Multi-dimensional microwave sensing using graphene waveguides

This paper presents an electrolytically gated broadband microwave sensor where atomically-thin graphene layers are integrated into coplanar waveguides and coupled with microfluidic channels. The interaction between a solution under test and the graphene surface causes material and concentration-specific modifications of graphene's DC and AC conductivity. Moreover, wave propagation in the waveguide is modified by the dielectric properties of materials in its close proximity via the fringe field, resulting in a combined sensing mechanism leading to an enhanced S-parameter response compared to metallic microwave sensors. The possibility of further controlling the graphene conductivity via an electrolytic gate enables a new, multi-dimensional approach merging chemical field-effect sensing and microwave measurement methods. By controlling and synchronizing frequency sweeps, electrochemical gating and liquid flow in the microfluidic channel, we generate multidimensional datasets that enable a thorough investigation of the solution under study. As proof of concept, we functionalize the graphene surface in order to identify specific single-stranded DNA sequences dispersed in phosphate buffered saline solution. We achieve a limit of detection of ~1 attomole per litre for a perfect match DNA strand and a sensitivity of ~3 dB/decade for sub-pM concentrations. These results show that our devices represent a new and accurate metrological tool for chemical and biological sensing

Atomically thin microwave biosensors

This thesis described the development of a new type of biosensor based on the integration of atomically thin graphene in a broadband radio-frequency (RF) coplanar waveguide (CPW). To combine both electrochemical and dielectric sensing concepts, a graphene channel is inserted into the CPW, which can then be functionalised using standard chemical processes developed for graphene direct-current (DC) sensors. The new RF sensors shown in this work inherit the strong response of graphene at low analyte concentrations, while enabling RF methods at concentrations not possible before. This is shown by limit of the detection for glucose, based on RF measurements, several orders of magnitude lower than that previously reported in literature, enabling measurements of glucose at levels found in human sweat. The combined effect of the two sensing responses can be seen as the high sensitivity at low concentrations, 7.30 dB/(mg/L), significantly higher than metallic state-of-the-art RF sensors, which gradually decreases as the graphene saturates and the response at higher concentrations aligns with that of previously reported metal sensors. This shows the extended operating range of the new sensors compared to the literature state-of-the-art. Similarly, for DNA strands, the graphene CPW sensors was able to distinguish between different types of DNA (perfect match, single mutation, and complete mismatch) at the limit of detection, 1 aΜ, improving the concentration response by orders of magnitude compared to existing RF DNA sensors and allowing for distinction of the types at lower concentration than those in contemporary DC graphene sensors. The additional effect of tunable graphene conductivity independently of the analyte, is the creation of multidimensional datasets for each *S*-parameter component by combining the frequency and potential responses. The resultant sensor response surfaces contain more information that can be used to determine the concentration and type of the analyte. In particular for DNA, the multidimensional approach, by considering the frequency and biasing condition for the largest joint changes in the parameters allowed for direct classification of the three DNA analyte types based on the sign of the changes in the parameters ($ℜ/ℑS_{ij}$ or $mag/∠S_{ij}$). Because of the multidimensional nature of the dataset, machine learning algorithms could be applied to extract features used for determining concentrations based on the raw measurements. For glucose the concentration was predicted with larger than 98% confidence, while the more feature-rich surfaces of the DNA response allowed the determination of the analyte type at 1 aΜ even with a simulated signal-to-noise ratio of 10 dB, proving the utility and resilience of the developed devices and measurement approach. The above approaches were only enabled by the new type of sensor combining both graphenes electronic properties and RF sensing concepts in a single device.EPSRC grant EP/L016087/

Determination of calibration function for fatigue crack propagation by measurment[!] surface deformation

Components and structures exposed to elastic dynamic loading respond with elastic strains on the surface of the material. Mechanical response could be monitored by deformations on the surface. The measurements and monitoring of these parameters could be performed with electronic devices for on-line measurements, controlled by computerized systems. In the case of fatigue crack initiation and propagation the cyclic strain amplitude deviated from initial strain response (mean value and amplitude). Implementation of appropriate monitoring system supported by computerized programs for evaluation, analyses and activation represent important means to safe service component or construction. To evaluate flaw depth growth, the strain gauge measuring sensors could be used. These sensors measure surface deformation relaxation due to flaw depth growth. The monitoring of the material under cyclic loading could be performed with experimentally determined calibration curve, representing deformation on the surface and depth of the semi-elliptical crack growth on the surface or cross section of the material. The goal of this paper is describe electronic device and experimental procedure in order to determine calibration function

Graphene for Biosensing Applications in Point-of-Care Testing.

Graphene and graphene-related materials (GRMs) exhibit a unique combination of electronic, optical, and electrochemical properties, which make them ideally suitable for ultrasensitive and selective point-of-care testing (POCT) devices. POCT device-based applications in diagnostics require test results to be readily accessible anywhere to produce results within a short analysis timeframe. This review article provides a summary of methods and latest developments in the field of graphene and GRM-based biosensing in POCT and an overview of the main applications of the latter in nucleic acids and enzymatic biosensing, cell detection, and immunosensing. For each application, we discuss scientific and technological advances along with the remaining challenges, outlining future directions for widespread use of this technology in biomedical applications

Highly Sensitive Glucose Sensors Based on Gated Graphene Microwave Waveguides

Publication status: PublishedAbstractA novel approach is demonstrated to identify glucose concentration in aqueous solutions based on the combined effect of its frequency‐dependent interaction with microwaves propagating in graphene channels and the modification of graphene radio frequency (RF) conductivity caused by physisorbed molecules. This approach combines broadband microwave sensing and chemical field effect transistor sensing in a single device, leading to information‐rich, multidimensional datasets in the form of scattering parameters. A sensitivity of 7.30 dB(mg/L)−1 is achieved, significantly higher than metallic state‐of‐the‐art RF sensors. Different machine learning methods are applied to the raw, multidimensional datasets to infer concentrations of the analyte, without the need for parasitic effect removals via de‐embedding or circuit modeling, and a classification accuracy of 100% is achieved for aqueous glucose solutions with a concentration variation of 0.09 mgL−1.</jats:p

Electrochemically-gated Graphene Broadband Microwave Waveguides for Ultrasensitive Biosensing

Identification of non-amplified DNA sequences and single-base mutations is essential for molecular biology and genetic diagnostics. This paper reports a novel sensor consisting of electrochemically-gated graphene coplanar waveguides coupled with a microfluidic channel. Upon exposure to analytes, propagation of electromagnetic waves in the waveguides is modified as a result of interactions with the fringing field and modulation of graphene dynamic conductivity resulting from electrostatic gating. Probe DNA sequences are immobilised on the graphene surface, and the sensor is exposed to DNA sequences which either perfectly match the probe, contain a singlebase mismatch or are unrelated. By monitoring the scattering parameters at frequencies between 50 MHz and 50 GHz, unambiguous and reproducible discrimination of the different strands is achieved at concentrations as low as 1 attomole per litre (1 aM). By controlling and synchronising frequency sweeps, electrochemical gating, and liquid flow in the microfluidic channel, the sensor generates multidimensional datasets. Advanced data analysis techniques are utilised to take full advantage of the richness of the dataset. A classification accuracy &gt; 97% between all three sequences is achieved using different Machine Learning models, even in the presence of simulated noise and low signal-to-noise ratios. The sensor exceeds state-of-the-art sensitivity of field-effect transistors and microwave sensors for the identification of single-base mismatches

The biaxial strain dependence of magnetic order in spin frustrated mn3nin thin films

Multi-component magnetic phase diagrams are a key property of functional materials for a variety of uses, such as manipulation of magnetisation for energy efficient memory, data storage and cooling applications. Strong spin-lattice coupling extends this functionality further by allowing electric-field-control of magnetisation via strain coupling with a piezoelectric . Here we explore the magnetic phase diagram of piezomagnetic Mn3NiN thin films, with a frustrated non-collinear antiferromagnetic (AFM) structure, as a function of the growth induced biaxial strain. Under compressive strain the films support a canted AFM state with large coercivity of the transverse anomalous Hall resistivity, ρxy, at low temperature, that transforms at a well-defined Néel transition temperature (TN) into a soft ferrimagnetic-like (FIM) state at high temperatures. In stark contrast, under tensile strain the low temperature canted AFM phase transitions to a state where ρxy is an order of magnitude smaller and therefore consistent with a low magnetisation phase. Neutron scattering confirms that the high temperature FIM-like phase of compressively strained films is magnetically ordered and the transition at TN is 1st-order. Our results open the field towards future exploration of electric-field driven piezospintronic and thin film caloric cooling applications in both Mn3NiN itself and the broader Mn3AN family