Accurate and rapid antibiotic susceptibility testing using a machine learning-assisted nanomotion technology platform.

Antimicrobial resistance (AMR) is a major public health threat, reducing treatment options for infected patients. AMR is promoted by a lack of access to rapid antibiotic susceptibility tests (ASTs). Accelerated ASTs can identify effective antibiotics for treatment in a timely and informed manner. We describe a rapid growth-independent phenotypic AST that uses a nanomotion technology platform to measure bacterial vibrations. Machine learning techniques are applied to analyze a large dataset encompassing 2762 individual nanomotion recordings from 1180 spiked positive blood culture samples covering 364 Escherichia coli and Klebsiella pneumoniae isolates exposed to cephalosporins and fluoroquinolones. The training performances of the different classification models achieve between 90.5 and 100% accuracy. Independent testing of the AST on 223 strains, including in clinical setting, correctly predict susceptibility and resistance with accuracies between 89.5% and 98.9%. The study shows the potential of this nanomotion platform for future bacterial phenotype delineation.

Nanomotion technology in combination with machine learning: a new approach for a rapid antibiotic susceptibility test for Mycobacterium tuberculosis.

Nanomotion technology is a growth-independent approach that can be used to detect and record the vibrations of bacteria attached to cantilevers. We have developed a nanomotion-based antibiotic susceptibility test (AST) protocol for Mycobacterium tuberculosis (MTB). The protocol was used to predict strain phenotype towards isoniazid (INH) and rifampicin (RIF) using a leave-one-out cross-validation (LOOCV) and machine learning techniques. This MTB-nanomotion protocol takes 21 h, including cell suspension preparation, optimized bacterial attachment to functionalized cantilever, and nanomotion recording before and after antibiotic exposure. We applied this protocol to MTB isolates (n = 40) and were able to discriminate between susceptible and resistant strains for INH and RIF with a maximum sensitivity of 97.4% and 100%, respectively, and a maximum specificity of 100% for both antibiotics when considering each nanomotion recording to be a distinct experiment. Grouping recordings as triplicates based on source isolate improved sensitivity and specificity to 100% for both antibiotics. Nanomotion technology can potentially reduce time-to-result significantly compared to the days and weeks currently needed for current phenotypic ASTs for MTB. It can further be extended to other anti-TB drugs to help guide more effective TB treatment.

Carrier density distribution in silicon nanowires investigated by scanning thermal microscopy and Kelvin probe force microscopy.

The use of scanning thermal microscopy (SThM) and Kelvin probe force microscopy (KPFM) to investigate silicon nanowires (SiNWs) is presented. SThM allows imaging of temperature distribution at the nanoscale, while KPFM images the potential distribution with AFM-related ultra-high spatial resolution. Both techniques are therefore suitable for imaging the resistance distribution. We show results of experimental examination of dual channel n-type SiNWs with channel width of 100 nm, while the channel was open and current was flowing through the SiNW. To investigate the carrier distribution in the SiNWs we performed SThM and KPFM scans. The SThM results showed non-symmetrical temperature distribution along the SiNWs with temperature maximum shifted towards the contact of higher potential. These results corresponded to those expressed by the distribution of potential gradient along the SiNWs, obtained using the KPFM method. Consequently, non-uniform distribution of resistance was shown, being a result of non-uniform carrier density distribution in the structure and showing the pinch-off effect. Last but not least, the results were also compared with results of finite-element method modeling.

Scanning probe microscopy investigations of the electrical properties of chemical vapor deposited graphene grown on a 6H-SiC substrate.

Sublimated graphene grown on SiC is an attractive material for scientific investigations. Nevertheless the self limiting process on the Si face and its sensitivity to the surface quality of the SiC substrates may be unfavourable for later microelectronic processes. On the other hand, chemical vapor deposited (CVD) graphene does not posses such disadvantages, so further experimental investigation is needed. In this paper CVD grown graphene on 6H-SiC (0001) substrate was investigated using scanning probe microscopy (SPM). Electrical properties of graphene were characterized with the use of: scanning tunnelling microscopy, conductive atomic force microscopy (C-AFM) with locally performed C-AFM current-voltage measurements and Kelvin probe force microscopy (KPFM). Based on the contact potential difference data from the KPFM measurements, the work function of graphene was estimated. We observed conductance variations not only on structural edges, existing surface corrugations or accidental bilayers, but also on a flat graphene surface.

Investigation of thermal effects in through-silicon vias using scanning thermal microscopy.

Results of quantitative investigations of copper through-silicon vias (TSVs) are presented. The experiments were performed using scanning thermal microscopy (SThM), enabling highly localized imaging of thermal contrast between the copper TSVs and the surrounding material. Both dc and ac active-mode SThM was used and differences between these variants are shown. SThM investigations of TSVs may provide information on copper quality in TSV, as well as may lead to quantitative investigation of thermal boundaries in micro- and nanoelectronic structures. A proposal for heat flow analysis in a TSV, which includes the influence of the boundary region between the TSV and the silicon substrate, is presented; estimation of contact resistance and boundary thermal conductance is also given.

Thermal mapping of a scanning thermal microscopy tip.

Scanning thermal microscopy (SThM) is a very promising technique for local investigation of temperature and thermal properties of nanostructures with great application potential in contemporary nanoelectronics and nanotechnology. In order to increase the localization of SThM measurements, the size of probes has recently substantially decreased, which results in novel types of SThM probes manufactured with the use of modern silicon microfabrication technology. Quantitative SThM measurements with these probes need methods, which enable to assess the quality of thermal contact between the probe and the investigated surface. In this paper we propose a tip thermal mapping (TThM) procedure, which is used to estimate experimentally the distribution of power dissipated by the tip of an SThM probe. We also show that the proposed power dissipation model explains the results of active-mode SThM measurements and that the TThM procedure is reversible for a given probe and sample.