Material Characterization Methods Research Articles

Uncovering the potential of industrial waste: turning discarded resources into sustainable advanced materials

To identify solutions for utilizing industrial wastes (slag, sludge, fly ash, and bottom ash) in the development of pro-environmental systems, this paper reviews existing literature and explores material characterization methods. A review analysis was conducted to uncover their potential, and it was found that many utilizations can be made to recycle them into sustainable materials. Structure characterization, optical-dielectric function, and morphology analysis were analyzed to confirm the recent review. Structural properties are represented by crystallite size and crystallinity, where nickel slag shows the smallest distribution (55 ± 10) nm with the highest crystallinity (25.42%), indicating its association with uniformity of response to external disturbances and micro-structural stability. From the analysis of optical and dielectric functions via Kramers Kronig relation, the widening of ∆(LO−TO) was shown by fly ash and slag indicating stable bonding suitable as x-ray shielding and sensor, while high electron loss functions were shown by sludge and bottom ash indicating high potential electronic transition performance. Based on their chemical and physical properties, these industrial wastes are not limited as construction materials and can even be upgraded to more advanced development materials.

Fast adaptive focusing confocal Raman microscopy for large-area two-dimensional materials

Large-area two-dimensional (2D) materials possess significant potential in the development of next generation semiconductor due to their unique physicochemical properties. Confocal Raman spectroscopy (CRM), a typical 2D material characterization method, has a limited effective measurement area owing to the restricted focus depth of the system and the less-than-ideal level of the substrate. We propose fast adaptive focusing confocal Raman microscopy (FAFCRM) to realize real-time focusing detection for large-area 2D materials. By observing spot changes on the charge coupled device (CCD) caused by placing an aperture in front of the CCD, the methodology gives a focusing resolution up to 100 nm per 60 μm without axial scanning. A graphene was measured over 25.6 mm × 25.6 mm area on focus through all the scanning. The research results provide new perspectives for non-destructive characterization of 2D materials at the inch level.

From fibers electrospun with honey to the healing of wounds: a review

In order to take advantage of the antiseptic and healing properties of honey, the preparation of polymeric micro and nanofibers with honey from bees has been investigated in many parts of the world, in order to enhance their use in the development of biomedical products such as dressings, bandages and other elements that favor wound closure and tissue restoration. To contribute to this line of research, a background review is presented here on the application of the electrospinning technique in the preparation of micro and nanofiber membranes with honey, focusing on experimental methodology including the use of polymers, solvents, therapeutic agents, active principles or drugs loaded in apitherapeutic fibers. Electrospinning techniques and parameters, tests and material characterization methods have been compiled, presenting the effect of these variables on the compositional, morphological, mechanical and physicochemical properties of the fibrous meshes. A compendium of biological tests evaluated in vitro and in vivo was made in order to analyze the functionality and potential of the application of fibers in tissue engineering, as well as in the construction of devices for clinical diagnosis and in general for the development of advanced materials for wound treatment. This review sees the establishment of the methodological foundations for the design of new materials based on honey and plant extracts not yet explored, and which could be developed into compounds of high scientific and industrial interest.

The Potential for Material Property Characterization Using Physics-Informed Neural Networks and Ultrasonic Wave Data

ABSTRACT There is a need for reliable nondestructive test methods that can collect data from structural members and analyze the results in a rapid and efficient manner. Large amounts of test data are needed to achieve such characterization, which provides additional challenges because of their heterogeneity and complexity. Advances in machine learning, in particular physics-informed neural networks (PINN), offer potential to address these problems. PINN is a particular form of artificial neural networks (ANN) and portends notable advantages over traditional measurand analysis or purely data-driven approaches. Here, we explore the potential of heterogeneous material property characterization using PINN and ultrasonic wave data. First, several types of 1-D ultrasonic wave data are numerically simulated for a spatially heterogeneous material, and then PINN is applied to predict wave velocity, defect location, and energy dissipation. Then, three different types of defects are simulated and all defects are detected using the corresponding 2-D ultrasonic wave data and PINN. The presented results demonstrate the promise of PINN to assist with heterogeneous material characterization methods.

Systematic evaluation of methods for iron-impregnation of biochar and effects on arsenic in flooded soils.

There is a need for innovative strategies to decrease the mobility of metal(loids) including arsenic (As) and cadmium (Cd) in agricultural soils, including rice paddies, so as to minimize dietary exposure to these toxic elements. Iron (Fe)-modified biochars (FBCs) are used to immobilize As and Cd in soil-water systems, but there is a lack of clarity on optimal methods for preparing FBCs because there are only limited studies that directly compare BCs impregnated with Fe under different conditions. There is also a lack of information on the long-term performance of FBCs in flooded soil environments, where reductive dissolution of Fe (oxy)hydroxide phases loaded onto biochar surfaces may decrease the effectiveness of FBCs. This study uses material characterization methods including FTIR, SEM-EDX, BET, and adsorption isotherm experiments to investigate the effects of Fe-impregnation methods (pH, pyrolysis sequence, and sonication) on the morphology and mineralogy of Fe loaded onto the biochar surface, and to FBC adsorbent properties for arsenate (As(V)), arsenite (As(III)), and Cd. Acidic impregnation conditions favored the adsorption of As(III) onto amorphous Fe phases that were evenly distributed on the biochar surface, including within the biochar pore structure. The combination of sonication with acidic Fe-impregnation conditions led to the best adsorption capacities for As(V) and As(III) (4830 and 11,166 μg As g-1 biochar, respectively). Alkaline Fe-impregnation conditions led to the highest Cd adsorption capacity of 3054 μg Cd g-1 biochar, but had poor effectiveness as an As adsorbent. Amending soil with 5% (w/w) of an acid-impregnated and sonicated FBC was more effective than an alkaline-impregnated FBC or ferrihydrite in decreasing porewater As concentrations. The acid-impregnated FBC also had greater longevity, decreasing As by 54% and 56% in two flooded phases, probably due to the greater stability of Fe(III) within the biochar pore structure that may have a direct chemical bond to the biochar surface. This study demonstrates that FBCs can be designed with selectivity towards different As species or Cd and that they can maintain their effectiveness under anaerobic soil conditions. This is the first study to systematically test how impregnation conditions affect the stability of FBCs in soils under multiple drying-rewetting cycles.

Equivalent network modeling of eddy-current transfer functions

The use of eddy-current techniques as a measurement method for material characterization instead of simple fault detection requires transformation of the electrical response signals to quantifiable physical parameters that correlate with material properties. Apart from calibration-curve methods, exact approaches that correctly represent all interactions between excitation field and response field are computationally intensive and not well suited to real-time application. In this work, an equivalent circuit network model is constructed and its analytical equation for the voltage transfer function is derived. This model is then implemented in a soft sensor system. Finally, measurement results from various materials with different electromagnetic properties are presented.

Impact of meteorological data factors and material characterization method on the predictions of leading edge erosion of wind turbine blades

Leading edge erosion of wind turbine blades is a major contributor to wind farm energy yield losses and maintenance costs. Presented is a multidisciplinary framework for predicting rain erosion lifetimes of wind turbine blades. Key aim is assessing the sensitivity of lifetime predictions to: modeling aspects (material erosion model, blade aerodynamics), input data and/or their preprocessing (joint frequency distribution of wind speed and droplet size based on synchronous site-specific measurements versus frequency distribution generated with partly site-agnostic modeling standards, wind speed records of nacelle anemometer or extrapolated at hub height from met masts), and environmental conditions (UV weathering). The analyses consider a Northwest England onshore site where a utility-scale turbine is operational, focus on a reference 5 MW turbine assumed operational at the site, and use a typical leading edge coating material. It is found that the largest variations in erosion lifetime predictions are due to material erosion model (based on rain erosion test data or fundamental material properties) and wind and rain model (measurement-based joint wind speed and droplet size distribution or standard-based modeled distribution). The use of joint wind and rain distribution also enables identifying wind/rain states with highest erosion potential, knowledge paramount to deploying erosion-safe turbine control.

A corrosion failure analysis of a titanium tank used for production and storage of molten sodium sulfide

The corrosion failure of a titanium tank operating under high temperature of 220 °C for the production and storage of molten Na2S was thoroughly analyzed in this study. The various materialcharacterization methods, such as visual inspection, microscopic observation, chemical analysis, and mechanical assessment, demonstrated that hydride-inducedembrittlement plays a considerable role in the failure of the titanium tank. The key finding was that side products of H2, H2S, and Na2SO3 cause the destruction of the passive oxide film and, thus, provide the conditions for the absorption and penetration of atomic hydrogen, resulting in the formation of brittle TiH2 and subsequent flaking on the surface. To failure prevention of the titanium tank in such environments, the selection of tank material from Monel®400, blowing nitrogen gas into the system, and loading Na2CO3 into the reactive media were proposed. By complementary electrochemical investigations, it was clarified that Na2CO3 can stabilize the passive oxide film on the titanium surface and, therefore, enhance the resistance of the titanium tank against corrosion and failure. Notably, the present study can provide helpful references for enhancing the safety maintenance management of similar types of equipment.

A feasibility study on phase characterisation of nickel-based superalloys using ultrasound

The use of nickel-based superalloys, such as Inconel 718, Udimet 720Li and Waspaloy, is widespread across the engineering industry due to their superior mechanical properties at elevated temperatures and excellent resistance to creep and fatigue under harsh working conditions. The microstructure of these materials, such as the precipitates and grain sizes, strongly influence the materials’ performance. Currently, existing materials characterisation methods are time-consuming, costly and destructive, as well as only capable of taking measurements of surface or near-surface properties.This paper presents a novel ultrasonic technique for bulk materials characterisation of nickel-based superalloys, based on a spherical harmonic convolution theory which has been successfully used to quantify texture in various metals; it is applied here to study a nickel-based superalloy, with a specific focus on the phase changes when subject to thermal loading. The key parameter used to interpret phase information of a material is the zeroth spherical harmonic coefficient of ultrasonic wave velocities, V00, which corresponds to the average velocities across all directions in 3D space and is independent of crystallographic texture. Experimental investigation using samples of a representative material, Inconel 718, with contrasting microstructures, has shown a clear and quantifiable sensitivity of this coefficient to microstructural changes occurring within the material, and has thus laid the foundations for the development of a rapid phase characterisation technique for nickel-based superalloys using ultrasound.

A Review of Sheet Metal Forming Evaluation of Advanced High-Strength Steels (AHSS)

This paper presents a review on the formability evaluation of AHSS, enhancing necking-based failure criteria limitations. Complementary fracture/damage constitutive modeling approaches specifically tailored to formability evaluation, validated through numerical and experimental methods, are also subjects of research. AHSS are widely processed through sheet metal forming processes. Although an excellent choice when lightweight, high-strength, and ductility are critical factors, their multi-phase microstructure accentuates forming challenges. To accurately model forming behavior, necking-based failure criteria as well as direct fracture models require improvements. As a necking-based failure model, the conventional forming limit diagram/curve (FLD/FLC) presents limitations in estimating direct fracture (surface cracks, edge cracks, shear cracks), as well as deformation histories under non-linear strain paths. Thus, significant research efforts are being made towards the development of advanced fracture constitutive models capable of predicting fracture scenarios without necking, which are more frequently observed in the realm of AHSS. Scientific community research is divided into several directions aiming at improving the forming and fracture behavior accuracy of parts subjected to sheet metal forming operations. In this review paper, a comprehensive overview of ductile fracture modeling is presented. Firstly, the limitations of FLD/FLC in modeling fracture behavior in sheet metal forming operations are studied, followed by recent trends in constitutive material modeling. Afterwards, advancements in material characterization methods to cover a broad range of stress states are discussed. Finally, damage and fracture models predicting failure in AHSS are investigated. This review paper supplies relevant information on the current issues the sheet metal forming community is challenged with due to the trend towards AHSS employment in the automotive industry.

Experimental full waveform inversion for elastic material characterization with accurate transducer modeling

For quality assurance and in-service safety, sufficient characterization of the materials is essential during the development, manufacture, and processing of a material in any industrial setting. Evaluation of elastic coefficients, material microstructures, morphological features, and related mechanical properties are all part of the process of characterizing a material. Ultrasonic signals are sensitive to material properties such as wave speeds, attenuation, diffusion backscattering, microstructural variation, and elastic characteristics (e.g., elastic modulus, hardness, etc.). Ultrasonic computed tomography (USCT) is an emerging imaging method that can be implemented to obtain a quantitative estimation of material properties. In this study, a source estimation technique was initially proposed to obtain the source time function for accurate forward modeling by constructing a linear inverse problem for the unknown transducer modeling. Finally, a material characterization approach was proposed with accurate source estimation to extract wave speed distribution from an elastic material by employing a wave-based method, known as full waveform inversion (FWI). Systematic performance analysis of the proposed FWI model with accurate source estimation was assessed using experimental and synthetic data obtained from a 6061 aluminum sample. Overall, the proposed FWI technique has successfully reconstructed the wave speed distribution, exhibiting the potential of the proposed method of material characterization in various engineering applications.

Pore structure characterization and effective thermal conductivity modeling of fibrous building thermal insulation materials based on X-ray tomography

The existing structural characterization methods of building materials as well as thermal conductivity calculation models can not be directly applied when considering fibrous building thermal insulation materials with intricate skeletons. In this study, rock wool is considered the research object, and the X-ray tomography method is used to characterize the pore structure and extract structural parameters. Based on the actual pore morphology of the material, the pores in the representative elementary volume (REV) are reasonably assumed to be cubic. Additionally, considering the contact thermal resistance of fibers and the randomness of pore distribution, the curved pattern of heat conduction pathway with the ever-changing diameter is reasonably simplified into a series-parallel form of the curved heat chain with the same diameter. On this basis, the fractal models of effective thermal conductivity are established in horizontal and vertical directions. Finally, a modified formula for the effective thermal conductivity calculation of fiber thermal insulation materials is proposed, taking into account the influence of fiber orientation on the material thermal conductivity. It was shown that the relative deviation between the calculated correction value and the experimental value of the effective thermal conductivity is all less than 16.13%.

Effect of grain boundary on scratch behavior of polycrystalline copper

The anisotropy in the elastoplastic response of crystalline solids influences substantially their scratch resistance at the microscale. While grain boundaries typically act as obstacles to the motion of dislocations at the grain level, the scratch behavior in the vicinity of the grain boundary is influenced by other factors such as crystallographic orientation and pile-up topography. We performed a systematic set of nano-scratch simulations using the mechanism-based strain gradient crystal plasticity to study the evolution of scratch force and depth near grain boundaries. To validate our model, we conducted a nano-scratch test on a polycrystalline copper sample and compared the scratch depth profile for a specific grain boundary with the simulated result, where a good qualitative agreement was achieved. Our simulations showed that the scratch depth, force, and hardness vary between the corresponding values for the individual constitutive grains, and the variation decreases by reducing the grain size. Additionally, we analyzed the scratch response in terms of the pile-up topography and subsurface stresses and distinguished different regimes when the indenter approaches and scratches across the boundary. Our findings offer a new direction to optimize the scratch resistance of polycrystalline metals by tailoring the size and orientation of grains near the surface. Additionally, it introduces scratching as a robust material characterization method.

Nanoscale intimacy in hierarchical catalytic structures for mediating furfural hydroconversion over Pd/CoxOy/SiAlOz

Precisely controlling nanoscale metal-acid intimacy of bifunctional catalysts is increasingly being exploited to improve the performance toward the tandem reactions. It remains a critical challenge to rationally design the spatial organization of dual-functional sites due to the lack of effective synthesis and material characterization methods at the nanoscale. Here we impose hierarchical structures into bifunctional catalysts, wherein Pd particles are controllably deposited on cobalt oxide (CoxOy) nanoglues, which themselves are dispersed on high-surface-area and acid silica-alumina (SiAlOz). The hydroconversion of furfural demonstrates that the catalytic performance is optimized by tailoring the intimacy between Pd and acid sites, that is, with an appropriate nanoscale rather than the closest intimacy. The conversion from furfural to cyclopentanone on hierarchical catalytic structures in Pd/CoxOy/SiAlOz undergoes the treble-site catalytic mechanism, comprising the dissociation of H2 on Pd, the preferential adsorption and hydrogenation of the carbonyl on CoxOy, followed by the hydrogenative ring-rearrangement of furfuryl alcohol intermediate on SiAlOz via the synergistic effect of acid sites and hydrogen spillover. Besides, the asynchronous catalysis resulting from Pd ensemble isolation from SiAlOz surface profoundly restrains the generation of tetrahydrofurfuryl alcohol by elongating the distance of hydrogen spillover, weakening the hydrogenation of the furan ring flat adsorbed on SiAlOz. Resultant Pd/CoxOy/SiAlOz-40 with an optimal Pd-acid intimacy delivers a conversion of 96% and selectivity toward cyclopentanone of 88%, outperforming most state-of-the-art noble metal catalysts. We anticipate that such a concept and synthesis strategy of hierarchical catalytic structures will extend the understanding of the metal-acid intimacy and provide a feasible approach for delicately regulating the location of functional sites in bifunctional catalysts, the results of which may enable the properties of multifunctional catalysts to be modulated to specific target processes.

Microstructure and tribological properties of laser directed energy deposited 316-NiTi heterogeneous bionic sandwich structure coatings

In this study, inspired by multilayer structures in nature, an equal weight ratio Ni/Cu composite sandwich specimen was introduced for joining 316 and NiTi alloys to improve the wear resistance of 316. The microstructural evolution process as well as the wear resistance mechanism is clarified by a series of material characterization methods and mechanical property tests. The microstructure of the Ni/Cu interlayer exhibits a dendritic morphology, and the NiTi layer shows both coarse and fine characteristics. The crystallography of 316-Ni/Cu–NiTi composite sandwich specimens was investigated by electron backscatter diffraction. Three types of friction balls (316, 440C, 100Cr6) were used to perform dry reciprocating sliding ball-on-plate wear testing on 316-Ni/Cu–NiTi composite sandwich specimens and 316 substrates under varying normal loads from 10 N to 30 N. The 316-Ni/Cu–NiTi specimens showed better wear resistance compared to the 316 substrate under different wear conditions, when the normal load is 30 N and the friction ball is 100Cr6, the specific wear rate of the coating is only 44% of the substrate. This study not only provides insights to enhance the wear resistance of 316, but also develops a novel approach to broaden the connection between austenitic stainless steel and NiTi alloys.

Upgraded VKI Plasmatron capabilities with supersonic nozzles for extended material characterization methods

In the domain of re-entry and hypersonic vehicles, advancing material development requires comprehensive material testing to thoroughly understand the aero-thermo-chemistry at the surface. This paper overviews hypersonic, high-temperature activities conducted at the von Karman Institute for Fluid Dynamics (VKI) Plasmatron facility, employing three recently developed supersonic nozzles. These activities aim to augment VKI’s experimental and numerical capabilities in high-temperature material research, contributing to a deeper understanding of the chemical surface interactions, at stagnation and off-stagnation locations, during re-entry. The newly developed nozzles were 3D printed using an additive manufacturing aluminum alloy. The three nozzles serve distinct purposes: two conical ones of varying lengths are designed for stagnation point testing, while the third nozzle, adopting a semi-elliptical shape, is tailored for off-stagnation point testing. The initial section of the paper focuses on designing, manufacturing, and simulating these nozzles, then we characterize the nozzle flow and compare with simulations, while the subsequent part will delve into showcases of recent activities conducted in the Plasmatron facility utilizing these distinct nozzle configurations.

RT-EOM-CCSD Calculations of Inner and Outer Valence Ionization Energies and Spectral Functions.

Photoelectron spectroscopy (PES) is a standard experimental method for material characterization, but its interpretation can be hampered by its reliance on standard materials. To facilitate the study of unknown systems, theoretical methods are desirable. Here, we present a real-time equation-of-motion coupled cluster (RT-EOM-CC) approach for valence PES, extending our core-level development. We demonstrate that RT-EOM-CC yields ionization energies and spectral functions in good agreement with experimental and CI-based results, even for some more correlated cases.

Material characterization of human middle ear using machine-learning-based surrogate models

This study aims to introduce a novel non-invasive method for rapid material characterization of middle-ear structures, taking into consideration the invaluable insights provided by the mechanical properties of ear tissues. Valuable insights into various ear pathologies can be gleaned from the mechanical properties of ear tissues, yet conventional techniques for assessing these properties often entail invasive procedures that preclude their use on living patients. In this study, in the first step, we developed machine-learning models of the middle ear to predict its responses with a significantly lower computational cost in comparison to finite-element models. Leveraging findings from prior research, we focused on the most influential model parameters: the Young's modulus and thickness of the tympanic membrane and the Young's modulus of the stapedial annular ligament. The eXtreme Gradient Boosting (XGBoost) method was implemented for creating the machine-learning models. Subsequently, we combined the created machine-learning models with Bayesian optimization (BoTorch) for fast and efficient estimation of the Young's moduli of the tympanic membrane and the stapedial annular ligament. We demonstrate that the resultant surrogate models can fairly represent the vibrational responses of the umbo, stapes footplate, and vibration patterns of the tympanic membrane at most frequencies. Also, our proposed material characterization approach successfully estimated the Young's moduli of the tympanic membrane and stapedial annular ligament (separately and simultaneously) with values of mean absolute percentage error of less than 7%. The remarkable accuracy achieved through the proposed material characterization method underscores its potential for eventual clinical applications of estimating mechanical properties of the middle-ear structures for diagnostic purposes.

Upgrading recovered carbon black (rCB) from industrial-scale end-of-life tires (ELTs) pyrolysis to activated carbons: Material characterization and CO2 capture abilities

The current study presents for the first time how recovered carbon black (rCB) obtained directly from the industrial-scale end-of-life tires (ELTs) pyrolysis sector is applied as a precursor for activated carbons (ACs) with application in CO2 capture. The rCB shows better physical characteristics, including density and carbon structure, as well as chemical properties, such as a consistent composition and low impurity concentration, in comparison to the pyrolytic char. Potassium hydroxide and air in combination with heat treatment (500–900 °C) were applied as agents for the conventional chemical and physical activation of the material. The ACs were tested for their potential to capture CO2. Ultimate and proximate analysis, Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDS), Raman spectroscopy, thermogravimetric analysis (TGA), and N2/CO2 gas adsorption/desorption isotherms were used as material characterization methods. Analysis revealed that KOH-activated carbon at 900 °C (AC-900K) exhibited the highest surface area and a pore volume that increased 6 and 3 times compared to pristine rCB. Moreover, the AC-900K possessed a well-developed dual porosity, corresponding to the 22% and 78% of micropore and mesopore volume, respectively. At 0 °C and 25 °C, AC-900K also showed a CO2 adsorption capacity equal to 30.90 cm3/g and 20.53 cm3/g at 1 bar, along with stable cyclic regeneration after 10 cycles. The high dependence of CO2 uptake on the micropore volume at width below 0.7–0.8 nm was identified. The selectivity towards CO2 in relation to N2 reached high values of 350.91 (CO2/N2 binary mixture) and 59.70 (15% CO2/85% N2).

GelMA/PEDOT:PSS Composite Conductive Hydrogel-Based Generation and Protection of Cochlear Hair Cells through Multiple Signaling Pathways.

Recent advances in cochlear implantology are exemplified by novel functional strategies such as bimodal electroacoustic stimulation, in which the patient has intact low-frequency hearing and profound high-frequency hearing pre-operatively. Therefore, the synergistic restoration of dysfunctional cochlear hair cells and the protection of hair cells from ototoxic insults have become a persistent target pursued for this hybrid system. In this study, we developed a composite GelMA/PEDOT:PSS conductive hydrogel that is suitable as a coating for the cochlear implant electrode for the potential local delivery of otoregenerative and otoprotective drugs. Various material characterization methods (e.g., 1H NMR spectroscopy, FT-IR, EIS, and SEM), experimental models (e.g., murine cochlear organoid and aminoglycoside-induced ototoxic HEI-OC1 cellular model), and biological analyses (e.g., confocal laser scanning microscopy, real time qPCR, flow cytometry, and bioinformatic sequencing) were used. The results demonstrated decent material properties of the hydrogel, such as mechanical (e.g., high tensile stress and Young's modulus), electrochemical (e.g., low impedance and high conductivity), biocompatibility (e.g., satisfactory cochlear cell interaction and free of systemic toxicity), and biosafety (e.g., minimal hemolysis and cell death) features. In addition, the CDR medicinal cocktail sustainably released by the hydrogel not only promoted the expansion of the cochlear stem cells but also boosted the trans-differentiation from cochlear supporting cells into hair cells. Furthermore, hydrogel-based drug delivery protected the hair cells from oxidative stress and various forms of programmed cell death (e.g., apoptosis and ferroptosis). Finally, using large-scale sequencing, we enriched a complex network of signaling pathways that are potentially downstream to various metabolic processes and abundant metabolites. In conclusion, we present a conductive hydrogel-based local delivery of bifunctional drug cocktails, thereby serving as a potential solution to intracochlear therapy of bimodal auditory rehabilitation and diseases beyond.