Abstract

Graphene Field-Effect Transistors (GFETs) are increasingly employed as biochemical sensors due to their exceptional electronic properties, surface sensitivity, and potential for miniaturization. A critical challenge in deploying GFETs is determining the optimal electrical readout strategy. GFETs are typically operated with either of two modalities: one measuring current in real time (amperometric) and the other monitoring the change in voltage for charge neutrality (potential potentiometric). Here, we undertake a systematic study of the two modalities to determine their relative advantages/disadvantages towards guiding the future use of GFETs in sensing. We focus on viral proteins in wastewater, given the matrix's complexity and the growing interest in the field of wastewater surveillance. Our results show that transconductance offers far superior limits of detection (LOD) but suffers from limited reproducibility, a narrower dynamic range, and is ineffective for some viral proteins. In comparison, we find that Dirac point tracking offers higher reproducibility and superior robustness, but at a higher LOD. Interestingly, both techniques exhibit similar sensitivity, highlighting the importance of the aptamers employed. Systematic experiments also help explain differences in dynamic range and limited functionality in detecting some proteins, resulting from hidden electrophoresis, and shifting the high transconductance point away from the active region. Thus, our findings provide crucial considerations for designing and operating resilient graphene biosensors suitable for real-time pathogen monitoring in environmental scenarios.

Abstract

Graphene Field-Effect Transistors (GFETs) are increasingly employed as biochemical sensors due to their exceptional electronic properties, surface sensitivity, and potential for miniaturization. A critical challenge in deploying GFETs is determining the optimal electrical readout strategy. GFETs are typically operated with either of two modalities: one measuring current in real time (amperometric) and the other monitoring the change in voltage for charge neutrality (potential potentiometric). Here, we undertake a systematic study of the two modalities to determine their relative advantages/disadvantages towards guiding the future use of GFETs in sensing. We focus on viral proteins in wastewater, given the matrix's complexity and the growing interest in the field of wastewater surveillance. Our results show that transconductance offers far superior limits of detection (LOD) but suffers from limited reproducibility, a narrower dynamic range, and is ineffective for some viral proteins. In comparison, we find that Dirac point tracking offers higher reproducibility and superior robustness, but at a higher LOD. Interestingly, both techniques exhibit similar sensitivity, highlighting the importance of the aptamers employed. Systematic experiments also help explain differences in dynamic range and limited functionality in detecting some proteins, resulting from hidden electrophoresis, and shifting the high transconductance point away from the active region. Thus, our findings provide crucial considerations for designing and operating resilient graphene biosensors suitable for real-time pathogen monitoring in environmental scenarios.

Abstract

Graphene Field-Effect Transistors (GFETs) are increasingly employed as biochemical sensors due to their exceptional electronic properties, surface sensitivity, and potential for miniaturization. A critical challenge in deploying GFETs is determining the optimal electrical readout strategy. GFETs are typically operated with either of two modalities: one measuring current in real time (amperometric) and the other monitoring the change in voltage for charge neutrality (potential potentiometric). Here, we undertake a systematic study of the two modalities to determine their relative advantages/disadvantages towards guiding the future use of GFETs in sensing. We focus on viral proteins in wastewater, given the matrix's complexity and the growing interest in the field of wastewater surveillance. Our results show that transconductance offers far superior limits of detection (LOD) but suffers from limited reproducibility, a narrower dynamic range, and is ineffective for some viral proteins. In comparison, we find that Dirac point tracking offers higher reproducibility and superior robustness, but at a higher LOD. Interestingly, both techniques exhibit similar sensitivity, highlighting the importance of the aptamers employed. Systematic experiments also help explain differences in dynamic range and limited functionality in detecting some proteins, resulting from hidden electrophoresis, and shifting the high transconductance point away from the active region. Thus, our findings provide crucial considerations for designing and operating resilient graphene biosensors suitable for real-time pathogen monitoring in environmental scenarios.

Abstract

Graphene Field-Effect Transistors (GFETs) are increasingly employed as biochemical sensors due to their exceptional electronic properties, surface sensitivity, and potential for miniaturization. A critical challenge in deploying GFETs is determining the optimal electrical readout strategy. GFETs are typically operated with either of two modalities: one measuring current in real time (amperometric) and the other monitoring the change in voltage for charge neutrality (potential potentiometric). Here, we undertake a systematic study of the two modalities to determine their relative advantages/disadvantages towards guiding the future use of GFETs in sensing. We focus on viral proteins in wastewater, given the matrix's complexity and the growing interest in the field of wastewater surveillance. Our results show that transconductance offers far superior limits of detection (LOD) but suffers from limited reproducibility, a narrower dynamic range, and is ineffective for some viral proteins. In comparison, we find that Dirac point tracking offers higher reproducibility and superior robustness, but at a higher LOD. Interestingly, both techniques exhibit similar sensitivity, highlighting the importance of the aptamers employed. Systematic experiments also help explain differences in dynamic range and limited functionality in detecting some proteins, resulting from hidden electrophoresis, and shifting the high transconductance point away from the active region. Thus, our findings provide crucial considerations for designing and operating resilient graphene biosensors suitable for real-time pathogen monitoring in environmental scenarios.