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At least 19 records

Methods of nanomanufacturing at fluid interfaces and systems for same

Methods of nanomanufacturing based on continuous additive nanomanufacturing at fluid interfaces (CANFI). This approach is a fabrication technique that involves, for example, photocuring or “printing” self-assembled layers. CANFI presents a fabrication capability with significant transformative potential improve (i) the spatial resolution, (ii) the speed, and (iii) the range of material compositions that can be printed. Various articles of manufacture can be made using the methods.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

CsPbI 3 Nanocrystals Go with the Flow: From Formation Mechanism to Continuous Nanomanufacturing

Despite the groundbreaking advancements in the synthesis of inorganic lead halide perovskite (LHP) nanocrystals (NCs), stimulated from their intriguing size-, composition-, and morphology-dependent optical and optoelectronic properties, their formation mechanism through the hot-injection (HI) synthetic route is not well-understood. Here in this work, for the first time, in-flow HI synthesis of cesium lead iodide (CsPbI 3 ) NCs is introduced and a comprehensive understanding of the interdependent competing reaction parameters controlling the NC morphology (nanocube vs nanoplatelet) and properties is provided. Utilizing the developed flow synthesis strategy, a change in the CsPbI 3 NC formation mechanism at temperatures higher than 150 °C, resulting in different CsPbI 3 morphologies is revealed. Through comparison of the flow- versus flask-based synthesis, deficiencies of batch reactors in reproducible and scalable synthesis of CsPbI 3 NCs with fast formation kinetics are demonstrated. The developed modular flow chemistry route provides a new frontier for high-temperature studies of solution-processed LHP NCs and enables their consistent and reliable continuous nanomanufacturing for next-generation energy technologies.

36 MATERIALS SCIENCE↗

Active Learning‐Driven Inkless Additive Nanomanufacturing for Printed Electronics

Inkless additive nanomanufacturing for printed electronics promises broad material and substrate versatility, yet the high-dimensional print parameter space makes tuning print parameters time-intensive. We present a Bayesian optimization study that constructs a digital twin from printed-silver data to benchmark surrogate models, acquisition functions, and batch sizes head-to-head to achieve user-specified target resistance. Tested surrogate models included Gaussian process, random forest, and Bayesian neural network surrogates with expected improvement and confidence bound acquisition functions. In total, we evaluate 48 unique model configurations alongside a random sampling baseline for comparison. For printed silver, the Bayesian neural network with a batch size of one achieved the lowest average cumulative regret, approximately four times more efficient on average than random sampling. To balance performance and substrate space, a random forest model with expected improvement and a batch size of four was chosen as the model for validation testing. Applying this chosen configuration to copper with an additional print parameter, the model achieved a resistance within 0.15 Ω of a 1 Ω target in fewer than 30 printed lines across five validation sets. Altogether, the workflow yields a tuned and validated model that efficiently guides experiments toward the target while simultaneously learning the parameter space.

Bevel, Colton [Auburn University, AL (United State↗

Standalone Block Copolymer Nanoballoons: Decoupling Self-Assembly from Implementation in Nanomanufacturing

Here we report a facile method to produce isolatable hollow-core elastomeric vesicles, “nanoballoons”, prepared via block copolymer self-assembly in a polymer blend. Poly(isoprene-block-dimethylsiloxane) (PI-PDMS) diblock copolymers are blended with PDMS homopolymers (h-PDMS) as a “solvent” phase to template the self-assembly of PDMS-tethered vesicles with PI walls. The walls are subsequently crosslinked to yield mechanically stabilized elastomeric vesicles. The h-PDMS inner-core and matrix are separated from the vesicles by dialysis to yield the matrix-free nanoballoons. These objects, 0.3 – 1 μm in diameter, can be further reincorporated into a crosslinkable PDMS. Throughout the self-assembly, recovery, and reincorporation processes we apply several techniques including solvent dispersion/dynamic light scattering (DLS) measurements, transmission electron microscopy (TEM)/energy-dispersive X-ray spectroscopy (EDS), and small-angle X-ray scattering (SAXS) to provide a consilient body of evidence that the nanoballoon morphology is retained. Furthermore, this work presents advanced nanomanufacturing schema that illustrate the decoupling of the thermodynamic and dynamic factors that govern macromolecular self-assembly from the environment in which the self-assembled objects are deployed.

36 MATERIALS SCIENCE↗

Scalable nanomanufacturing of chalcogenide inks: a case study on thermoelectric V–VI nanoplates

Solution-processed semiconducting main-group chalcogenides (MMCs) have attracted increasing research interest for next-generation device technologies owing to their unique nanostructures and superior properties. To achieve the full potential of MMCs, the development of highly universal, scalable, and sustainable synthesis and processing methods of chalcogenide particles is thus becoming progressively more important. Here we studied scalable factors for the synthesis of two-dimensional (2D) V–VI chalcogenide nanoplates (M 2 Q 3 : M = Sb, Bi; Q = Se, Te) and systematically investigated their colloidal behaviour and chemical stability. Based on a solvent engineering technique, we demonstrated scale-up syntheses of MMCs up to a 900% increase of batch size compared with conventional hydrazine-based gram-level syntheses, and such a scalable approach is highly applicable to various binary and ternary MMCs. Furthermore, we studied the stability of printable chalcogenide nanoparticle inks with several formulation factors including solvents, additives, and pH values, resulting in inks with high chemical stability (>4 months). As a proof of concept, we applied our solution-processed chalcogenide particles to multiple additive manufacturing methods, confirming the high printability and processability of MMC inks. Furthermore, the ability to combine the top-down designing freedom of additive manufacturing with bottom-up scalable synthesis of chalcogenide particles promises great opportunities for large-scale design and manufacturing of chalcogenide-based functional devices for broad application.

36 MATERIALS SCIENCE↗

Holographic Lithography for Industrial Nanomanufacturing

The participant constructed interference lithography experiments on their prototype of a coordinated holographic industrial-scale electromagnetic lithography (CHISEL) tool. These experiments involved generating several laser beams and interfering them in photosensitive materials, whereupon subsequent development resulted in micro- and nano-structured samples. We characterized these samples using scanning electron microscopy and various optical interrogation methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Nanomanufacturing of Nanophononic Devices: Ultra-high ZT Thermoelectrics for Efficient Conversion of Waste Heat

Fabrication and Characterization Summary: For this program, the team fabricated and tested silicon thermoelectric test structures that experimentally demonstrated record thermal conductivity reduction (> 85 %) without changes in electrical properties (conductivity and Seebeck coefficient). We also demonstrated the highest ever reported energy conversion efficiency for silicon thermoelectric devices. The team developed a design for 1 cm 2 die with thousands of nanophononic metamaterial structures in the form of nanowalled membranes but were unable to solve all fabrication challenges before the end of the program. Multiple aspects of the design were submitted for patent protection. Primary challenges were related to silicon-on-insulator material quality and high-aspect-ratio etching.

30 DIRECT ENERGY CONVERSION↗

Microfluidic synthesis of multilayered lipid–polymer hybrid nanoparticles for the formulation of low solubility drugs

Hybrid phospholipid/block copolymer membranes where polymers and lipids are molecularly mixed or phase-separated into polymer-rich and lipid-rich domains are promising drug delivery materials. Harnessing the chemical diversity of polymers and the biocompatability of lipids is a compelling approach to design the next generation of drug carriers. Here, we report on the development of a microfluidics-based strategy analogous to produce lipid nanoparticles (LNPs) for the nanomanufacturing of multilayered hybrid nanoparticles (HNPs). In conclusion, using X-ray scattering, Cryo-electron, and polarized microscopy we show that phosphatidylcholine (PC) and PBD-b-PEO (poly(butadiene-block-ethylene oxide)) hybrid membranes can be nanomanufactured by microfluidics into HNPs with dense and multilayered cores which are ideal carriers of low-solubility drugs of the Biopharmaceutical Classification System (BCS) II and IV such as antimalarial DSM265 and Paclitaxel, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Systems Approach to Estimating the Uncertainty Limits of X-Ray Radiographic Metrology

Micro- and nanomanufacturing capabilities have rapidly expanded over the past decade to include complex three-dimensional (3D) structure fabrication; however, the metrology required to accurately assess these processes via part inspection and characterization has struggled to keep pace. X-ray computed tomography (CT) is considered an ideal candidate for providing the critically needed metrology on the smallest scales, especially internal features, or inaccessible regions. X-ray CT supporting micro- and nanomanufacturing often push against the poorly understood resolution and variation limits inherent to the machines, which can distort or hide fine structures. In this study, we have developed and experimentally verify a comprehensive analytical uncertainty propagation signal variation flow graph (SVFG) model for X-ray radiography in this work to better understand resolution and image variability limits on the small scale. The SVFG approach captures, quantifies, and predicts variations occurring in the system that limit metrology capabilities, particularly in the micro/nanodomain. This work is the first step to achieving full uncertainty modeling of CT reconstructions and provides insight into improving X-ray attenuation imaging systems. The SVFG methodology framework is applied to generate a complete basis set of functions describing the major sources of variation in radiographs. Five models are identified, covering variation in energy, intensity, length, blur, and position. Radiographic system experiments are defined to measure the parameters required by the SVFGs. Best practices are identified for these measurements. The SVFG models are confirmed via direct measurement of variation to predict variation within 30% on average.

47 OTHER INSTRUMENTATION↗

Machine Learning Guided Synthesis of Flash Graphene

Advances in nanoscience have enabled the synthesis of nanomaterials, such as graphene, from low-value or waste materials through flash Joule heating. Though this capability is promising, the complex and entangled variables that govern nanocrystal formation in the Joule heating process remain poorly understood. In this work, machine learning (ML) models are constructed to explore the factors that drive the transformation of amorphous carbon into graphene nanocrystals during flash Joule heating. An XGBoost regression model of crystallinity achieves an r 2 score of 0.8051 ± 0.054. Feature importance assays and decision trees extracted from these models reveal key considerations in the selection of starting materials and the role of stochastic current fluctuations in flash Joule heating synthesis. Furthermore, partial dependence analyses demonstrate the importance of charge and current density as predictors of crystallinity, implying a progression from reaction-limited to diffusion-limited kinetics as flash Joule heating parameters change. Finally, a practical application of the ML models is shown by using Bayesian meta-learning algorithms to automatically improve bulk crystallinity over many Joule heating reactions. Furthermore, these results illustrate the power of ML as a tool to analyze complex nanomanufacturing processes and enable the synthesis of 2D crystals with desirable properties by flash Joule heating.

01 COAL, LIGNITE, AND PEAT↗

Scalable Nanoimprint Manufacturing of Functional Multilayer Metasurface Devices

Optical metasurfaces, consisting of subwavelength-scale meta-atom arrays, hold great promise of overcoming the fundamental limitations of conventional optics. Due to their structural complexity, metasurfaces usually require high-resolution yet slow and expensive fabrication processes. Here, using a metasurface polarimetric imaging device as an example, the photonic structures and the Nanoimprint lithography (NIL) processes are designed, creating two separate NIL molds over a patterning area of > 20 mm2 with designed Moiré alignment markers by electron-beam writing, and further subsequently integrate silicon and aluminum metasurface structures on a chip. Uniquely, the silicon and aluminum metasurfaces are fabricated by using the nanolithography and 3D pattern-transfer capabilities of NIL, respectively, achieving nanometer-scale linewidth uniformity, sub-200 nm translational overlay accuracy, and <0.017 rotational alignment error while significantly reducing fabrication complexity and surface roughness. Here, the micro-sized multilayer metasurfaces have high circular polarization extinction ratios as large as ≈20 and ≈80 in blue and red wavelengths. Further, the metasurface chip-integrated CMOS imager demonstrates high accuracy in broad-band, full Stokes parameter analysis in the visible wavelength ranges and single-shot polarimetric imaging. This novel, NIL-based, multilayered nanomanufacturing approach is applicable to the scalable production of large-area functional structures for ultra-compact optic, electronic, and quantum devices.

36 MATERIALS SCIENCE↗

Fully Inkjet‐Printed, 2D Materials‐Based Field‐Effect Transistor for Water Sensing

Abstract Despite significant progress in solution‐processing of 2D materials, it remains challenging to reliably print high‐performance semiconducting channels that can be efficiently modulated in a field‐effect transistor (FET). Herein, electrochemically exfoliated MoS 2 nanosheets are inkjet‐printed into ultrathin semiconducting channels, resulting in high on/off current ratios up to 10 3 . The reported printing strategy is reliable and general for thin film channel fabrication even in the presence of the ubiquitous coffee‐ring effect. Statistical modeling analysis on the printed pattern profiles suggests that a spaced parallel printing approach can overcome the coffee‐ring effect during inkjet printing, resulting in uniform 2D flake percolation networks. The uniformity of the printed features allows the MoS 2 channel to be hundreds of micrometers long, which easily accommodates the typical inkjet printing resolution of tens of micrometers, thereby enabling fully printed FETs. As a proof of concept, FET water sensors are demonstrated using printed MoS 2 as the FET channel, and printed graphene as the electrodes and the sensing area. After functionalization of the sensing area, the printed water sensor shows a selective response to Pb 2+ in water down to 2 ppb. This work paves the way for additive nanomanufacturing of FET‐based sensors and related devices using 2D nanomaterials.

36 MATERIALS SCIENCE↗

Adaptive simulations enable computational design of electron beam processing of nanomaterials with supersonic micro-jet precursor

Focused Electron Beam Induced Processing (FEBIP) is a powerful tool for the “direct-write” of nanomaterials with the possibility of atomistic control on suspended 2D material substrates. FEBIP capabilities have been significantly expanded by using a localized jet-based delivery of precursors, and especially when a thermally energized supersonic micro-jet enhances the delivery of mass flux along with controlling the far-from-equilibrium thermodynamic state of adsorbed adatoms. The possibilities of growing nanomaterials with “dialed-in” composition with ultra-high growth rates and aspect ratios up to 100:1 have been demonstrated using the supersonic micro-jet-FEBIP. Bringing this scientific discovery to the level of maturity required for practical applications in additive nanomanufacturing requires simulation tools that are capable of capturing the complex flow physics of micro-jet-substrate interactions that bridge a wide range of flow regimes from the high-density gas micro-jet expanding into the vacuum environment of FEBIP. To address this significant computational challenge, a new approach has been developed and described in this work for a multiscale adaptive DSMC (Direct Simulation Monte Carlo) algorithm to predict the micro-jet gas dynamics in an FEBIP environment, spanning the full range of flow regimes from low Knudsen (Kn) number O(0.01) continuum flow to high Kn of O(10) for the molecular flow within a unified computational framework. Here, the fundamental principles of the adaptive DSMC algorithm are described, its viability as a DSMC technique is demonstrated, and computational improvements for the benchmark cases are discussed in the context of advancing 3D nanofabrication with FEBIP. Ultimately, combining the first principle simulations via adaptive DSMC with the complementary experimental data will enable the creation of the powerful CAD tools for in silico design and optimal operation of micro-jet-FEBIP.

36 MATERIALS SCIENCE↗

Enhanced internal condensation of R1233zd(E) on micro- and nanostructured copper and aluminum surfaces

In-tube condensation of refrigerants is an important process which affects thermal efficiency in many applications, ranging from refrigeration and air conditioning to electronics thermal management. In-tube heat transfer and pressure drop are important to heat exchanger sizing and design. Here, in this work, micro- and nanostructured surfaces are applied to the internal wetted areas of copper and aluminum mini-channels to enhance the condensation heat transfer coefficient of hydrofluorocarbon R1233zd(E) refrigerant. To achieve scalable nanomanufacturing, surfaces were uniformly structured by relying on hydrochloric acid etching of aluminum and chemical oxidation of copper. The etched aluminum surfaces exhibited a 150% increase in heat transfer coefficient compared to smooth aluminum channels at specific qualities, with a 66% heat transfer coefficient improvement for complete phase change from saturated vapor to saturated liquid. Copper oxide structures showed no discernable difference in thermal-hydraulic performance when compared to smooth copper channels. Critical dimensionless parameters governing the heat transfer enhancement were identified by varying the tube internal diameter (2.3 mm to 4.7 mm), refrigerant mass flux (50 to 300 kg/(m 2 ·s)), and refrigerant quality (0 to 1). The dimensionless parameters include the Bond number normalized to the condensate film thickness, and the Weber number modified by the vapor friction factor. The relatively small increase in pressure drop (< 10%) associated with these surface enhancements further supports the promise of this method. The scalable and cost-effective techniques used to create these aluminum microstructures may reduce manufacturing cost when compared with current enhancement approaches such as extrusion, drawing, and welding.

42 ENGINEERING↗

Horizons of modern molecular dynamics simulation in digitalized solid freeform fabrication with advanced materials

Our ability to shape and finish a component by combined methods of fabrication including (but not limited to) subtractive, additive and/or no theoretical mass-loss/addition during the fabrication is now popularly known as solid free form fabrication. Fabrication of a telescope mirror is a typical example where grinding and polishing processes are first applied to shape the mirror and thereafter an optical coating is usually applied to enhance its optical performance. The area of nanomanufacturing cannot grow without a deep knowledge of the fundamentals of materials and consequently, the use of computer simulations is becoming ubiquitous. This article is intended to introduce the most recent advances in the computation benefit specific to the area of solid free form fabrication as these systems are traversing through the journey of digitalisation and Industry-4.0. Specifically, this article demonstrates that the application of the latest materials modelling approaches, based on techniques such as molecular dynamics, are enabling breakthroughs in applied precision manufacturing techniques.

36 MATERIALS SCIENCE↗

Tuning 3-D Nanomaterial Architectures Using Atomic Layer Deposition to Direct Solution Synthesis

The ability to synthesize nanoarchitected materials with tunable geometries provides a means to control their functional properties, with applications in biological, environmental, and energy fields. To this end, various bottom-up and top-down synthesis processes have been developed. However, many of these processes require prepatterning or etching steps, making them challenging to scale-up to complex, nonplanar substrates. Furthermore, the ability to integrate nanomaterials into hierarchical arrays with precise control of feature spacing and orientation remains a challenge. One approach to overcome these patterning challenges is the use of surface modification layers to guide the resulting geometry of nanomaterial architectures grown from the substrate. A powerful strategy to accomplish this is what we will refer to as “surface-directed assembly,” where the resulting geometric parameters (feature size, shape, orientation) are predetermined by the initial surface layer. In particular, the use of Atomic Layer Deposition (ALD) to form a surface layer, followed by solution-based growth processes, has the ability to synthesize architected structures with tunable geometries on complex, nonplanar surfaces. Over the past decade, we have reported a series of studies where surface-directed assembly is used to synthesize ZnO nanowires (NWs) on top of a variety of substrates. In this case, a thin film of ZnO is deposited onto the substrate using ALD, which can guide the NW diameter, spacing, and angular orientation with respect to the substrate by controlling epitaxial relationships. Furthermore, we have shown that by depositing a submonolayer overcoat of a secondary material (e.g., amorphous TiO 2 ), nucleation sites are partially blocked, which can further tune the spacing between nanowires while minimizing changes to their other geometric properties. This approach can be used to generate multilevel hierarchical structures, such as hyperbranched NW arrays with tunable control of each level of hierarchy using ALD. Finally, we have demonstrated that the tunable control of geometric parameters can be scaled-up to curved, nonplanar substrates. This highlights the power of ALD to conformally and uniformly deposit the seed layers on complex substrates with subnanometer precision. To complement these seeded hydrothermal approaches, we expanded this strategy to include conversion chemistry of the initial ALD seed layers. For example, by replacing ZnO with Al 2 O 3 as the seed layer without changing the hydrothermal growth conditions, Al–Zn layered-double hydroxide nanosheets can be formed instead of nanowires. In another example of conversion chemistry, a solution anion-exchange process was used to incorporate sulfur into ALD metal oxide films. In both of these conversion processes, the properties of the initial ALD film enabled tuning of the resulting nanostructure geometry. In this Account, we describe the use of ALD to guide the growth of diverse nanomaterial systems, with tunable control over their geometry and composition. We further show how these approaches can be used to tune functional properties for a range of applications, including superomniphobic surfaces, antibiofouling coatings, and photocatalysis. In conclusion, we conclude with an outlook on how the combination of ALD and solution synthesis can enable future directions in scalable nanomanufacturing to overcome the limitations of traditional top-down and bottom-up approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗