Rahul Panat

ABSTRACT Next‐generation microelectronic devices and energy systems will require fabrication techniques that enable the rapid spatial arrangement of 1D and 2D functional nanomaterials. Arranging atomically thin 2D nanosheets in three‐dimensional (3D) space, however, is challenging due to the need for additives or support materials required for their spatial build‐up. Here, we report an advanced fabrication technique that can arrange nanometer‐thick micron‐sized Ti 3 C 2 T x MXene 2D nanosheets in self‐supporting three‐dimensional structures in a single printing step. This additive‐free approach leverages aerosol jet 3D nanoprinting (AJP), where fluid dynamics of rapidly evaporating aerosol droplets is used to achieve precise, support‐free, freestanding 3D geometries of 2D nanosheets. A real‐time thickening effect during printing and van der Waals interactions between MXene nanosheets are identified as the basis of robust structure formation in 3D, offering a pathway to use 2D materials in device applications. The versatility and impact of this technique are demonstrated by constructing 3D microsupercapacitors (MSCs) with finely patterned 3D MXene electrodes. These devices exhibit a breakthrough areal capacitance of 375 mF·cm −2 at a current density of 1.5 mA·cm −2 (equivalent electrode capacitance of 1500 mF·cm −2 ) and an energy density of 11.04 µWh·cm −2 at a power density of 0.40 mW·cm −2 . This electrochemical performance far exceeds that of MSCs fabricated by other high‐resolution patterning methods. This work paves the way for the use of 2D materials in micron‐sized device systems.

Aerosol Jet (AJ) printing is a versatile additive manufacturing technique capable of producing high-resolution interconnects on both 2D and 3D substrates. The AJ process is complex and dynamic with many hidden and unobservable states that influence the machine performance, including aerosol particle diameter, aerosol carrier density, vial level, and ink deposition in the tube and nozzle. Despite its promising potential, the widespread adoption of AJ printing is limited by inconsistencies in print quality that often stem from variability in these hidden states. To address these challenges, we develop a digital twin model of the AJ process that offers real-time insights into the machine's operations. The digital twin is built around a physics-based macro-model created through simulation and experimentation. The states and parameters of the digital model are continuously updated using probabilistic sequential estimation techniques to closely align with real-time measurements extracted from the AJ system's sensor and video data. The result is a digital model of the AJ process that continuously evolves over a physical machine's lifecycle. The digital twin enables accurate monitoring of unobservable physical characteristics, detects and predicts anomalous behavior, and forecasts the effect of control adjustments. This work presents a comprehensive end-to-end digital twin framework that integrates customized computer vision techniques, physics-based macro-modeling, and advanced probabilistic estimation methods to construct an evolving digital representation of the AJ equipment and process. While the methodologies are customized for aerosol jet printing, the process for constructing the digital twin can be applied for other advanced manufacturing techniques.

Non-Enzymatic Electrochemical Glucose Sensor In the Research Article (DOI: 10.1002/adsr.202500069), Rahul Panat, Suhas Jejurikar, and co-workers demonstrate effective detection of glucose molecules using a carbon paper electrode modified by a stack of MWCNTs and NiO. Various characterization techniques show that the unique combination of materials in the stack enhances the electrocatalytic activity of the electrode, leading to the observed effects. This approach leads to enhanced non-enzymatic sensors for biomolecule detection.

Abstract Non‐enzymatic high‐performance glucose sensors are important due to their stability and low cost. Nickel oxide and its composites with various materials such as multi‐walled carbon nanotubes (MWCNTs) have emerged as a platform for non‐enzymatic glucose detection at micromolar concentrations. In this article, the reaction mechanism within a MWCNTs/NiO/MWCNTs stacked electrode system used for glucose detection is explored and elucidated. Micro‐Raman and ‐Xray Photoelectron Spectroscopy are used to track the changes associated with the chemical state of the MWCNTs in the composite electrode during the oxidation of glucose molecules. The results show that the presence of MWCNTs provides abundant active sites for the electrochemical reaction. The enhanced electron transfer improves sensor sensitivity as evidenced by distinct redox peaks in the cyclic voltammograms. We conclude that the MWCNTs used herewith provide an ultrahigh surface‐area‐to‐volume ratio for the adsorption of OH − ions from the alkaline medium, which, in turn, facilitates the formation of NiOOH from NiO. The NiOOH formed further acts as an oxidizing agent for glucose molecules, altering them to gluconolactone via a chemical reaction that produces hydrogen peroxide while regenerating NiO. The detailed understanding of the reaction mechanism underscores the significant role of MWCNTs in enhancing the efficiency and sensitivity of non‐enzymatic glucose sensors.

The integration and fabrication of electrical circuits conformably onto 3D surfaces offer greater spatial efficiency, increased functionality, and improved performance in compact and tightly coupled electro-mechanical systems. However, existing 3D circuit prototyping workflows are often constrained by limited performance, insufficient generalizability or excessive manual effort and time requirements. In this paper, we present a framework that transforms 2D circuit design onto high-curvature 3D surfaces while preserving user-defined circuit characteristics and desired electrical parameters, such as trace length matching and resistance value target, allowing for the design of complex 3D circuitry using conventional 2D circuit design software that are intuitive for electrical engineers. The key contribution of this work is a two-stage processing algorithm that employs surface parameterization for 3D conformal circuit mapping followed by local distortion optimization for circuit parameter preservation. This method takes a 2D circuit design and a 3D CAD of the target surface as input, and then generates 3D circuit fabrication and process plans. We demonstrate the efficacy of our framework with a comparative analysis of circuit property preservation against other mapping approaches, both in simulation and in physical experiments, showing an 85% reduction in circuit deformation. We also demonstrate the potential of our framework through test case applications in aerospace and medical devices.

High Resolution Image Download MS PowerPoint Slide The fabrication of electronic devices of two-dimensional (2D) materials such as MXenes, via jetting-based 3D printing techniques, has shown great promise for advanced applications, including flexible sensors and energy storage devices. The synthetic routes for device fabrication often require extended durations and multiple complex processes, particularly for the synthesis of printable inks, thereby greatly hampering the scalability and practical deployment of such technologies. Herein, we report a facile strategy for the synthesis of 2D Ti 3 C 2 -APTES, Ti 3 C 2 -MPTES, and Ti 3 C 2 -MPTMS via silylation reaction, as well as their dispersions in suitable solvents for 3D aerosol jet printing (3D-AJP). By merging 2D MXene with organosilanes, the resulting inks exhibit high stability with excellent water dispersibility, cost-effectiveness, tunable surface functionalization, and enhanced accessibility to reactive sites. Moreover, under ambient conditions, the 3D-AJP inks show stability for up to 18 months, demonstrating exceptional durability, which is an ideal feature for long-term practical applications of the ink. This work thus not only establishes a paradigm for the 3D printing of flexible advanced materials but also presents a low-cost, scalable strategy for the preparation of multifunctional, additive-free, and conductive inks suitable for large-scale applications.

Theoretical studies have shown that plate-lattice structures exhibit exceptional mechanical properties such as high strength-to-weight ratios. Their fabrication, however, is challenging and has only been realized for metals via the Laser Powder Bed Fusion (LPBF) process. A deeper understanding of the deformation mechanisms of LPBF fabricated plate-lattice structures, including their post-yielding and energy absorption characteristics, is needed to evaluate their applicability in defense, aerospace, and biomedical industries. In this study, AlSi10Mg plate-lattice structures with four unit cell topologies were fabricated using LPBF and tested in quasi-static compression to determine mechanical properties, deformation behaviors, and energy absorption capabilities. Microcomputer tomography revealed surface variations resulting from adhered powder and dross formation were comparable in scale to plate thicknesses. Tested plate-lattices experience primarily stretch-dominant deformation consistent with theoretical Gibson-Ashby models. Stretch-dominant deformation is maintained for large compressive strains post-yielding until brittle fracture occurs in unit cell layers or diagonal bands, leading to high strength localized. For the simple cubic geometry, high yield stresses that were maintained post-yielding resulted in the highest specific energy absorption yet observed in lattice materials, reaching up to 27.2 J/g at a density of 1.23 g/cc. This research highlights AlSi10Mg plate-lattices as excellent candidates for light-weight energy absorption applications.

Integrity of thin films with micron-sized thickness is of high importance to the microelectronics industry. The mechanisms and mechanics of the cracking of such films made by conventional methods such as chemical and/or physical vapor deposition are well understood. Printed electronic techniques have recently emerged that allow films of various functional materials to be fabricated on-demand via nanoparticle printing followed by sintering. The failure mechanisms in such cases, however, are strongly influenced by the fabrication technique and the material used, but this dependence is not well understood. In this research, we study the mechanisms of cracking and delamination of Aerosol Jet (AJ) 3D nano-printed gold films on ceramic substrates. The layer-by-layer film fabrication allows the determination of effect of each process step (printing, drying, and sintering) on film stress and failure. We show that film cracking occurs only during the film drying phase (i.e., immediately following printing), and is relatively independent of the underlying substrate. We also show that the most significant factor affecting cracking is the glass transition temperature (T g ) of the binder in the printed film (which is removed during sintering but is present during printing and drying); with drying-induced capillary stress giving rise to the classic 'mud-cracking’. In other words, if printing is done close to the T g of the binder, the system becomes unusually strain tolerant and cracking can be avoided. As expected, the delamination is found to be a function of the film-substrate interface interaction. Finally, we develop failure mechanism maps for printed electronic films and determine the thickness below which reliable films can be fabricated. This work lays the foundation of engineering strategies for the reliable fabrication of electronic films via 3D printing.

Manufacturing of ceramics is challenging due to their low toughness and high hardness. Additive Manufacturing (AM) has been explored to create complex ceramic structures, but current techniques face a tradeoff between precisely controlled feature sizes and high shrinkage at the microscales. Here, we introduce 3D-AJP, a novel freeform ceramic fabrication method that enables highly complex microscale 3D ceramic architectures-such as micropillars, spirals, and lattices-with minimal shrinkage and no auxiliary support. Using a near-binder-free nanoparticle ink in an Aerosol Jet (AJ) 3D printer, our approach precisely controls feature sizes down to 20 µm with aspect ratios up to 30:1. The resulting structures exhibit exceptionally low linear shrinkage of 2-6% upon sintering, spanning five orders of magnitude in length scale. Bi-material 3D architectures (zinc oxide/zirconia, zinc oxide/titania, titania/zirconia) and hybrid ceramics further demonstrate the technique's versatility. We showcase two key applications. First, 3D ceramic photocatalysts improve water purification performance, achieving a 400% increase in photocatalytic efficiency compared to bulk ceramics. Second, we develop a highly sensitive Her2 biomarker sensor for breast cancer detection, achieving a 22-second response time and a record-low detection limit of 0.0193 fm. Our technique will lead to high-performance sensing, filtration, microelectronics packaging, catalysis, and tissue regeneration technologies.

The surging demand for electronics is causing detrimental environmental consequences through massive electronic waste production. Urgently shifting toward renewable and eco-friendly materials is crucial for fostering a green circular economy. Herein, we develop a multifunctional bionanocomposite using an algae-derived carbohydrate biopolymer (alginate) and boron nitride nanosheet (BNNS) that can be readily employed as a multifunctional dielectric material. The adopted rational design principle includes spatial locking of superhigh loading of BNNS via hydrogel casting followed by layer-by-layer assembly via solvent evaporation, successive cross-link engineering, and hot pressing. We harness the hierarchical assembly of BNNS and the molecular interaction of alginates with BNNS to achieve synergistic material properties with excellent mechanical robustness (tensile strength ∼135 MPa, Young’s modulus ∼18 GPa), flexibility, thermal conductivity (∼4.5 W m –1 K –1 ), flame retardance, and dielectric properties (dielectric constant ∼7, dielectric strength ∼400 V/μm, and maximum energy density ∼4.33 J/cm 3 ) that outperform traditional synthetic polymer dielectrics. Finally, we leverage the synergistic material properties of our engineered bionanocomposite to showcase its potential in green electronic applications, for example, supercapacitors and flexible interconnects. The supercapacitor device consisting of aerosol jet-printed single-walled carbon nanotube electrodes on our engineered bionanocomposite demonstrated a volumetric capacitance of ∼7 F/cm 3 and robust rate capability, while the printed silver interconnects maintained conductivity in various deformed states (i.e., bending or flexing).

Aerosol Jet (AJ) printing is a jetting-based additive manufacturing (AM) technique that uses droplets in an aerosol form to deposit nanoparticles or polymer inks at a length scale of about 10 micrometers. The desired structural geometries via AJ printing can be obtained at a high efficiency and accuracy by engineered toolpaths and fill strategies. Recently, AJ printing is used to create three-dimensional (3D) freestanding microarchitectures such as microlattices, spirals, walls, and micropillars without any auxiliary support during printing. In this work, we demonstrate that for curved segments, the difference in the printed material volume on the convex side vs concave side leads to the accumulation of material while building freestanding 3D microarchitectures. This effect is most severe for sharp corners, which leads to build-defects such as protrusions and voids. We carry out a systematic study of the material accumulation on curved segments of AJ printed 3D microarchitectures. For 3D microwall segments with sharp curved portions, a positive (or negative) material accumulation causing large overgrowths (or voids) as a function of the angle between the tangents on the two sides of the microwalls and the radii of curvature are studied. For sharp bends (<15°) in the microwalls, adding a radius of curvature may not be sufficient to avoid overgrowths and voids, and the lines can be considered as individual segments. For microwall bends with >45° angle between the segments, smaller radii of curvature can be tolerated. We conclude that a fillet radius equal to the line width for 30° angles is necessary to avoid accumulation and therefore the protrusion defects. A simple model based on mass-conservation is also developed which shows the importance of considering ink self-leveling during printing. This information is then used for toolpath strategies to avoid defects on sharp curved microwall segments for complex 3D architectures such as protruding star shape and Scotty Dog, the Carnegie Mellon University mascot. This research will enable the defect-free fabrication of highly complex 3D microarchitectures via jetting-based AM techniques such as AJ printing.

Three-dimensional (3D) gold microarchitectures such as micropillars, microwires, and microlattices are used in applications such as implantable biosensors, microelectronic circuits, and catalytic devices. Additive Manufacturing (AM) is being explored to create such structures as lithography is more suitable to fabricate 2D or planar architectures. In this work, we use Aerosol Jet (AJ) nanoprinting, a jetting-based AM technique, to demonstrate fabrication of gold micropillars via stacking of nanoparticles and sintering them at temperatures ranging from 300°C to 900°C. We first demonstrate that AJ printed 2D planar films and 3D micropillars exhibit a different grain size distribution, even if they are printed and sintered under identical conditions. This unusual observation indicates that specific AM technique and structures are important in determining their grain structure, which affects their mechanical behavior. The AJ printed 3D gold micropillars are fabricated with aspect ratios up to 10:1 and sintered from lower to higher temperatures, to yield porosities ranging from 15 % to 2 %, and average grain sizes from 25 nm to 1.7 µm, respectively. Micropillars sintered at lower temperatures exhibit a brittle behavior with higher yield strength despite having a higher porosity but with smaller grain sizes, and vice versa. These results indicate that the 3D geometry of AJ printed architectures dictates the grain size evolution, and hence the mechanical properties. Further, the grain size dominates over porosity in determining the micropillar deformation. These results provide important design guidelines for 3D printed microarchitected structures fabricated via jetting-based AM techniques.

Abstract Architected materials, exhibiting unique mechanical properties derived from their designs, have seen significant growth due to the design versatility and cost‐effectiveness offered by additive manufacturing. While finite element methods accurately evaluate the mechanical response of these structures, identifying new designs exhibiting specific mechanical properties remains challenging, often requiring computationally expensive simulations and design expertise. This underscores the need for a framework that generates structures based on desired mechanical properties without requiring expert input. In this work, a novel denoising diffusion‐based model is presented that generates complex lattice unit cell structures based on desired mechanical properties, manufacturable via additive techniques. The proposed framework generates unique lattice unit cell structures in the implicit domain which can be easily converted to mesh structures for fabrication and voxel structures for structural analysis. The proposed model accelerates the design process by generating unique structures with both isotropic and anisotropic stiffness, outperforming traditional unit cells like simple cubic and body‐centered‐cubic in energy absorption and compression load at lower densities. Additionally, this work explores a new class of hybrid structures, derived by combining multiple configurations of triply periodic minimal surface structures using non‐linear transition functions, which may offer equivalent or enhanced strength compared to conventional designs.

Sensing of viral antigens has become a critical tool in combating infectious diseases. Current sensing techniques have a tradeoff between sensitivity and time of detection; with 10-30 min of detection time at a relatively low sensitivity and 6-12 h of detection at a high (picomolar) sensitivity. In this research, uniquely nanoengineered interfaces are demonstrated on 3D electrodes that enable the detection of spike antigens of SARS-CoV-2 and their variants in seconds at femtomolar concentrations with excellent specificity, thus, overcoming this tradeoff. The 3D electrodes, manufactured using a high-resolution aerosol jet 3D nanoprinter, consist of a microelectrode array of sintered gold nanoparticles coated with graphene and antibodies specific to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) spike antigens. An impedance-based sensing modality is employed to sense several pseudoviruses of SARS-CoV-2 variants of concern (VOCs). This device is sensitive to most of the pseudoviruses of SARS-CoV-2 VOCs. A high sensitivity of 100 fm, along with a low limit-of-detection of 9.2 fm within a test range of 0.1-1000 pm, and a detection time of 43 s are shown. This work illustrates that effective nano-bioengineering of interfaces can be used to create an ultrafast and ultrasensitive healthcare diagnostic tool for combating emerging infections.

Transition metal carbides (MXenes) are novel 2D nanomaterials with exceptional properties, promising significant impact in applications such as energy storage, catalysis, and energy conversion. A major barrier preventing the widespread use of MXenes is the lack of methods for assembling MXene in 3D space without significant restacking, which degrades their performance. Here, this challenge is successfully overcome by introducing a novel material system: a 3D network of MXene formed on a porous ceramic backbone. The backbone dictates the network's 3D architecture while providing mechanical strength, gas/liquid permeability, and other beneficial properties. Freeze casting is used to fabricate a silica backbone with open pores and controlled porosity. Next, capilary flow is used to infiltrate MXene into the backbone from a dispersion. The system is then dried to conformally coat the pore walls with MXene, creating an interconnected 3D‐MXene network. The fabrication approach is reproducible, and the MXene‐infiltrated porous silica (MX‐PS) system is highly conductive (e.g., 340 S m −1 ). The electrical conductivity of MX‐PS is controlled by the porosity distribution, MXene concentration, and the number of infiltration cycles. Sandwich‐type supercapacitors with MX‐PS electrodes are shown to produce excellent areal capacitance (7.24 F cm −2 ) and energy density (0.32 mWh cm −2 ) with only 6% added MXene mass. This approach of creating 3D architectures of 2D nanomaterials will significantly impact many engineering applications.

Finite element analysis (FEA), a common approach for simulating stress distribution for a given geometry, is generally associated with high computational cost, especially when high mesh resolution is required. Furthermore, the non-adaptive nature of FEA requires the entire model to be solved even for minor geometric variations creating a bottleneck during iterative design optimization. This necessitates a framework that can efficiently predict stress distribution in geometries based on given boundary and loading conditions. In this paper, we present StressD, a framework for predicting von Mises stress fields based on the denoising diffusion model. The StressD framework involves two models, a U-net-based denoising diffusion model and an auxiliary network to generate and predict stress distribution in structures. The denoising diffusion model generates a normalized stress map based on the given geometry, boundary conditions and loading condition, while the auxiliary network is used to determine the scaling information needed to un-normalize the generated stress map. We evaluate the StressD framework on cantilever structures and show that it is able to accurately predict von Mises stress fields while significantly reducing computational cost compared to traditional FEA.

The HTML version of this Article incorrectly omits Supplementary Movie 1 , Supplementary Movie 2 , Supplementary Movie 3 , and Supplementary Movie 4 . The Supplementary Movies can be found as Supplementary Information associated with the original article and this Correction, and their descriptions can be found in the file entitled ‘Description of Additional Supplementary Files’.

Sintering theory predicts no long-range mass transport or distortion for uniformly heated particles during particle coalescence. However, in sintering-based manufacturing processes, permanent part distortion is often observed. The driving forces and mechanisms leading to this phenomenon are not understood, and efforts to reduce distortion are largely limited to a trial-and-error approach. In this paper, we demonstrate that distortion during sintering results from mass-transport driven by nonhomogeneous temperature distribution. We then show that hitherto unknown mass transport mechanisms, working in the direction opposite to temperature gradient are the likely cause of distortion. The experimental setup, designed for this purpose, enables the quantification of distortion during sintering. Two possible mass transport mechanisms are defined, and the continuum model applicable to both is formulated. The model accurately predicts the transient and permanent distortion observed during experiments, including their size dependence. Methods to control distortion that can give rise to 4D printing are discussed.

Mechanical behavior of lattice structures is important for a range of engineering applications. Herein, a new semiempirical model is proposed that describes the entire range of stress–strain response of lattice structures, including the stress‐instability region which is modeled as an oscillator. The model can be fit to individual stress–strain curves to extract elastic modulus, yield stress, collapse stress, post‐yield collapse ratio, densification strain, and the energy absorbed per unit volume. The model is fit to 119 unique experimental stress–strain curves from 13 research papers in literature covering four different lattice designs, namely, octet truss, body‐centered cubic with vertical members, body‐centered cubic, and hexagonal. Manufacturing methods (additive and conventional) and materials (metals and polymers) were also included in the analysis. The fitted model yields several new insights into the compression behavior of previously tested lattice structures and can be applied to additional lattice designs. Among other results, analysis of variance (ANOVA) reveals that the octet truss lattice demonstrates the highest post‐yield collapse ratio and the smallest normalized energy absorption per unit volume amongst the lattice structures investigated. The proposed model is a powerful tool for designers to quantitatively compare and select 3D lattice structures with the desired mechanical characteristics.

Fossil power generation systems are increasingly vulnerable to attack from both cybercriminals as well as internal threats. These vulnerabilities demand that emerging technologies such as blockchains be utilized to secure the data involved in the information flows within the Supervisory Control and Data Acquisition (SCADA) systems of the fossil power generation plants. The publicly accessible blockchain protocols, although secure, are visible to everyone. Even private blockchains currently are unable to support different levels of access to different participants, which is a critical requirement for the existing SCADA systems running the power plants. In light of the above, novel blockchain protocols that are specifically adapted to fossil power generation environments need to be developed in order to achieve the goal of cybersecure sensor networks. In this work, we address this question by creating a novel blockchain technology, namely smart private ledger, for cybersecure communication within the fossil power generation systems. A lab-scale sensor network consisting of strain and temperature sensors is constructed to develop the ledger. The technology has hierarchical access control which is compatible with the existing SCADA systems in fossil power plants. The sensor data is used with cryptographic digital signatures and secret sharing protocols within the nodes of the blockchain technology. The research results will lead to cybersecurity for machine-to-machine interactions, infrastructure for secure data logging for sensors, decentralized data storage, and second-layer technologies for high volume machine-to-machine interactions in the power plants. The work aims to largely address the concerns for the security of distributed sensor networks in such systems that can be compromised by insider threats and by cybercriminals. The research has led to the training of the next generation of engineers and scientists in the important areas of sensor engineering and blockchain technology.