Nanoscale Characterization Research Articles

Nonlinear Magnetic Sensing with Hybrid Nitrogen-Vacancy/Magnon Systems.

Magnetic sensing beyond the linear regime could broaden the frequency range of detectable magnetic fields, which is crucial to various microwave and quantum applications. Recently, nonlinear interactions in diamond nitrogen-vacancy (NV) centers are proposed to realize magnetic sensing across arbitrary frequencies. In this work, we enhanced these capabilities by exploiting the nonlinear spin dynamics in hybrid systems of NV centers and ferri- or ferromagnetic (FM) thin films. We studied the frequency mixing effect in the hybrid systems and demonstrated that the introduction of FM films not only amplifies the intensity of nonlinear resonance signals that are intrinsic to NV spins but also enables novel frequency mixing through parametric pumping and nonlinear magnon scattering effects. The discovery and understanding of the magnetic nonlinearities in hybrid NV/magnon systems position them as a prime candidate for magnetic sensing with a broad frequency range and high tunability, particularly meaningful for nanoscale, dynamical, and noninvasive materials characterization.

Nano-scale evidence for coupled interfacial dissolution-reprecipitation (CDR) controlling corrosion of alumina-forming austenitic (AFA) steel in static lead-bismuth eutectic (LBE) at 600°C

Despite extensive research on dissolution corrosion, whether element dissolution is selective or non-selective remains unclear, due to limitations of past characterization technologies. Using nano-scale characterization, we investigated AFA steel exposed to LBE with 10−8 wt.% oxygen at 600°C for 1700 h, found that alloying elements dissolve non-selectively into LBE and then reprecipitate, forming penetrable corrosion zone that inherits substrate crystallographic information and comprises ferrite, river-like NiAl, and NiAl nanoparticles. The ferrite and river-like NiAl exhibit complete elemental segregation due to liquid-phase diffusion, while NiAl nanoparticles form via reaction-diffusion. This supports that coupled dissolution-reprecipitation mechanism primarily controls dissolution corrosion at 600°C.

Chinese knot inspired isotropic linear scanning method for improved imaging performance in AFM

Atomic force microscope (AFM) is an important nano-scale surface characterization and measurement method. Raster scanning method (RSM), widely used in AFMs, faces limitations on scanning speed and imaging accuracy. In this paper, an isotropic linear scanning method (ILSM) is proposed to improve the AFM imaging performance. Inspired by Chinese knot, ILSM is constructed by integrating two iterative triangular scanning trajectories in X and Y axes, similar to triangular Lissajous. Compared with the other scanning methods, ILSM features isotropic scanning trajectory across the scanning region. It is also easy to increase either the scanning speed or scanning resolution using ILSM. Subsequently, to address the hysteresis associated with the piezoelectric actuator, a new tracking algorithm is proposed by combining adaptive Kalman filtering and direct inverse modeling approach. Finally, AFM imaging experiments are conducted to validate the effectiveness of the proposed method. It can be found that the artifacts in RSM can be efficiently eliminated using the proposed method, thus improving the imaging quality.

Nanophysics Is Boosting Nanotechnology for Clean Renewable Energy.

As nanophysics constitutes the scientific core of nanotechnology, it has a decisive potential for advancing clean renewable energy applications. Starting with a brief foray into the realms of nanophysics' potential, this review manuscript is expected to contribute to understanding why and how this science's eruption is leading to nanotechnological innovations impacting the clean renewable energy economy. Many environmentally friendly energy sources are considered clean since they produce minimal pollution and greenhouse gas emissions; however, not all are renewable. This manuscript focuses on experimental achievements where nanophysics helps reduce the operating costs of clean renewable energy by improving efficiency indicators, thereby ensuring energy sustainability. Improving material properties at the nanoscale, increasing the active surface areas of reactants, achieving precise control of the physical properties of nano-objects, and using advanced nanoscale characterization techniques are the subject of this in-depth analysis. This will allow the reader to understand how nanomaterials can be engineered with specific applications in clean energy technologies. A special emphasis is placed on the role of such signs of progress in hydrogen production and clean storage methods, as green hydrogen technologies are unavoidable in the current panorama of energy sustainability.

Mn-enhanced performance of the Ni-CaO/γ-Al2O3 dual function material for CO2 capture and in situ methanation

The CH4 yield over dual functional materials (DFMs) remains low and requires further improvement. In this work, we first examined the influence of Mn on the performance of the Ni-CaO/γ-Al2O3 DFM for CO2 capture and in situ methanation. Our results showed that the MnNi-DFM-3 (MnNi-CaO/γ-Al2O3 DFM) exhibited the best performance at 350 °C, with a CH4 yield of 0.56 mmol/g which is 4 times higher than that of the Ni-DFM-1 (Ni-CaO/γ-Al2O3 DFM) (0.14 mmol/g). Nanoscale characterization revealed that highly scattered Mn3O4 acted as a barrier preventing the agglomeration of Ni-based catalysts. Furthermore, our density functional theory (DFT) analysis demonstrated that the introduction of Mn enhanced the activation of CO2, promoted the dissociation of H2 and intermediates, and reduced the activation energy needed to produce carboxylic acid intermediates on the Ni catalyst. The prepared MnNi-DFM is promising to be a cheap efficient material for CO2 capture and in situ methanation. This work opens up a new pathway for enhancing the performance of DFMs using inexpensive transition metals.

Study on the global and nano-scale characterization of heat-induced changes in ordinary Portland cement paste

Cement-based composite materials can be damaged by distributed micro-cracking and degradation of hydration products when exposed to sustained high temperatures. In this study, a nano-scale characterization tool (dynamic nanoindentation) and global mechanical methods (vibration resonance frequency and damping) are employed to better understand the degradation of ordinary Portland cement paste subjected to high temperature exposures. A connection between the methods is demonstrated.

Nano-scale characterization of iron-carbohydrate complexes by cryogenic scanning transmission electron microscopy: Building the bridge to biorelevant characterization

Iron deficiency and iron deficiency anemia pose significant health challenges worldwide. Iron carbohydrate nanoparticles administered intravenously are a mainstay of treatment to deliver elemental iron safely and effectively. However, despite decades of clinical use, a complete understanding of their physical structure and the significance for their behavior, particularly at the nano-bio interface, is still lacking, underscoring the need to employ more sophisticated characterization methods. Our study used cryogenic Scanning Transmission Electron Microscopy (cryo-STEM) to examine iron carbohydrate nanoparticle morphology. This method builds upon previous research, where direct visualization of the iron cores in these complexes was achieved using cryogenic Transmission Electron Microscopy (cryo-TEM). Our study confirms that the average size of the iron cores within these nanoparticles is approximately 2 nm across all iron-based products studied. Furthermore, our investigation revealed the existence of discernible cluster-like morphologies, not only for ferumoxytol, as previously reported, but also within all the examined iron-carbohydrate products. The application of cryo-STEM for the analyses of product morphologies provides high-contrast and high-resolution images of the nanoparticles, and facilitates the characterization at liquid nitrogen temperature, thereby preserving the structural integrity of these complex samples. The findings from this study offer valuable insights into the physical structure of iron-carbohydrate nanoparticles, a crucial step towards unraveling the intricate relationship between the structure and function of this widely used drug class in treating iron deficiency. Additionally, we developed and utilized the self-supervised machine learning workflow for the image analysis of iron-carbohydrate complexes, which might be further expanded into a useful characterization tool for comparability studies.

Nanoscale Characterization of a Novel Electro-Chemical Memory Device by STEM-EELS

Nanoscale Characterization of a Novel Electro-Chemical Memory Device by STEM-EELS

From Nanoscale to Macroscale Characterization of Sulfur-Modified Oxidized Carbon Nanotubes in Styrene Butadiene Rubber Compounds.

The homogeneous dispersion of carbon nanotubes (CNTs) in a rubber matrix is a key factor limiting their amazing potential. CNTs tend to agglomerate into bundles due to van der Waals interactions. To overcome this limitation, CNTs have been surface-modified with oxygen-bearing groups and sulfur. Using atomic force microscopy (AFM) techniques, a deep nanoscale characterization of the morphology, the degree of dispersion of the CNTs in the styrene butadiene rubber (SBR) matrix, and the thickness of the interfacial layer was carried out in this study. In this context, the results from nanoscale characterization showed that the thermal oxidation-sulfur treatment leads to a composite with better dispersion in the matrix, as well as a thicker interfacial layer, indicating a stronger filler-rubber interaction. The second part of this work focused on the macroscale results, such as the Payne effect, vulcanization curves, and mechanical properties. The Payne effect, vulcanization curves, and mechanical properties confirmed the lower reinforcing effect observed in the case of the chemical oxidation treatment because, on the one hand, this composite showed the highest agglomeration of CNTs after the acid treatment. On the other hand, the presence of acid residues provoked the absorption of basic accelerators on the surface of the CNTs.

Novel Detection Scheme for Temporal and Spectral X-Ray Optical Analysis: Study of Triple-Cation Perovskites

Multimodal x-ray microscopy is key to assessing the property-functionality relationships of semiconductor devices with the utmost sensitivity and spatial resolution. Here, we report on a novel setup—the “Analyzer of X-ray excited Optical Luminescence Offering Temporal and spectraL resolution” (AXOLOTL)—and demonstrate its use by investigating a series of triple-cation mixed-halide perovskite solar cells (PSCs) with varying Cs content. These PSCs exhibit spatially varying performance and are thus ideally probed by multimodal x-ray microscopy to elucidate the origin of the performance variations. Specifically, our nanoscale characterization of the wrinkled perovskite photoabsorber unveils a segregation of I and Br, which is accompanied by a narrowed band gap and an increased charge-carrier lifetime in thick absorber areas. Overall, we demonstrate with this technique the spatial correlation of compositional inhomogeneities, topography, electrical performance, and optical performance, which is of highest interest for identifying loss mechanisms at the nanoscale in high-performance electronic device development, including solar cells. Published by the American Physical Society 2024

Efficient nanoscale characterization of wafer surfaces using intelligent sampling and Bayesian optimization

The geometrical attributes of a wafer, such as thickness, uniformity, and local curvature, serve as eminent determinants of its quality. Therefore, measurements that are both rapid and accurate are paramount as multi-stage fabrication processes hinge on them to ensure high product reliability, proper process control, and maximum efficiency. The manual wafer profiling measurement approach in use today is, unfortunately, a time-consuming process. This creates a need for fast and prompt analysis of wafer attributes. This research thus proposes an iterative sampling method that boasts reducing the number of samplings down to a minimum without the need to discard a sufficient level of accuracy for the purpose of reliable attribute estimation. Subsequently, we suggest a series of methods to improve the monitoring and evaluation of the surface topography, all within the context of ultra-precision/nanoscale manufacturing processes, such as ultra-precision machining (UPM) and chemical–mechanical planarization (CMP). For the purpose of both real-time and exception-based detection of anomalies in the UPM process, we constructed a process-machine interaction (PMI) model with Bayesian learning, which amalgamates the received data across heterogeneous sensors such as force, vibration, and acoustic emission in situ. Similarly, the CMP process is quantitatively characterized by a multi-scaled multilayer nonlinear decomposition model with predictive capabilities. This model helps understand the physio-mechanical phenomena underlying both CMP and the UPM processes and describe and predict the nonlinear interactions, as evidenced by the experimentally collected vibration signal patterns.

A quantum sensing metrology for magnetic memories

Magnetic random access memory (MRAM) is a leading emergent memory technology that is poised to replace current non-volatile memory technologies such as eFlash. However, controlling and improving distributions of device properties becomes a key enabler of new applications at this stage of technology development. Here, we introduce a non-contact metrology technique deploying scanning NV magnetometry (SNVM) to investigate MRAM performance at the individual bit level. We demonstrate magnetic reversal characterization in individual, <60 nm-sized bits, to extract key magnetic properties, thermal stability, and switching statistics, and thereby gauge bit-to-bit uniformity. We showcase the performance of our method by benchmarking two distinct bit etching processes immediately after pattern formation. In contrast to ensemble averaging methods such as perpendicular magneto-optical Kerr effect, we show that it is possible to identify out of distribution (tail-bits) bits that seem associated to the edges of the array, enabling failure analysis of tail bits. Our findings highlight the potential of nanoscale quantum sensing of MRAM devices for early-stage screening in the processing line, paving the way for future incorporation of this nanoscale characterization tool in the semiconductor industry.

Conformation Influence of DNA on the Detection Signal through Solid-State Nanopores.

The detection and identification of nanoscale molecules are crucial, but traditional technology comes with a high cost and requires skilled operators. Solid-state nanopores are new powerful tools for discerning the three-dimensional shape and size of molecules, enabling the translation of molecular structural information into electric signals. Here, DNA molecules with different shapes were designed to explore the effects of electroosmotic forces (EOF), electrophoretic forces (EPF), and volume exclusion on electric signals within solid-state nanopores. Our results revealed that the electroosmotic force was the main driving force for single-stranded DNA (ssDNA), whereas double-stranded DNA (dsDNA) was primarily dominated by electrophoretic forces in nanopores. Moreover, dsDNA caused greater amplitude signals and moved faster through the nanopore due to its larger diameter and carrying more charges. Furthermore, at the same charge level and amount of bases, circular dsDNA exhibited a tighter structure compared to brush DNA, resulting in a shorter length. Consequently, circular dsDNA caused higher current-blocking amplitudes and faster passage speeds. The characterization approach based on nanopores allows researchers to get molecular information about size and shape in real time. These findings suggest that nanopore detection has the potential to streamline nanoscale characterization and analysis, potentially reducing both the cost and complexity.

Tip-enhanced Raman scattering and near-field optical imaging of semiconducting monolayer and few-layer MoTe2

Transition metal dichalcogenides (TMDs) offer exceptional platforms to study unique phenomena in two-dimensional (2D) materials. The understanding of phonon interactions in atomically thin TMDs is crucial for the development of novel applications. However, advancing our knowledge on phonon dynamics in TMDs under optical, thermal, electric, and strain perturbations requires comprehensive and minimally invasive chemical imaging techniques with nanoscale spatial resolution. Tip-enhanced Raman scattering (TERS) provides new promising avenues towards this goal while also enabling a detailed analysis of structural heterogeneity. Here, we demonstrate gap-mode TERS imaging of mechanically exfoliated monolayer and few-layer 2H–MoTe2. At 633 nm, 671 nm, and 785 nm laser excitations, we report an overwhelmingly selective TERS enhancement of the out-of-plane A1g phonon mode relative to in-plane E12g phonon mode for mono-to few-layer MoTe2. The pure near-field spectral line shapes are clearly distinct from the well-characterized far-field counterparts. We demonstrate that near-field interactions of selective phonon modes are extremely sensitive to the excitation wavelength, sample thickness, and structural defects. Our results therefore provide fundamental information for the nanoscale characterization of semiconducting MoTe2-based devices.

Towards a new impact geochronometer: Deformation microstructures and U-Pb systematics of shocked xenotime

Shock-deformation microstructures in xenotime have been proposed to record diagnostic evidence for meteorite impacts. Evaluating the potential for impact-induced U-Pb age resetting of the various microstructures that form in shocked xenotime remains largely unexplored. In this study, we investigate the U-Pb systematics of shocked xenotime from three impact structures, including Vredefort (South Africa), Santa Fe (New Mexico, USA), and Araguainha (Brazil). Xenotime at these sites is found in shocked granite, impact melt rock, and as detrital grains, and preserves a range of impact-induced microstructures, including planar fractures, planar deformation bands, deformation twins, and polycrystalline neoblastic grains. Microstructures in xenotime were characterised by electron backscatter diffraction (EBSD) and then targeted for U-Pb geochronology. Secondary ion mass spectrometry (SIMS) and correlated atom probe tomography (APT) were used to determine age and element mobility mechanisms at micrometer- to nanometer-scale. At the precision of SIMS spots, grain areas characterised by lattice deformation microstructures do not show evidence of U-Pb system resetting. In contrast, some grains with neoblastic textures were found to yield impact ages, with U-Pb disturbance correlating to the extent of grain recrystallisation. The APT data showed nanoscale compositional heterogeneities in the form of Pb*-Ca enriched clusters, dislocations arrays, and grain boundaries, the latter with higher concentration of trace elements such as Si, Mg, Ca, Na, Cl, and Al. Combining microstructural, geochronological and nanoscale characterisation, this study demonstrates that neoblastic microstructures can yield accurate impact ages. Shocked xenotime with neoblastic texture is the most reliable geochronometer for dating impact events.

Bridging Nanomanufacturing and Artificial Intelligence-A Comprehensive Review.

Nanomanufacturing and digital manufacturing (DM) are defining the forefront of the fourth industrial revolution-Industry 4.0-as enabling technologies for the processing of materials spanning several length scales. This review delineates the evolution of nanomaterials and nanomanufacturing in the digital age for applications in medicine, robotics, sensory technology, semiconductors, and consumer electronics. The incorporation of artificial intelligence (AI) tools to explore nanomaterial synthesis, optimize nanomanufacturing processes, and aid high-fidelity nanoscale characterization is discussed. This paper elaborates on different machine-learning and deep-learning algorithms for analyzing nanoscale images, designing nanomaterials, and nano quality assurance. The challenges associated with the application of machine- and deep-learning models to achieve robust and accurate predictions are outlined. The prospects of incorporating sophisticated AI algorithms such as reinforced learning, explainable artificial intelligence (XAI), big data analytics for material synthesis, manufacturing process innovation, and nanosystem integration are discussed.

Nanoscale Spectroscopic Identification and Characterization of Minerals and Organic Matter in Ryugu Particles

AbstractCarbonaceous asteroids are leftover materials from the early solar system. They did not undergo planetary differentiation processes and thus still retained signatures and clues of the origin and evolution of the solar system. Thus, samples of carbonaceous asteroids provide significant potential for deciphering the origin of the solar system. The Hayabusa2 spacecraft returned the first samples of a carbonaceous asteroid (162173) Ryugu. In this work, we report the nanoscale mineralogy and organic matter content of two Ryugu particles, A0030 and C0034. These were analyzed by highly novel scattering‐type scanning near‐field optical microscopy (s‐SNOM)‐based nanoscale‐Fourier transform infrared (nano‐FTIR) spectroscopy with ∼20 nm spatial resolution. The nano‐FTIR measurements were supported by confocal micro‐Raman imaging and spectroscopy (∼500 nm/pixel spatial sampling). Our investigations show that the two Ryugu particles (a) contain different silicate mineralogies, indicating heterogeneous and incomplete aqueous alteration and (b) are highly rich in organic matter, consisting a variety of molecular functional groups. The spatial distributions of chemical functional groups and their associations based on pseudo‐heterodyne (PsHet) SNOM imaging show that the organic matter is distributed as either diffused or discrete grains. Micro‐Raman spectra show that the Ryugu particles experienced minimal thermal metamorphism, although A0030 was slightly more heated than C0034. The identification of abundant nanoscale organic molecules within the Ryugu grains that could not be identified via micrometer‐scale investigations emphasizes the importance of using nanoscale nondestructive methods for studying primitive solar system materials, such as Ryugu and OSIRIS‐Rex particles and those that will be returned in the future (such as MMX samples).

Label-Free In Situ Chemical Characterization of Amyloid Plaques in Human Brain Tissues.

The accumulation of amyloid plaques and increased brain redox burdens are neuropathological hallmarks of Alzheimer's disease. Altered metabolism of essential biometals is another feature of Alzheimer's, with amyloid plaques representing sites of disturbed metal homeostasis. Despite these observations, metal-targeting disease treatments have not been therapeutically effective to date. A better understanding of amyloid plaque composition and the role of the metals associated with them is critical. To establish this knowledge, the ability to resolve chemical variations at nanometer length scales relevant to biology is essential. Here, we present a methodology for the label-free, nanoscale chemical characterization of amyloid plaques within human Alzheimer's disease tissue using synchrotron X-ray spectromicroscopy. Our approach exploits a C-H carbon absorption feature, consistent with the presence of lipids, to visualize amyloid plaques selectively against the tissue background, allowing chemical analysis to be performed without the addition of amyloid dyes that alter the native sample chemistry. Using this approach, we show that amyloid plaques contain elevated levels of calcium, carbonates, and iron compared to the surrounding brain tissue. Chemical analysis of iron within plaques revealed the presence of chemically reduced, low-oxidation-state phases, including ferromagnetic metallic iron. The zero-oxidation state of ferromagnetic iron determines its high chemical reactivity and so may contribute to the redox burden in the Alzheimer's brain and thus drive neurodegeneration. Ferromagnetic metallic iron has no established physiological function in the brain and may represent a target for therapies designed to lower redox burdens in Alzheimer's disease. Additionally, ferromagnetic metallic iron has magnetic properties that are distinct from the iron oxide forms predominant in tissue, which might be exploitable for the in vivo detection of amyloid pathologies using magnetically sensitive imaging. We anticipate that this label-free X-ray imaging approach will provide further insights into the chemical composition of amyloid plaques, facilitating better understanding of how plaques influence the course of Alzheimer's disease.

Nano-Scale and Macro-Scale Characterizations of the Effects of Recycled Plastics on Asphalt Binder Properties

This paper summarizes the results of one of the first comprehensive laboratory studies that was conducted to evaluate the effects of adding different contents of recycled polyethylene terephthalate (rPETE) as a modifier to an asphalt binder on the rheological and mechanical properties of the modified binder as well as on the agglomeration behavior between the rPETE and asphalt binder at a multiscale level. The high-temperature and low-temperature performances of the modified binder were investigated at the macro-scale and compared with those of the unmodified binder using dynamic shear rheometer (DSR) and bending-beam rheometer (BBR) rheological tests, as well as asphalt binder cracking device (ABCD) testing. The nano-scale evaluation of the binder properties, including the surface roughness, bonding energy, and reduced modulus, was accomplished using atomic force microscopy (AFM). The results indicated that the addition of rPETE enhanced the high- and intermediate-temperature rheological properties of the modified PG 64-22 binder. The low-temperature rheological properties and resistance to cracking decreased slightly with increasing rPETE content in the asphalt binder. However, this reduction was not remarkable when adding 4%, 8%, and 10% rPETE contents. The asphalt binder modified with 4% rPETE had a low-temperature grade of −22, similar to that of the unmodified binder, indicating that 4% rPETE can be added to the binder to improve its high- and intermediate-temperature properties without reducing its resistance to low-temperature damage. The AFM tapping-mode results indicated that the inclusion of rPETE in the asphalt binder improved the stiffness properties of the modified binder as compared with those of the control asphalt binder. In addition, the rPETE-modified binders showed rougher surfaces than the control binder. The addition of rPETE to the binder increased the values of the reduced modulus and bonding energy compared with those of the control binder.

Synthesis of nanocrystalline nickel via pulsed current electrodeposition in additive-free deposition bath and comparison of nanoscale characterization

An experimental investigation on synthesis of nanocrystalline nickels by pulsed current electrodeposition has been carried out in an additive-free Watts bath employing nickel-sulphate solution with similar nickel ion concentrations. Aluminum was used as a substrate. It demonstrated the advantage of easier removal process of electrodeposited nanocrystalline nickel from its substrate. Whereas the use of high-purity nickel anode was intended to replace nickel ions, which decreased during electrodeposition. Different peak current densities of 450, 750 and 1000 mA/cm2 were applied. A pulsed current was set at a similar pulse pattern of on-time and off-time of 1 ms and 9 ms respectively. The shorter on-time demonstrated the ability to limit ion deposition, which was related to the formation of finer grains. The off-time arrangement was targeted to ensure that the ion mobility had completely stopped. Higher current density demonstrated a dominant impact on deposits, generating a higher nucleation rate that is related to depositing nanocrystalline nickel. A peak current density of 1000 mA/cm2 produced grain sizes in the nanoscale regime. Without any additional additive, nanocrystalline nickel was successfully yielded. Investigation of grain size obtained from the 1000 mA/cm2 has been conducted by extracting full width at half maximum peak intensity (FWHM) revealed from X-ray diffraction (XRD) and Transmission Electron Microscopy (TEM) exhibited consistent results of 22 nm and 25.4±3.4 nm, respectively. It is also evidence of the significant role of pulsed current density. In inclusion, nanocrystalline nickel can be synthesized in an electrodeposition bath without any addition of additives