Embedded Fluidic Sensing and Control with Soft Open‐Cell Foams
Source abstract
Abstract
Abstract The synthesis of soft matter intelligence with circuit‐driven logic has enabled a new class of robots that perform complex tasks or conform to specialized form factors in unique ways that cannot be realized through conventional designs. Translating this hybrid approach to fluidic systems, the present work addresses the need for sheet‐based circuit materials by leveraging the innate porosity of foam—a soft material—to develop pneumatic components that support digital logic, mixed‐signal control, and analog force sensing in wearables and soft robots. Analytical tools and experimental techniques developed in this work serve to elucidate compressible gas flow through porous sheets, and to inform the design of centimeter‐sized foam resistors with fluidic resistances on the order of 109 Pa s m−3. When embedded inside soft robots and wearables, these resistors facilitate diverse functionalities spanning both sensing and control domains, including digital logic using textile logic gates, digital‐to‐analog signal conversion using ladder networks, and analog sensing of forces up to 40 N via compression‐induced changes in resistance. By combining features of both circuit‐based and materials‐based approaches, foam‐enabled fluidic circuits serve as a useful paradigm for future hybrid robotic architectures that fully embody the sensing and computing capabilities of soft fluidic materials.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Soft Robotics and Applications · Micro and Nano Robotics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Mechanical Engineering Rice University 6100 Main St Houston TX 77005 USA
Funding
U.S. Department of Energy · National Science Foundation · Rice University
References (47)
Show source-provided references
1. 10.1038/nature1910010.1038/nature19100 ↗
2. 10.1038/nature1454310.1038/nature14543 ↗
3. 10.1002/adma.20170703510.1002/adma.201707035 ↗
4. 10.1002/admt.20180047710.1002/admt.201800477 ↗
5. 10.1126/scirobotics.abg699410.1126/scirobotics.abg6994 ↗
6. 10.1073/pnas.220981911910.1073/pnas.2209819119 ↗
7. 10.1002/adma.20160497710.1002/adma.201604977 ↗
8. 10.3389/frobt.2021.72070210.3389/frobt.2021.720702 ↗
9. 10.1002/aisy.20210016310.1002/aisy.202100163 ↗
10. 10.1126/scirobotics.aar798610.1126/scirobotics.aar7986 ↗
11. 10.1073/pnas.182067211610.1073/pnas.1820672116 ↗
12. 10.1126/scirobotics.aaw549610.1126/scirobotics.aaw5496 ↗
13. 10.1126/scirobotics.aay262710.1126/scirobotics.aay2627 ↗
14. 10.1073/pnas.220211811910.1073/pnas.2202118119 ↗
15. 10.1002/aisy.20230078510.1002/aisy.202300785 ↗
16. 10.1073/pnas.220592211910.1073/pnas.2205922119 ↗
17. 10.1016/j.matt.2022.06.00210.1016/j.matt.2022.06.002 ↗
18. 10.1063/5.003699110.1063/5.0036991 ↗
19. 10.1002/advs.20200138410.1002/advs.202001384 ↗
20. 10.1038/s41586-021-03623-y10.1038/s41586-021-03623-y ↗
21. 10.1021/accountsmr.1c0007110.1021/accountsmr.1c00071 ↗
22. 10.1126/sciadv.abq438510.1126/sciadv.abq4385 ↗
23. 10.1146/annurev-matsci-080921-10291610.1146/annurev-matsci-080921-102916 ↗
24. 10.1038/s41467-021-21920-y10.1038/s41467-021-21920-y ↗
25. 10.1038/s41586-022-05004-510.1038/s41586-022-05004-5 ↗
26. 10.1038/s41467-018-06491-910.1038/s41467-018-06491-9 ↗
27. 10.1073/pnas.221248912010.1073/pnas.2212489120 ↗
28. 10.1002/advs.20230208010.1002/advs.202302080 ↗
29. 10.1038/s41586-020-03123-510.1038/s41586-020-03123-5 ↗
30. 10.1002/adma.20200693910.1002/adma.202006939 ↗
31. 10.1103/PhysRevLett.130.26820410.1103/PhysRevLett.130.268204 ↗
32. 10.1002/adma.20230148710.1002/adma.202301487 ↗
33. 10.1002/adma.20230110910.1002/adma.202301109 ↗
34. 10.1017/CBO978051180095510.1017/CBO9780511800955 ↗
35. 10.1002/j.1538-7305.1955.tb03765.x10.1002/j.1538-7305.1955.tb03765.x ↗
36. 10.1002/j.1538-7305.1958.tb03883.x10.1002/j.1538-7305.1958.tb03883.x ↗
37. Mano M. M. · 1979
38. Horowitz P. · 2021
39. Incropera F. P. · 2007
40. 10.1038/s41467-023-39691-z10.1038/s41467-023-39691-z ↗
41. 10.1177/0021955X660020011210.1177/0021955X6600200112 ↗
42. 10.1016/j.ijsolstr.2006.12.02510.1016/j.ijsolstr.2006.12.025 ↗
43. 10.1002/adfm.20200742810.1002/adfm.202007428 ↗
44. 10.1016/j.device.2023.10005910.1016/j.device.2023.100059 ↗
45. 10.1126/sciadv.ade245010.1126/sciadv.ade2450 ↗
46. 10.1109/TMECH.2023.324434710.1109/TMECH.2023.3244347 ↗
47. B.Jumet Z. A.Zook D.Xu N.Fino A.Rajappan M. W.Schara J.Berning N.Escobar M. K.O'Malley D. J.Preston in2022 IEEE 5th Int. Conf. on Soft Robotics (RoboSoft) IEEE Piscataway NJ2022 pp.741–746.10.1109/RoboSoft54090.2022.9762149 ↗