Toward Electrochemical Studies on the Nanometer and Atomic Scales: Progress, Challenges, and Opportunities.
Sergei V KalininOndrej DyckNina Balke WisingerSabine M NeumayerWan-Yu TsaiRama VasudevanDavid B LingerfeltMahshid AhmadiMaxim ZiatdinovMatthew T McDowellEvgheni StrelcovPublished in: ACS nano (2019)
Electrochemical reactions and ionic transport underpin the operation of a broad range of devices and applications, from energy storage and conversion to information technologies, as well as biochemical processes, artificial muscles, and soft actuators. Understanding the mechanisms governing function of these applications requires probing local electrochemical phenomena on the relevant time and length scales. Here, we discuss the challenges and opportunities for extending electrochemical characterization probes to the nanometer and ultimately atomic scales, including challenges in down-scaling classical methods, the emergence of novel probes enabled by nanotechnology and based on emergent physics and chemistry of nanoscale systems, and the integration of local data into macroscopic models. Scanning probe microscopy (SPM) methods based on strain detection, potential detection, and hysteretic current measurements are discussed. We further compare SPM to electron beam probes and discuss the applicability of electron beam methods to probe local electrochemical behavior on the mesoscopic and atomic levels. Similar to a SPM tip, the electron beam can be used both for observing behavior and as an active electrode to induce reactions. We briefly discuss new challenges and opportunities for conducting fundamental scientific studies, matter patterning, and atomic manipulation arising in this context.
Keyphrases
- electron microscopy
- label free
- gold nanoparticles
- living cells
- ionic liquid
- single molecule
- molecularly imprinted
- small molecule
- electron transfer
- fluorescence imaging
- loop mediated isothermal amplification
- quantum dots
- healthcare
- health information
- risk assessment
- case control
- machine learning
- real time pcr
- solar cells