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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Effect of Molecular Structure of Quinones and Carbon Electrode Surfaces on the Interfacial Electron Transfer Process

Quinones can undergo thermodynamically reversible proton-coupled electron transfer reactions and are being applied as electroactive compounds in aqueous organic batteries. However, the electrochemical reversibility of these compounds is affected not only by their molecular structure but also by the properties of a carbon-based electrode surface. This study combines experimental and theoretical approaches to understand this dependence. Specifically, we study the electron transfer kinetics of two synthesized quinone derivatives and two commercially available ones with a glassy carbon, a highly ordered pyrolytic graphite, and a high-edge-density graphite electrode (HEDGE). The electrochemical reversibility is notably improved on the HEDGE, which shows a higher density of defects and presents oxygenated functional groups at its surface. The electron transfer kinetics are controlled by adsorbed species onto the HEDGE. Molecular dynamics simulation and quantum mechanics calculations suggest defects with oxygen-containing functional groups, such as C-O and C$=$O, on HEDGE surfaces drive the interaction with the functional groups of the molecules, during physisorption from van der Waals forces. The presence of sulfonic acid side groups and a greater number of aromatic rings in the molecular structure may contribute to a higher stabilization of quinone derivatives on HEDGEs. We propose that high-performance carbon-based electrodes can be obtained without catalysts for organic batteries, by the engineering of carbon-based surfaces with edge-like defects and oxygenated functional groups.

25 ENERGY STORAGE↗
DOE OSTI2022

Atomistic and cluster dynamics modeling of fission gas (Xe) diffusivity in TRISO fuel kernels

TRISO fuel particles are candidates for use in next generation reactors including gas reactors, fluoride salt-cooled high temperature reactors, and micro-reactors. The UCO fuel kernel consists of a uranium dioxide (UO) and uranium carbide mixture. The addition of UC helps suppress the formation of carbon monoxide gas, which led to failures during initial TRISO development. The addition of uranium carbide alters the chemistry of the UO kernel, which is known to influence performance parameters such as fission gas diffusivity, although the impact has not been quantified and no models exist that take the change in chemistry into account. Therefore, better understanding and more accurate models of the impact of chemistry on fuel performance are of high priority. In this paper, a first-principles density functional theory (DFT) and empirical potential based multi-scale study has been carried out to model the diffusivity of fission gas xenon (Xe) in UCO TRISO fuel kernels. The focus is on the UO component in the UCO fuel kernels, as that represents the largest volume fraction of the fuel kernels. The study relies on DFT and empirical potential calculations to determine Xe and point defect properties, which are then used in thermodynamic and kinetic models to predict diffusion for intrinsic conditions. In addition, the information is utilized in cluster dynamics simulations using the Centipede code to estimate the impact of irradiation on defect transport. Additionally, the presence of UC or UC in the UCO fuel kernels is shown to have a substantial impact on the UO non-stoichiometry by inducing oxygen vacancies and driving UO sub-stoichiometric, which causes much slower Xe diffusion in UCO compared to light water reactor UO fuel. The application of this model in fuel performance simulations using the Bison code is also demonstrated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Capture efficiency and bias from the defect dynamics near grain boundaries in BCC Fe using mesoscale simulations

The capture efficiency describes the capability of a sink, such as a grain boundary (GB), dislocation, and void, to absorb point defects (PDs). The bias defines the difference in capture efficiency between the absorption of a vacancy and dumbbell at a sink. Complete kinetic information on PDs, including diffusion barriers and diffusion orientations, as well as accurate saddle points, are needed to determine the capture efficiency and bias at a sink accurately, which is computationally demanding. Here, in the present study, the Self-Evolving Atomistic Kinetic Monte Carlo (SEAKMC) method was used to investigate the defect dynamics of PDs near different types of grain boundaries (GBs) (with both $\langle$100$\rangle$ and $\langle$110$\rangle$ families) accurately in body-centered cubic (BCC) iron (Fe). The capture efficiency, sink strength, and bias factor of different types of GBs were determined in Fe, which, different from traditional rate theory estimation, showed a distinct capture efficiency, sink strength, and bias in different GBs. The results demonstrate a strong positive correlation between the capture efficiency and the GB strain width, instead of the GB misorientation, GB energy, or GB-PD binding energy, which have been investigated previously. This work provides valuable insight into the radiation-induced microstructural evolution of GBs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Role of kinetic energy on Nb 3 Sn thin films by low-temperature co-sputtering

Nb 3 Sn is a promising thin film material for superconducting radio frequency (SRF) applications. Although surface resistivity, critical temperature, and critical field are advantageous in comparison to pure Nb, currently the performance of Nb 3 Sn is lacking behind due to its complex defect structure and phase inhomogeneities. In this work, the influence of the kinetic energy of the deposited particles on the defect structure in Nb 3 Sn thin films synthesized at low temperatures is investigated. A combination of extended x-ray absorption fine structure analysis, x-ray absorption spectroscopy mapping, and transmission electron microscopy reveals an improved local order and elemental homogeneity of the Nb 3 Sn films induced by higher kinetic energies of the elemental species during deposition. Even more, these process conditions lead to suppressed local inhomogeneities at grain boundaries, which can be one of the causes of critically reduced superconducting properties of low temperature sputter-coated Nb 3 Sn thin films. Finally, we show that the magnetic field-induced reduction of critical currents across weak-links formed at grain boundaries can be eliminated by the suggested materials’ synthesis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Structure and Site Evolution of Framework Ni Species in MIL-127 MOFs for Propylene Oligomerization Catalysis

A mixed-valence oxotrimer metal–organic framework (MOF), Ni-MIL-127, with a fully coordinated nickel atom and two iron atoms in the inorganic node, generates a missing linker defect upon thermal treatment in helium (>473 K) to engender an open coordination site on nickel which catalyzes propylene oligomerization devoid of any cocatalysts or initiators. This catalyst is stable for ~20 h on stream at 500 kPa and 473 K, unprecedented for this chemistry. The number of missing linkers on synthesized and activated Ni-MIL-127 MOFs is quantified using temperature-programmed oxidation, 1 H nuclear magnetic resonance spectroscopy, and X-ray absorption spectroscopy to be ~0.7 missing linkers per nickel; thus, a majority of Ni species in the MOF framework catalyze propylene oligomerization. In situ NO titrations under reaction conditions enumerate ~62% of the nickel atoms as catalytically relevant to validate the defect density upon thermal treatment. Propylene oligomerization rates on Ni-MIL-127 measured at steady state have activation energies of 55–67 kJ mol –1 from 448 to 493 K and are first-order in propylene pressures from 5 to 550 kPa. Density functional theory calculations on cluster models of Ni-MIL-127 are employed to validate the plausibility of the missing linker defect and the Cossee–Arlman mechanism for propylene oligomerization through comparisons between apparent activation energies from steady-state kinetics and computation. Here this study illustrates how MOF precatalysts engender defective Ni species which exhibit reactivity and stability characteristics that are distinct and can be engineered to improve catalytic activity for olefin oligomerization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Integrated Direct Air Capture and H₂-Free CO₂ Valorization

This project advances fundamental understanding of a novel integrated direct air capture (DAC) and CO₂ conversion process that valorizes atmospheric CO₂ without external H₂. The research encompasses four critical components: (1) design of task-specific ionic liquids for efficient CO₂ capture under ambient conditions, (2) development of H₂-free tandem catalytic systems using ethane as a reductant, (3) advanced operando characterization to elucidate capture and conversion mechanisms, and (4) data science-driven predictive computation to accelerate material discovery. Over the project period, we developed five high-performance DAC sorbent systems—including CaO/superbase ionic liquid composites, Ni-MOF/Ionic Liquid (IL) hybrids, fluorinated covalent organic frameworks with ion-pair functional groups, defect-engineered UiO-66, and a validated kinetic model for humid-condition operation, achieving CO₂ capacities up to 1.86 mmol/g at 400 ppm with excellent cycling stability. For H₂-free conversion, we constructed atomically synergistic Zn–O–Cr binuclear catalytic sites that achieve 100% ethylene selectivity, ~9.6% ethane conversion, and 99% CO₂ utilization in equimolar co-conversion of ethane and CO₂. We further demonstrated downstream valorization pathways converting CO and C₂H₄ into polyketones and C₃ chemicals. These advances strengthen the scientific foundation for producing value-added materials from ambient CO₂.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Glancing Angle Deposition in Gas Sensing: Bridging Morphological Innovations and Sensor Performances

Glancing Angle Deposition (GLAD) has emerged as a versatile and powerful nanofabrication technique for developing next-generation gas sensors by enabling precise control over nanostructure geometry, porosity, and material composition. Through dynamic substrate tilting and rotation, GLAD facilitates the fabrication of highly porous, anisotropic nanostructures, such as aligned, tilted, zigzag, helical, and multilayered nanorods, with tunable surface area and diffusion pathways optimized for gas detection. This review provides a comprehensive synthesis of recent advances in GLAD-based gas sensor design, focusing on how structural engineering and material integration converge to enhance sensor performance. Key materials strategies include the construction of heterojunctions and core–shell architectures, controlled doping, and nanoparticle decoration using noble metals or metal oxides to amplify charge transfer, catalytic activity, and redox responsiveness. GLAD-fabricated nanostructures have been effectively deployed across multiple gas sensing modalities, including resistive, capacitive, piezoelectric, and optical platforms, where their high aspect ratios, tailored porosity, and defect-rich surfaces facilitate enhanced gas adsorption kinetics and efficient signal transduction. These devices exhibit high sensitivity and selectivity toward a range of analytes, including NO2, CO, H2S, and volatile organic compounds (VOCs), with detection limits often reaching the parts-per-billion level. Emerging innovations, such as photo-assisted sensing and integration with artificial intelligence for data analysis and pattern recognition, further extend the capabilities of GLAD-based systems for multifunctional, real-time, and adaptive sensing. Finally, current challenges and future research directions are discussed, emphasizing the promise of GLAD as a scalable platform for next-generation gas sensing technologies.

Chemistry↗
DOE OSTI2025

Coupled cluster and dislocation dynamics modeling of microstructure evolution in irradiated materials

We develop here a coupled cluster and dislocation dynamics framework to study the microstructure evolution of irradiated materials. The framework not only accounts for the three dimensional diffusion of radiation-generated clusters, but also their interaction with dislocation networks and the resultant climb motion of discrete dislocations within finite crystals. The framework is solved with a superposition solution scheme, and is applied to investigate the evolution of the irradiation-induced dislocation loops in zirconium (Zr), considering the effects of various bias factors including the diffusion anisotropy difference (DAD) of interstitials and interstitial clusters, the dislocation bias of defects to discrete dislocation segments, and the production bias of defects from the radiation cascade. We find that the DAD is the most critical factor influencing the kinetics of the loop evolution in Zr, while the recombination/interaction of mobile defects can induce a strong spatial dependence of the loop evolution together with the DAD. Here, the method is also adopted to study the evolution of interstitial $\langle$a$\rangle$ and vacancy $\langle$c$\rangle$ dislocation loop ensembles consistent with the microstructure observed during irradiation-induced growth of Zr. Our findings not only reveal the spatial dependence of the size and ellipticity of the dislocation loops, but also suggest a limit on the anisotropy factor of interstitials to reproduce the co-growth of $\langle$a$\rangle$ and $\langle$c$\rangle$ loops in zirconium, in good agreement with experimental observations and other simulation results.

Bias factors↗
DOE OSTI2021

Tuning Point Defects by Elastic Strain Modulates Nanoparticle Exsolution on Perovskite Oxides

Exsolution generates stable and catalytically active metal nanoparticles via phase precipitation out of a host oxide. An ability to control the size and dispersion of the exsolution particles is desirable for design of nanostructured (electro)catalysts. In this work, we demonstrate that tuning point defects by lattice strain affects both the thermodynamics and the kinetics of iron (Fe 0 ) exsolution on La 0.6 Sr 0.4 FeO 3 (LSF) thin film model. By combining in situ surface characterization and ab initio defect modeling, we show oxygen vacancy and Schottky defects to be the primary point defects formed upon Fe0 exsolution. Lattice strain tunes the formation energy, and thus the abundance of these defects, and alters the amount and size of the resulting exsolution particles. In addition, we find that the density of exsolved nanoparticles matches the concentration of oxygen vacancy pairs, thus pointing to the surface oxygen vacancy pairs as preferential nucleation sites for exsolution. The tensile-strained LSF with a facile formation of these critical point defects results in a higher Fe 0 metal concentration, a larger density of nanoparticles, and a reduced particle size at its surfaces. These results provide important mechanistic insights and highlight the role of point-defect engineering in designing nanostructured catalysts in energy and fuel conversion technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Machine learning pipeline to predict defect behavior in metallic alloy systems

The interaction between defect and solute atoms is critical to the thermodynamic and kinetic behavior of metallic alloys under exposure to high-energy radiation, causing irradiation damage in materials. Radiation can generate non-equilibrium concentrations of point defects such as vacancies and interstitials. The excess point defects not only accelerate diffusional processes such as precipitation that cause radiation embrittlement, but also change the pathway of phase transformations, including nucleation processes. Understanding these defect behaviors is complicated by the challenge and complexity of addressing each possible local and discrete distribution of environments and chemical interactions around targeted defects-solute or solute-solute complexes. To resolve the challenge, machine learning regression techniques have emerged as powerful tools that can train and construct an energy model to accurately describe the chemical interactions of solutes and defects. In Fiscal Year 2022, the work focused on the workflow development and demonstration using machine learning regression, density functional theory, cluster expansion, and Monte Carlo simulation to predict the effects of ternary solute elements (e.g., aluminum and molybdenum) and point defects on the Cr-rich $\alpha^{\prime}$ precipitation in multicomponent FeCr model alloys. The computational outcomes include the prediction of the ternary phase diagram, vacancy formation energy for different compositions, and the effect of vacancies on the nucleation of Cr-rich clusters. The simulations predict a pronounced change of Cr solubility in bcc Fe by the addition of Al and the rejection of Al atoms from $\alpha^{\prime}$ precipitates. Additionally, the simulations show the formation of Cr-vacancy clusters as the initial nuclei for stable nucleation and growth of $\alpha^{\prime}$ particles. The results demonstrate important outcomes and applications of using machine learning pipeline to study model or commercial alloys with multicomponent solute species and point defects.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Migration energy barriers and diffusion anisotropy of point defects on tungsten surfaces

We report tungsten is one of the most promising candidates for plasma-facing materials in future fusion devices, owing to its high performance under extreme irradiation conditions. However, irradiation-induced surface morphology varies significantly, depending on the irradiation type, fluence, and flux. Therefore, it is critical to examine the dynamics of point defects on tungsten (W) surfaces to understand how irradiation affects surface morphology. In this study, we employ the Self-Evolving Atomistic Kinetic Monte Carlo (SEAKMC) method to search for potential migration paths of point defects on W (1 0 0), (1 1 0) and (1 1 1) surfaces. The first-principles calculations are then used to accurately determine the migration energy barriers. The obtained paths and barriers are incorporated into a kinetic Monte Carlo (KMC) model to determine trajectories and diffusivities, which are described by diffusion tensors to demonstrate their anisotropic features. Multiple diffusion mechanisms have been identified on different surfaces, with various anisotropy factors. Particularly, point defects on the W (1 1 0) surface have the highest diffusivities, with anisotropy factors independent of temperatures. In comparison, the anisotropy of the W (1 0 0) surface decreases as temperature increases, while the W (1 1 1) surface is isotropic for point defects. This study provides insights into defect transport properties on different surfaces, which are essential for understanding the early stages of irradiation-induced microstructural evolutions and surface morphology of tungsten.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Solvent-Free Coating of Organic Semiconductor Membranes with Centimetric Crystalline Domains

Organic semiconductors (OSCs) have shown great promise in a variety of applications. Although solution processing of OSCs has resulted in high-quality films, exquisite control of structural development to minimize defect formation during large-scale fabrication remains formidable. Compounding this challenge is the use of halogenated organic solvents, which poses significant health and environmental hazards. However, the solvent-free techniques introduced thus far impose additional limitations on solidification kinetics; the resulting OSC thin films are often more defective than those processed from solution. Here, a solvent-free technique is reported to prepare OSC membranes with centimetric crystalline domains. Leveraging the tendency for liquid crystalline materials to preferentially orient, OSCs are “prealigned” by depositing them from the melt over a metal frame to form a freely suspended membrane. Additionally, crystallization from this prealigned phase affords membranes with unprecedented structural order across macroscopic distances. Field-effect transistors comprising membranes of dioctyl[1]-benzothieno[3,2-b][1]benzothiophene (C8BTBT) and didodecyl[1]-benzothieno[3,2-b][1]benzothiophene (C12BTBT) having centimeter-sized domains as active layers exhibit a hole mobility of ≈8.6 cm2 V -1 s -1 , superseding the mobility of any transistors whose active layers are deposited from melt. This technique is scalable to yield membranes with large crystalline domains over wafer dimensions, making it amenable for broad applications in large-area organic electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Atomically Revealing Bulk Point Defect Dynamics in Hydrogen‐Driven γ‐Fe 2 O 3 → Fe 3 O 4 → FeO Transformation

Understanding how point defects in the bulk govern redox transformations is essential for advancing hydrogen-based metal production and designing high-performance oxide materials. This study reveals the atomic-scale mechanisms driving hydrogen-induced reduction of γ-Fe 2 O 3 to Fe 3 O 4 , focusing on how bulk vacancy dynamics dictate structural evolution and reaction kinetics. A key finding is the pronounced contrast in defect behavior between the two oxides: in γ-Fe 2 O 3 , intrinsic Fe vacancies promote oxygen vacancy clustering, destabilizing the local lattice and driving nanopore formation. In contrast, Fe 3 O 4 exhibits a higher oxygen vacancy formation energy and lacks intrinsic Fe vacancies, suppressing vacancy aggregation and maintaining a dense, pore-free structure. This divergence governs distinct reduction pathways—γ-Fe 2 O 3 undergoes an interface-reaction-limited transformation confined to the γ-Fe 2 O 3 /Fe 3 O 4 boundary, while Fe 3 O 4 supports a uniform increase in oxygen vacancy concentration, enabling bulk-phase reduction to lower-oxide FeO. Integrated in situ electron microscopy and density functional theory modeling uncover a vacancy-mediated mechanism, where synergistic cation-anion vacancy dynamics steer microstructure evolution and phase progression. These insights highlight the critical role of vacancy dynamics in controlling oxide reactivity and offer a pathway toward vacancy engineering to enhance reduction kinetics in hydrogen metallurgy and to tailor porosity, reactivity, and structural resilience in oxide-based catalysts and energy materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

In Situ Visualization of the Pinning Effect of Planar Defects on Li Ion Insertion

Longevity of Li ion batteries strongly depends on the interaction of transporting Li ions in electrode crystals with defects. However, detailed interactions between the Li ion flux and structural defects in the host crystal remain obscure due to the transient nature of such interactions. Here, by in situ transmission electron microscopy and density function theory calculations, we reveal how the diffusion pathways and transport kinetics of a Li ion can be affected by planar defects in a tungsten trioxide lattice. We uncover that changes in charge distribution and lattice spacing along the planar defects disrupt the continuity of ion conduction channels and dramatically increase the energy barrier of Li diffusion, thus, arresting Li ions at the defect sites and twisting the lithiation front. In conclusion, the atomic-scale understanding holds critical implications for rational interface design in solid-state batteries and solid oxide fuel cells.

25 ENERGY STORAGE↗
DOE OSTI2021

Microstructure-dependent rate theory model of defect segregation and phase stability in irradiated polycrystalline LiAlO 2

We report gamma lithium aluminate (LiAlO 2 ) is a breeder material for tritium and is one of key components in a tritium-producing burnable absorber rod (TPBAR). Dissolution and precipitation of second phases such as LiAl 5 O 8 and voids are observed in irradiated LiAlO 2 . Such microstructure changes cause the degradation of thermomechanical properties of LiAlO 2 and affect tritium retention and release kinetics, and hence, the TPBAR performance. In this work, a microstructure-dependent model of radiation-induced segregation (RIS) has been developed for investigating the accumulation of species and phase stability in polycrystalline LiAlO 2 structures under irradiation. Three sublattices (i.e. [Li, Al, V] I [O, V o ] II [Li i , Al i , O i , V i ] III ), and concentrations of six diffusive species (i.e. Li; vacancy of Li or Al at [Li, Al, V] I sublattice, O vacancy at [O, V o ] II sublattice, and Li, Al and O interstitials at [Li i , Al i , O i , V i ] III interstitial sublattices; are used to describe spatial and temporal distributions of defects and chemistry. Microstructure-dependent thermodynamic and kinetic properties including the generation, reaction, and chemical potentials of defects and defect mobility are taken into account in the model. The parametric studies demonstrated the capability of the developed RIS model to assess the effect of thermodynamic and kinetic properties of defects on the segregation and depletion of species in polycrystalline structures and to explain the phase stability observed in irradiated LiAlO 2 samples. The developed RIS model will be extended to study the precipitation of LiAl 5 O 8 and voids and tritium retention by integrating the phase-field method.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Passive Oxide Film Growth Observed On the Atomic Scale

Despite of the ubiquitous presence of passivation on most metal surfaces, the microscopic-level picture of how surface passivation occurs has been hitherto unclear. Using the canonical example of the surface passivation of aluminum, here we employ in situ atomistic transmission electron microscopy observations and computational modeling to disentangle entangled microscopic processes and identify the atomic processes leading to the surface passivation. Based on atomic-scale observations of the layer-by-layer expansion of the metal lattice and its subsequent transformation into the amorphous oxide, it is shown that the surface passivation occurs via a two-stage oxidation process, in which the first stage is dominated by intralayer atomic shuffling whereas the second stage is governed by interlayer atomic disordering upon the progressive oxygen uptake. The first stage can be bypassed by increasing surface defects to promote the interlayer atomic migration that results in direct amorphization of multiple atomic layers of the metal lattice. The identified two-stage reaction mechanism and the effect of surface defects in promoting interlayer atomic shuffling can find broader applicability in utilizing surface defects to tune the mass transport and passivation kinetics, as well as the composition, structure and transport properties of the passivation films.

25 ENERGY STORAGE↗
DOE OSTI2021

Carbon nanospike coated nanoelectrodes for measurements of neurotransmitters

Here, carbon nanoelectrodes enable the detection of neurotransmitters at the level of single cells, vesicles, synapses and small brain structures. Previously, the etching of carbon fibers and 3D printing based on direct laser writing have been used to fabricate carbon nanoelectrodes, but these methods lack the ability of mass manufacturing. In this paper, we mass fabricate carbon nanoelectrodes by growing carbon nanospikes (CNSs) on metal wires. CNSs have a short, dense and defect-rich surface that produces remarkable electrochemical properties, and they can be mass fabricated on almost any substrate without using catalysts. Tungsten wires and niobium wires were electrochemically etched in batch to form sub micrometer sized tips, and a layer of CNSs was grown on the metal wires using plasma-enhanced chemical vapor deposition (PE-CVD). The thickness of the CNS layer was controlled by the deposition time, and a thin layer of CNSs can effectively cover the entire metal surface while maintaining the tip size within the sub micrometer scale. The etched tungsten wires produced tapered conical nanotips, while the etched niobium wires were long and thin. Both showed excellent sensitivity for the detection of outer sphere ruthenium hexamine and the inner sphere test compound ferricyanide. The CNS nanosensors were used for the measurement of dopamine, serotonin, ascorbic acid and DOPAC with fast-scan cyclic voltammetry. The CNS nanoelectrodes had a large surface area and numerous defect sites, which improved the sensitivity, electron transfer kinetics and adsorption. Finally, the CNS nanoelectrodes were compared with other nanoelectrode fabrication methods, including flame etching, 3D printing, and nanopipettes, which are slower to make and more difficult for mass fabrication. Thus, CNS nanoelectrodes are a promising strategy for the mass fabrication of nanoelectrode sensors for neurotransmitters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗