RESEARCH: CANCER
FOLDING PROJECT #15406 PROFILE

PROJECT TEAM

Manager(s): Adrija Dutta
Institution: UIUC

WORK UNIT INFO

Atoms: 127,408
Core: 0x24
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

PFAS are dangerous chemicals polluting our water and causing health problems. This project looks at how PFAS interact with other molecules to find better ways to clean up PFAS contamination.

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

Note: Glossary items are a high level summary and may not be 100% accurate.

PFAS

Per- and polyfluoroalkyl substances

Acronym: Research & Development
Environmental Science / Water Contamination

PFAS are a group of man-made chemicals that are resistant to breakdown in the environment. They are found in many everyday products and can contaminate water sources. Exposure to PFAS has been linked to various health problems, including liver damage, thyroid disease, and certain cancers.


contaminants

Substances that make water impure or harmful.

Technical: Research & Development
Environmental Science / Water Quality

Contaminants are substances found in the environment that can pose a risk to human health and the ecosystem. These can include chemical pollutants, bacteria, viruses, and even naturally occurring materials in excess.


remediation

The process of cleaning up contaminated sites.

Technical: Research & Development
Environmental Science / Pollution Control

Remediation refers to the actions taken to remove or neutralize pollutants from soil, water, or air. It involves various techniques, such as excavation, filtration, and chemical treatment, aimed at restoring the affected environment to a safe and usable state.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Tuesday, 14 April 2026 06:31:39
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 11,881,059 445,154 26.69 0 hrs 54 mins
2 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 11,699,902 441,892 26.48 0 hrs 54 mins
3 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 8,063,746 393,645 20.48 1 hrs 10 mins
4 Radeon RX 7900XT/XTX/GRE
Navi 31 [Radeon RX 7900XT/XTX/GRE]
AMD Navi 31 7,538,301 71,136 105.97 0 hrs 14 mins
5 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 6,133,103 356,494 17.20 1 hrs 24 mins
6 TITAN V
GV100 [TITAN V] M 12288
Nvidia GV100 6,069,904 71,136 85.33 0 hrs 17 mins
7 Radeon RX 9070(XT)
Navi 48 [Radeon RX 9070(XT)]
AMD Navi 48 5,638,495 71,136 79.26 0 hrs 18 mins
8 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 4,264,236 70,576 60.42 0 hrs 24 mins
9 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 4,227,012 315,510 13.40 1 hrs 47 mins
10 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 Super]
Nvidia TU106 4,034,837 71,136 56.72 0 hrs 25 mins
11 GeForce RTX 4060
AD107 [GeForce RTX 4060]
Nvidia AD107 4,004,766 71,136 56.30 0 hrs 26 mins
12 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 3,975,899 308,746 12.88 1 hrs 52 mins
13 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 3,848,263 71,136 54.10 0 hrs 27 mins
14 Radeon RX 6950 XT
Navi 21 [Radeon RX 6950 XT]
AMD Navi 21 3,831,713 71,136 53.86 0 hrs 27 mins
15 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 2,895,077 134,649 21.50 1 hrs 7 mins
16 Radeon RX 6700(XT)/6800M
Navi 22 XT-XL [Radeon RX 6700(XT)/6800M]
AMD Navi 22 XT-XL 2,443,012 71,136 34.34 0 hrs 42 mins
17 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,947,687 245,260 7.94 3 hrs 1 mins
18 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,780,738 228,490 7.79 3 hrs 5 mins
19 GeForce GTX 1660 Ti
TU116 [GeForce GTX 1660 Ti]
Nvidia TU116 1,677,010 71,136 23.57 1 hrs 1 mins
20 Radeon RX 6600(XT/M)
Navi 23 XT-XL [Radeon RX 6600(XT/M)]
AMD Navi 23 XT-XL 1,657,923 231,265 7.17 3 hrs 21 mins
21 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 1,505,353 71,136 21.16 1 hrs 8 mins
22 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,123,974 76,069 14.78 1 hrs 37 mins
23 GeForce GTX 1050 LP
GP107 [GeForce GTX 1050 LP] 1862
Nvidia GP107 480,254 71,136 6.75 3 hrs 33 mins
24 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 357,974 71,136 5.03 4 hrs 46 mins
25 GeForce GTX 1070 Mobile
GP104BM [GeForce GTX 1070 Mobile] 6463
Nvidia GP104BM 224,337 70,360 3.19 7 hrs 32 mins
26 GeForce GT 1030
GP108 [GeForce GT 1030]
Nvidia GP108 141,733 71,136 1.99 12 hrs 3 mins
27 Quadro K1200
GM107GL [Quadro K1200]
Nvidia GM107GL 137,574 71,136 1.93 12 hrs 25 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Tuesday, 14 April 2026 06:31:39
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make