForce GTX 1050 LP GP107 [GeForce GTX 1050 LP] 1862 |
Nvidia | GP107 | 491,915 | 71,656 | 6.86 | 3 hrs 30 mins |
| 28 | Quadro K1200 GM107GL [Quadro K1200] |
Nvidia | GM107GL | 141,733 | 71,656 | 1.98 | 12 hrs 8 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Tuesday, 14 April 2026 06:31:40|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|