Next-Generation Diamond Electrodes for Neurochemical Sensing: Challenges and Opportunities

Evaluation of In Vitro Serotonin-Induced Electrochemical Fouling Performance of Boron Doped Diamond Microelectrode Using Fast-Scan Cyclic Voltammetry

Fast-scan cyclic voltammetry (FSCV) is an electrochemical sensing technique that can be used for neurochemical sensing with high spatiotemporal resolution. Carbon fiber microelectrodes (CFMEs) are traditionally used as FSCV sensors. However, CFMEs are prone to electrochemical fouling caused by oxidative byproducts of repeated serotonin (5-HT) exposure, which makes them less suitable as chronic 5-HT sensors. Our team is developing a boron-doped diamond microelectrode (BDDME) that has previously been shown to be relatively resistant to fouling caused by protein adsorption (biofouling). We sought to determine if this BDDME exhibits resistance to electrochemical fouling, which we explored on electrodes fabricated with either femtosecond laser cutting or physical cleaving. We recorded the oxidation current response after 25 repeated injections of 5-HT in a flow-injection cell and compared the current drop from the first with the last injection. The 5-HT responses were compared with dopamine (DA), a neurochemical that is known to produce minimal fouling oxidative byproducts and has a stable repeated response. Physical cleaving of the BDDME yielded a reduction in fouling due to 5-HT compared with the CFME and the femtosecond laser cut BDDME. However, the femtosecond laser cut BDDME exhibited a large increase in sensitivity over the cleaved BDDME. An extended stability analysis was conducted for all device types following 5-HT fouling tests. This analysis demonstrated an improvement in the long-term stability of boron-doped diamond over CFMEs, as well as a diminishing sensitivity of the laser-cut BDDME over time. This work reports the electrochemical fouling performance of the BDDME when it is repeatedly exposed to DA or 5-HT, which informs the development of a chronic, diamond-based electrochemical sensor for long-term neurotransmitter measurements in vivo.

Stability Study of Synthetic Diamond Using a Thermally Controlled Biological Environment: Application towards Long-Lasting Neural Prostheses

This paper demonstrates, for the first time, the stability of synthetic diamond as a passive layer within neural implants. Leveraging the exceptional biocompatibility of intrinsic nanocrystalline diamond, a comprehensive review of material aging analysis in the context of in-vivo implants is provided. This work is based on electric impedance monitoring through the formulation of an analytical model that scrutinizes essential parameters such as the deposited metal resistivity, insulation between conductors, changes in electrode geometry, and leakage currents. The evolution of these parameters takes place over an equivalent period of approximately 10 years. The analytical model, focusing on a fractional capacitor, provides nuanced insights into the surface conductivity variation. A comparative study is performed between a classical polymer material (SU8) and synthetic diamond. Samples subjected to dynamic impedance analysis reveal distinctive patterns over time, characterized by their physical degradation. The results highlight the very high stability of diamond, suggesting promise for the electrode's enduring viability. To support this analysis, microscopic and optical measurements conclude the paper and confirm the high stability of diamond and its strong potential as a material for neural implants with long-life use.

Analytical Determination of Serotonin Exocytosis in Human Platelets with BDD-on-Quartz MEA Devices

Amperometry is arguably the most widely used technique for studying the exocytosis of biological amines. However, the scarcity of human tissues, particularly in the context of neurological diseases, poses a challenge for exocytosis research. Human platelets, which accumulate 90% of blood serotonin, release it through exocytosis. Nevertheless, single-cell amperometry with encapsulated carbon fibers is impractical due to the small size of platelets and the limited number of secretory granules on each platelet. The recent technological improvements in amperometric multi-electrode array (MEA) devices allow simultaneous recordings from several high-performance electrodes. In this paper, we present a comparison of three MEA boron-doped diamond (BDD) devices for studying serotonin exocytosis in human platelets: (i) the BDD-on-glass MEA, (ii) the BDD-on-silicon MEA, and (iii) the BDD on amorphous quartz MEA (BDD-on-quartz MEA). Transparent electrodes offer several advantages for observing living cells, and in the case of platelets, they control activation/aggregation. BDD-on-quartz offers the advantage over previous materials of combining excellent electrochemical properties with transparency for microscopic observation. These devices are opening exciting perspectives for clinical applications.

Editors' Choice-Review-The Future of Carbon-Based Neurochemical Sensing: A Critical Perspective

Carbon-based sensors have remained critical materials for electrochemical detection of neurochemicals, rooted in their inherent biocompatibility and broad potential window. Real-time monitoring using fast-scan cyclic voltammetry has resulted in the rise of minimally invasive carbon fiber microelectrodes as the material of choice for making measurements in tissue, but challenges with carbon fiber's innate properties have limited its applicability to understudied neurochemicals. Here, we provide a critical review of the state of carbon-based real-time neurochemical detection and offer insight into ways we envision addressing these limitations in the future. This piece focuses on three main hinderances of traditional carbon fiber based materials: diminished temporal resolution due to geometric properties and adsorption/desorption properties of the material, poor selectivity/specificity to most neurochemicals, and the inability to tune amorphous carbon surfaces for specific interfacial interactions. Routes to addressing these challenges could lie in methods like computational modeling of single-molecule interfacial interactions, expansion to tunable carbon-based materials, and novel approaches to synthesizing these materials. We hope this critical piece does justice to describing the novel carbon-based materials that have preceded this work, and we hope this review provides useful solutions to innovate carbon-based material development in the future for individualized neurochemical structures.

Platinum and palladium nanoparticles on boron-doped diamond for the electrochemical detection of hydrogen peroxide: a comparison study

Hydrogen peroxide (H2O2) plays a role in many facets - a household item, an important industrial chemical, a biomarker in vivo, and several others. For this reason, its measurement and quantification in a variety of media are important. While spectroscopic detection is primarily used for H2O2, electrochemical methods offer advantages in versatility, cost, and sensitivity. In this work, we investigate a 2-step surface metal nanoparticle (NP) modification for platinum (Pt) and palladium (Pd) on boron-doped diamond (BDD) electrodes for the detection of H2O2. Several parameters such as the metal salt concentration and electrodeposition charge in the 2-step modification were varied to find an optimum. Using cyclic voltammetry (CV), the BDD-PdNP electrode types were found to yield a sharper, more well-resolved H2O2 oxidation peak compared to the BDD-PtNP electrodes. Both metal NP electrode types significantly improved the response compared to the bare BDD electrode; a 150-200× improvement in sensitivity was observed across all modified electrode types. Calibration experiments were completed at both low and high concentration ranges in stagnant and flow-based solutions. The lowest limit of detection (LOD) obtained was 50 nM (5E-08 M) on a BDD-PdNP electrode modified with 1.0 mM PdCl2 to 5.0 mC in the wet chemical seeding and electrodeposition steps. 0.25 mM PdCl2 to 3.23 mC and 0.25 mM HPtCl6- to 3.23 mC also yielded a sufficient response for low-level H2O2, with LODs around 100 nM (1E-07 M). Overall, this work exemplifies the wide applicability of BDD and achieves sub-μM H2O2 LODs with a non-enzymatic electrode material.

In Vitro Biofouling Performance of Boron-Doped Diamond Microelectrodes for Serotonin Detection Using Fast-Scan Cyclic Voltammetry

Neurotransmitter release is important to study in order to better understand neurological diseases and treatment approaches. Serotonin is a neurotransmitter known to play key roles in the etiology of neuropsychiatric disorders. Fast-scan cyclic voltammetry (FSCV) has enabled the detection of neurochemicals, including serotonin, on a sub-second timescale via the well-established carbon fiber microelectrode (CFME). However, poor chronic stability and biofouling, i.e., the adsorption of interferent proteins to the electrode surface upon implantation, pose challenges in the natural physiological environment. We have recently developed a uniquely designed, freestanding, all-diamond boron-doped diamond microelectrode (BDDME) for electrochemical measurements. Key potential advantages of the device include customizable electrode site layouts, a wider working potential window, improved stability, and resistance to biofouling. Here, we present a first report on the electrochemical behavior of the BDDME in comparison with CFME by investigating in vitro serotonin (5-HT) responses with varying FSCV waveform parameters and biofouling conditions. While the CFME delivered lower limits of detection, we also found that BDDMEs showed more sustained 5-HT responses to increasing or changing FSCV waveform-switching potential and frequency, as well as to higher analyte concentrations. Biofouling-induced current reductions were significantly less pronounced at the BDDME when using a "Jackson" waveform compared to CFMEs. These findings are important steps towards the development and optimization of the BDDME as a chronically implanted biosensor for in vivo neurotransmitter detection.

Pascual L, Peltola E, Sainio J, Laurila T. Modulating the Geometry of the Carbon Nanofiber Electrodes Provides Control over Dopamine Sensor Performance

One of the major challenges for in vivo electrochemical measurements of dopamine (DA) is to achieve selectivity in the presence of interferents, such as ascorbic acid (AA) and uric acid (UA). Complicated multimaterial structures and ill-defined pretreatments have been frequently utilized to enhance selectivity. The lack of control over the realized structures has prevented establishing associations between the achieved selectivity and the electrode structure. Owing to their easily tailorable structure, carbon nanofiber (CNF) electrodes have become promising materials for neurobiological applications. Here, a novel yet simple strategy to control the sensitivity and selectivity of CNF electrodes toward DA is reported. It consists of adjusting the lengths of CNF by modulating the growth phase during the fabrication process while keeping the surface chemistries similar. It was observed that the sensitivity of the CNF electrodes toward DA was enhanced with the increase in the fiber lengths. More importantly, the increase in the fiber length induced (i) an anodic shift in the DA oxidation peak and (ii) a cathodic shift in the AA oxidation peak. As the UA oxidation peak remained unaffected at high anodic potentials, the electrodes with long CNFs showed excellent selectivity. Electrodes without proper fibers showed only a single broad peak in the solution of AA, DA, and UA, completely lacking the ability to discriminate DA. Hence, the simple strategy of controlling CNF length without the need to carry out any complex chemical treatments provides us a feasible and robust route to fabricate electrode materials for neurotransmitter detection with excellent sensitivity and selectivity.

In Vitro Monitoring of Nitric Oxide Release in the Mouse Colon Using a Boron-Doped Diamond Microelectrode Modified with Platinum Nanoparticles and Nafion

This research reports on the preparation of a boron-doped diamond microelectrode modified with platinum nanoparticles and Nafion and its application for detecting nitric oxide (NO) in vitro in the mouse colon. Platinum nanoparticle deposition was performed potentiodynamically using a 2.0 mmol L^-1 potassium hexachloroplatinate solution and cycling from -0.2 to 1.3 V vs Ag/AgCl at 0.01 V s^-1 for 10 cycles. The Nafion overlayer was applied by immersion in a solution containing 2.5% (w/v) colloidal Nafion and drying overnight at 55 °C in a humid environment. The optimal microelectrode preparation conditions were chosen based on the electrode response for NO oxidation as well as rejection of nitrite (NO₂^-) oxidation, the main interferent in the electrochemical detection of NO in biological media. Detection figures of merit include a sensitivity of 16.7 ± 2.7 mA M^-1 cm^-2 (n = 3 electrodes), a detection limit of 0.5 μmol L^-1 (S/N = 3), and an electrode response reproducibility of 2.5% (RSD). Electrical stimulation and continuous amperometry were used to measure NO release from myenteric ganglia in wild-type male and female mice in response to an increasing number of electrical stimuli to study nitrergic signaling in the colon. We also present preliminary data regarding the use of optogenetics to selectively stimulate nitrergic myenteric neurons using blue light stimulation with a goal of understanding how inhibitory neuromuscular signaling is involved in the myenteric plexus circuitry that controls intestinal motility.

MPCVD-Grown Nanodiamond Microelectrodes with Oxygen Plasma Activation for Neurochemical Applications

Nanodiamonds (NDs) are a carbon nanomaterial that has a diamond core with heteroatoms and defects at the surface. The large surface area, defect sites, and functional groups on NDs make them a promising material for electrochemical sensing. Previously, we dip-coated ND onto carbon-fiber microelectrodes (CFMEs) and found increases in sensitivity, but the coating was sparse. Here, we directly grew thin films of ND on niobium wires using microwave plasma chemical vapor deposition (MP-CVD) to provide full surface coverage. ND microelectrodes show a reliable performance in neurotransmitter detection with good antifouling properties. To improve sensitivity, we oxygen plasma etched ND films to activate the surface and intentionally add defects and oxygen surface functional groups. For fast-scan cyclic voltammetry detection of dopamine, oxygen plasma-etching increases the sensitivity from 21 nA/μM to 90 nA/μM after treatment. Fouling was tested by repeated injections of serotonin or tyramine, and both ND and plasma oxidized nanodiamond (NDO) microelectrodes maintain their currents better compared to CFMEs and therefore are more antifouling. A biofouling test in brain slices shows that ND microelectrodes barely have any current drop, while the more hydrophilic NDO microelectrodes decrease more, but still not as much as CFMEs. Overall, grown ND microelectrodes are promising in neurotransmitter detection with excellent fouling resistance, whereas oxygen plasma etching slightly lowers the fouling resistance but dramatically increases sensitivity.

In vitro electrochemical measurement of serotonin release in the human jejunum mucosa using a diamond microelectrode

We report herein on the use of a boron-doped diamond microelectrode (DME) to record oxidation currents in vitro associated with the release of serotonin from enterochromaffin cells in the epithelium of the human intestinal mucosa.

Diamond-Based Electrodes for Detection of Metal Ions and Anions

Diamond electrodes have long been a well-known candidate in electrochemical analyte detection. Nano- and micro-level modifications on the diamond electrodes can lead to diverse analytical applications. Doping of crystalline diamond allows the fabrication of suitable electrodes towards specific analyte monitoring. In particular, boron-doped diamond (BDD) electrodes have been reported for metal ions, anions, biomolecules, drugs, beverage hazards, pesticides, organic molecules, dyes, growth stimulant, etc., with exceptional performance in discriminations. Therefore, numerous reviews on the diamond electrode-based sensory utilities towards the specified analyte quantifications were published by many researchers. However, reviews on the nanodiamond-based electrodes for metal ions and anions are still not readily available nowadays. To advance the development of diamond electrodes towards the detection of diverse metal ions and anions, it is essential to provide clear and focused information on the diamond electrode synthesis, structure, and electrical properties. This review provides indispensable information on the diamond-based electrodes towards the determination of metal ions and anions.

Carbon-based neural electrodes: promises and challenges

Neural electrodes are primary functional elements of neuroelectronic devices designed to record neural activity based on electrochemical signals. These electrodes may also be utilized for electrically stimulating the neural cells, such that their response can be simultaneously recorded. In addition to being medically safe, the electrode material should be electrically conductive and electrochemically stable under harsh biological environments. Mechanical flexibility and conformability, resistance to crack formation and compatibility with common microfabrication techniques are equally desirable properties. Traditionally, (noble) metals have been the preferred for neural electrode applications due to their proven biosafety and a relatively high electrical conductivity. Carbon is a recent addition to this list, which is far superior in terms of its electrochemical stability and corrosion resistance. Carbon has also enabled 3D electrode fabrication as opposed to the thin-film based 2D structures. One of carbon's peculiar aspects is its availability in a wide range of allotropes with specialized properties that render it highly versatile. These variations, however, also make it difficult to understand carbon itself as a unique material, and thus, each allotrope is often regarded independently. Some carbon types have already shown promising results in bioelectronic medicine, while many others remain potential candidates. In this topical review, we first provide a broad overview of the neuroelectronic devices and the basic requirements of an electrode material. We subsequently discuss the carbon family of materials and their properties that are useful in neural applications. Examples of devices fabricated using bulk and nano carbon materials are reviewed and critically compared. We then summarize the challenges, future prospects and next-generation carbon technology that can be helpful in the field of neural sciences. The article aims at providing a common platform to neuroscientists, electrochemists, biologists, microsystems engineers and carbon scientists to enable active and comprehensive efforts directed towards carbon-based neuroelectronic device fabrication.

Resource-constrained FPGA/DNN co-design

Deep neural networks (DNNs) have demonstrated super performance in most learning tasks. However, a DNN typically contains a large number of parameters and operations, requiring a high-end processing platform for high-speed execution. To address this challenge, hardware-and-software co-design strategies, which involve joint DNN optimization and hardware implementation, can be applied. These strategies reduce the parameters and operations of the DNN, and fit it into a low-resource processing platform. In this paper, a DNN model is used for the analysis of the data captured using an electrochemical method to determine the concentration of a neurotransmitter and the recoding electrode. Next, a DNN miniaturization algorithm is introduced, involving combined pruning and compression, to reduce the DNN resource utilization. Here, the DNN is transformed to have sparse parameters by pruning a percentage of its weights. The Lempel-Ziv-Welch algorithm is then applied to compress the sparse DNN. Next, a DNN overlay is developed, combining the decompression of the DNN parameters and DNN inference, to allow the execution of the DNN on a FPGA on the PYNQ-Z2 board. This approach helps avoid the need for inclusion of a complex quantization algorithm. It compresses the DNN by a factor of 6.18, leading to about 50% reduction in the resource utilization on the FPGA.