Atomic force microscopy-based infrared spectroscopy (AFM-IR) is a rapidly emerging technique that provides chemical analysis and compositional mapping with spatial resolution far below conventional optical diffraction limits. AFM-IR works by using the tip of an AFM probe to locally detect thermal expansion in a sample resulting from absorption of infrared radiation. AFM-IR thus can provide the spatial resolution of AFM in combination with the chemical analysis and compositional imaging capabilities of infrared spectroscopy. This article briefly reviews the development and underlying technology of AFM-IR, including recent advances, and then surveys a wide range of applications and investigations using AFM-IR. AFM-IR applications that will be discussed include those in polymers, life sciences, photonics, solar cells, semiconductors, pharmaceuticals, and cultural heritage. In the Supporting Information, the authors provide a theoretical section that reviews the physics underlying the AFM-IR measurement and d...

AFM-IR: Technology and Applications in Nanoscale Infrared Spectroscopy and Chemical Imaging

The rise of low-cost sensing for managing air pollution in cities.

Polymer and life science applications of a technique that combines atomic force microscopy (AFM) and infrared (IR) spectroscopy to obtain nanoscale IR spectra and images are reviewed. The AFM-IR spectra generated from this technique contain the same information with respect to molecular structure as conventional IR spectroscopy measurements, allowing significant leverage of existing expertise in IR spectroscopy. The AFM-IR technique can be used to acquire IR absorption spectra and absorption images with spatial resolution on the 50 to 100 nm scale, versus the scale of many micrometers or more for conventional IR spectroscopy. In the life sciences, experiments have demonstrated the capacity to perform chemical spectroscopy at the sub-cellular level. Specifically, the AFM-IR technique provides a label-free method for mapping IR-absorbing species in biological materials. On the polymer side, AFM-IR was used to map the IR absorption properties of polymer blends, multilayer films, thin films for active devices such as organic photovoltaics, microdomains in a semicrystalline polyhydroxyalkanoate copolymer, as well as model pharmaceutical blend systems. The ability to obtain spatially resolved IR spectra as well as high-resolution chemical images collected at specific IR wavenumbers was demonstrated. Complementary measurements mapping variations in sample stiffness were also obtained by tracking changes in the cantilever contact resonance frequency. Finally, it was shown that by taking advantage of the ability to arbitrarily control the polarization direction of the IR excitation laser, it is possible to obtain important information regarding molecular orientation in electrospun nanofibers.

https://journals.sagepub.com/doi/pdf/10.1366/12-06804

AFM-IR: Combining Atomic Force Microscopy and Infrared Spectroscopy for Nanoscale Chemical Characterization

Evaluation of amorphous solid dispersion properties using thermal analysis techniques.

This paper presents a literature review of studies that investigate infrastructure needs to support the market introduction of plug-in electric vehicles (PEVs). It focuses on literature relating to consumer preferences for charging infrastructure, and how consumers interact with and use this infrastructure. This includes studies that use questionnaire surveys, interviews, modelling, GPS data from vehicles, and data from electric vehicle charging equipment. These studies indicate that the most important location for PEV charging is at home, followed by work, and then public locations. Studies have found that more effort is needed to ensure consumers have easy access to PEV charging and that charging at home, work, or public locations should not be free of cost. Research indicates that PEV charging will not impact electricity grids on the short term, however charging may need to be managed when the vehicles are deployed in greater numbers. In some areas of study the literature is not sufficiently mature to draw any conclusions from. More research is especially needed to determine how much infrastructure is needed to support the roll out of PEVs. This paper ends with policy implications and suggests avenues of future research.

/pdf/a-review-of-consumer-preferences-of-and-interactions-with-4evrb8sg2i.pdf

A review of consumer preferences of and interactions with electric vehicle charging infrastructure

https://www.eprints.ncl.ac.uk/file_store/production/208949/C2BEE006-82C3-4A9C-9854-5E464EA1C020.pdf

A probabilistic approach to combining smart meter and electric vehicle charging data to investigate distribution network impacts

https://eprints.ncl.ac.uk/file_store/production/239452/1467580F-3551-4096-A3D0-D0FF84859BCD.pdf

Analysing the usage and evidencing the importance of fast chargers for the adoption of battery electric vehicles

https://eprints.ncl.ac.uk/file_store/production/189336/2632DF19-3C33-46FC-B84A-D990959FAC62.pdf

Analysis of electric vehicle driver recharging demand profiles and subsequent impacts on the carbon content of electric vehicle trips

This study develops a more accurate range prediction for electric vehicles (EVs) resulting in a routing system that could extend the driving range of EVs through calculating the minimum energy route to a destination, based on topography and traffic conditions of the road network. Energy expenditure of EVs under different conditions is derived using high-resolution real-world data from the SwitchEV trial. The SwitchEV trial has recorded the second-by-second driving events of 44 all-electric vehicles covering a distance of over 400 000 miles across the North East of England, between March 2010 and May 2013. Linear models are used to determine the energy expenditure equations and Dijkstra's graph search algorithm is used to find the route minimising energy consumption. The results from this study are being used to better inform the decisions of the smart navigation and eco-driving assist systems in EVs, thus improving the intelligent transport systems provisions for EV drivers. The outputs of the research are twofold: providing more accurate estimations of available range and supporting drivers' optimisation of energy consumption and as a result extending their driving range. Both outputs could help mitigate range anxiety and make EVs a more attractive proposition to potential customers.

https://eprints.ncl.ac.uk/file_store/production/193642/D1E848AC-EA96-4CA2-A4FA-0B0CDBC0A47C.pdf

Graeme Hill

Papers

A probabilistic approach to combining smart meter and electric vehicle charging data to investigate distribution network impacts

Analysing the usage and evidencing the importance of fast chargers for the adoption of battery electric vehicles

Analysis of electric vehicle driver recharging demand profiles and subsequent impacts on the carbon content of electric vehicle trips

Routing systems to extend the driving range of electric vehicles

The role of electric vehicles in near-term mitigation pathways and achieving the UK's carbon budget