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

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

CLAIRE—Parallelized Diffeomorphic Image Registration for Large-Scale Biomedical Imaging Applications

We study the performance of CLAIRE—a diffeomorphic multi-node, multi-GPU image-registration algorithm and software—in large-scale biomedical imaging applications with billions of voxels. At such resolutions, most existing software packages for diffeomorphic image registration are prohibitively expensive. As a result, practitioners first significantly downsample the original images and then register them using existing tools. Our main contribution is an extensive analysis of the impact of downsampling on registration performance. We study this impact by comparing full-resolution registrations obtained with CLAIRE to lower resolution registrations for synthetic and real-world imaging datasets. Our results suggest that registration at full resolution can yield a superior registration quality—but not always. For example, downsampling a synthetic image from 10243 to 2563 decreases the Dice coefficient from 92% to 79%. However, the differences are less pronounced for noisy or low contrast high resolution images. CLAIRE allows us not only to register images of clinically relevant size in a few seconds but also to register images at unprecedented resolution in reasonable time. The highest resolution considered are CLARITY images of size 2816×3016×1162. To the best of our knowledge, this is the first study on image registration quality at such resolutions.

Himthani, Naveen↗
DOE OSTI2024

Probing the optical properties and toxicological profile of zinc tungstate nanorods

Zinc tungstate is a semiconductor known for its favorable photocatalytic, photoluminescence, and scintillation properties, coupled with its relatively low cost, reduced toxicity, and high stability in biological and catalytic environments. In particular, zinc tungstate evinces scintillation properties, namely the ability to emit visible light upon absorption of energetic radiation such as x rays, which has led to applications not only as radiation detectors but also for biomedical applications involving the delivery of optical light to deep tissue, such as photodynamic therapy and optogenetics. Here, we report on the synthesis of zinc tungstate nanorods generated via an optimized but facile method, which allows for synthetic control over the aspect ratio of the as-synthesized anisotropic motifs via rational variation of the solution pH. Additionally, we investigate the effect of aspect ratio on their resulting photoluminescent and radioluminescent properties. We further demonstrate the potential of these zinc tungstate nanorods for biomedical applications, such as photodynamic therapy for cancer treatment, by analyzing their toxicological profile within cell lines and neurons.

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

Application of lipid-stabilized liquid-liquid interfaces in 3D printing of biomaterials

Developing strategies to stabilize liquid-liquid interfaces is essential for advancing applications in various biomedical systems. This study introduces a novel biocompatible in situ-forming material in which lipid self-assembly stabilizes water–oil interfaces, enabling controlled structuring of liquids through liquid-in-liquid 3D printing. The stabilization process, driven by the formation of nanostructures at the interface, is thoroughly analyzed through small-angle X-ray scattering (SAXS), rheometry, and microscopy techniques. This material system enables the fabrication of complex 3D constructs, including fibers, substrates, and microneedle patches, which exhibit outstanding mechanical properties and biocompatibility, as confirmed by tensile testing and cell viability tests. Here, by leveraging the unique properties of lipid-stabilized interfaces, this work demonstrates the potential of this approach for diverse biomedical applications such as drug delivery and tissue engineering while establishing a foundation for future advancements in liquid-in-liquid 3D printing technology.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Investigation of the photoluminescent properties, scintillation behaviour and toxicological profile of various magnesium tungstate nanoscale motifs

We have synthesized several morphologies and crystal structures of MgWO 4 using a one-pot hydrothermal method, producing not only monoclinic stars and large nanoparticles but also triclinic wool balls and sub-10 nm nanoparticles. Herein we describe the importance of reaction parameters in demonstrating morphology control of as-prepared MgWO 4 . Moreover, we correlate structure and composition with the resulting photoluminescence and radioluminescence properties. Specifically, triclinic-phase samples yielded a photoluminescence emission of 421 nm, whereas monoclinic-phase materials gave rise to an emission maximum of 515 nm. The corresponding radioluminescence data were characterized by a broad emission peak, located at 500 nm for all samples. Annealing the wool balls and sub-10 nm particles to transform the crystal structure from a triclinic to a monoclinic phase yielded a radioluminescence (RL) emission signal that was two orders of magnitude greater than that of their unannealed counterparts. Finally, to confirm the practical utility of these materials for biomedical applications, a series of sub-10 nm particles, including as-prepared and annealed samples, were functionalized with biocompatible PEG molecules, and subsequently were found to be readily taken up by various cell lines as well as primary cultured hippocampal neurons with low levels of toxicity, thereby highlighting for the first time the potential of this particular class of metal oxides as viable and readily generated platforms for a range of biomedical applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Biobased Semi-Interpenetrating Polymer Networks of Poly(ε-caprolactone) and Epoxidized Soybean Oil with Nanoscale Morphology, Shape-Memory Effect, and Biocompatibility

Creating biobased polymer blends with outstanding properties, nanoscale morphology, shape-memory capability, and biocompatibility is very crucial and requires a fundamental understanding of the phase behavior, macromolecular structure, and biological compatibility of the polymer blends with living cells. It is very critical to understand the complex relationships among the polymer structure, morphology, and performance of multifunctional smart materials under conditions that they are likely to encounter during use, particularly in biomedical applications. Biobased semi-interpenetrating polymer networks of poly(ε-caprolactone) and epoxidized soybean oil with nanoscale morphology have been successfully synthesized via in situ cationic polymerization and compatibilization in a homogeneous solution. Varies analytical and characterization techniques, such as Fourier transform infrared spectroscopy, differential scanning calorimetry, dynamic mechanical analysis, transmission electron microscopy, X-ray scattering, cell toxicity, and shape-memory effects (SMEs), have been employed to understand the structure–properties relationship of these smart, biobased nanostructured polymer blends. The synthesized nano blends were nontoxic or biocompatible and supported attachment of human vein endothelial cells, showing their potential use in biomedical applications. The current versatile, low-cost strategy for synthesizing the nanoscale morphology of semi-interpenetrating polymer networks with SMEs and biocompatibility should be widely applicable for polymer systems. This study is also considered as a continuation to our efforts in the area of biobased polymers to develop innovative technologies to transform natural resources into smart multifunctional materials for a wide range of applications, including coatings, adhesives, and medical devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Wireless Frequency‐Multiplexed Acoustic Array‐Based Acoustofluidics

Abstract Acoustofluidics has shown great potential in enabling on‐chip technologies for driving liquid flows and manipulating particles and cells for engineering, chemical, and biomedical applications. To introduce on‐demand liquid sample processing and micro/nano‐object manipulation functions to wearable and embeddable electronics, wireless acoustofluidic chips are highly desired. This paper presents wireless acoustofluidic chips to generate acoustic waves carrying sufficient energy and achieve key acoustofluidic functions, including arranging particles and cells, generating fluid streaming, and enriching in‐droplet particles. To enable these functions, the wireless acoustofluidic chips leverage mechanisms, including inductive coupling‐based wireless power transfer (WPT), frequency multiplexing‐based control of multiple acoustic waves, and the resultant acoustic radiation and drag forces. For validation, the wirelessly generated acoustic waves are measured using laser vibrometry when different materials (e.g., bone, tissue, and hand) are inserted between the WPT transmitter and receiver. Moreover, the wireless acoustofluidic chips successfully arrange nanoparticles into different patterns, align cells into parallel pearl chains, generate streaming, and enrich in‐droplet microparticles. This research is anticipated to facilitate the development of embeddable wireless on‐chip flow generators, wearable sensors with liquid sample processing functions, and implantable devices with flow generation and acoustic stimulation abilities for engineering, veterinary, and biomedical applications.

Li, Jiali↗
DOE OSTI2021

In-situ Investigations on Gold Nanoparticles Stabilization Mechanisms in Biological Environments Containing HSA

Nanoparticles (NPs) developments advance innovative biomedical applications. However, complex interactions and the low colloidal stability of NPs in biological media restrict their widespread utilization. The influence of NPs properties on the colloidal stability for gold NPs with 5 and 40 nm in diameter with two surface modifications, methoxy-polyethylene glycol-sulfhydryl (PEG) and citrate, in NaCl and human serum albumin (HSA) protein solution, is investigated. This study is based on small-angle X-ray scattering (SAXS) methods allowing the in-situ monitoring of interactions in physiological conditions. The PEG coating provides high colloidal stability for NPs of both sizes. For 5 nm NPs in NaCl solution, a stable 3D self-assembled body-centered cubic (BCC) arrangement is detected with an interparticle distance of 20.7 ± 0.1 nm. In protein solution, this distance increases to 21.9 ± 0.1 nm by protein penetration inside the ordered structure. For citrate-capped NPs, a different mechanism is observed. The protein particles attach to the NPs surfaces, and an appropriate concentration of proteins results in a stable suspension. Cryogenic transmission electron microscopy (Cryo-TEM), UV–visible spectroscopy, and dynamic light scattering (DLS) support the SAXS results. The findings will pave the way to design and synthesize NPs with controlled behaviors in biomedical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Computationally guided synthesis of carbon coated mesoporous silica materials

Mesoporous silica materials (MSMs) are well-suited for biomedical applications due to their unique features, including a large surface area and tunable pore size. To enhance their durability, the small pores in MSMs are filled with carbon precursors and then carbonized to prevent them from interacting with unreacted silicic acid. Here, in this study, we synthesized and healed MSMs using a combination of non-reactive and reactive molecular dynamics (MD) simulations. The non-reactive MD simulation revealed that the self-assembly of Pluronic® L64 polymers in water resulted in nearly 80 % hydrogen bonds between the hydrophilic sections of the micelle and water. In the bond-boosted ReaxFF MD simulations, silicic acid precursors were condensed on the micelle surface, with over 60 % of them leading to the creation of periodic mesoporous silica within the system. Condensation of silicic acid precursors at 300 K with bond-boosting and at 1500 K without it both significantly promoted the polymerization of Si(OH) 4 , with the latter doubling the rate compared to the former. Subsequently, we healed the MSM surface by carbonizing carbon precursors inside an MSM pore. Polyethylene (PE) and high-rank lignite were identified as the most suitable precursors due to their ability to form turbostratic graphene structures. High-rank lignite exhibited the highest carbon conversion ratio to 6-membered rings, closely followed by PE, in the carbon ring formation analysis. Additionally, the production of gases, such as H 2 , increased significantly for PE at both 2200 K and 2600 K, indicating the conversion of a considerable portion of carbon into graphitic or turbostratic structures. The carbonization of PE primarily led to the formation of planar (sp 2 ) structures, while sucrose yielded the least planar structures. Finally, we studied the protective blocking of unreacted silicic acid precursor by considering a PET turbostratic graphene structure in a silica mesopore formed at 2600 K. The trajectory analysis showed that the surface of the silica was effectively coated with PET tar, preventing unreacted silicic acid from interacting with the inner silica pore surface. These findings offer valuable insights into the synthesis and carbonization-based healing processes of MSMs, enhancing their potential for various biomedical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, and robustness. Inspired by the concept of Edge Artificial Intelligence (Edge AI), we propose a robust approach that enables fast FLI with no degradation of accuracy. This approach couples a recurrent neural network (RNN), which is trained to estimate the fluorescence lifetime directly from raw timestamps without building histograms, to SPAD TCSPC systems, thereby drastically reducing transfer data volumes and hardware resource utilization, and enabling real-time FLI acquisition. We train two variants of the RNN on a synthetic dataset and compare the results to those obtained using center-of-mass method (CMM) and least squares fitting (LS fitting). Results demonstrate that two RNN variants, gated recurrent unit (GRU) and long short-term memory (LSTM), are comparable to CMM and LS fitting in terms of accuracy, while outperforming them in the presence of background noise by a large margin. To explore the ultimate limits of the approach, we derive the Cramer-Rao lower bound of the measurement, showing that RNN yields lifetime estimations with near-optimal precision. To demonstrate real-time operation, we build a FLI microscope based on an existing SPAD TCSPC system comprising a 32 x 32 SPAD sensor named Piccolo. Four quantized GRU cores, capable of processing up to 4 million photons per second, are deployed on the Xilinx Kintex-7 FPGA that controls the Piccolo. Powered by the GRU, the FLI setup can retrieve real-time fluorescence lifetime images at up to 10 frames per second. The proposed FLI system is promising and ideally suited for biomedical applications, including biological imaging, biomedical diagnostics, and fluorescence-assisted surgery, etc.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Competing Magnetic Interactions and Field-Induced Metamagnetic Transition in Highly Crystalline Phase-Tunable Iron Oxide Nanorods

The inherent existence of multi phases in iron oxide nanostructures highlights the significance of them being investigated deliberately to understand and possibly control the phases. Here, the effects of annealing at 250 °C with a variable duration on the bulk magnetic and structural properties of high aspect ratio biphase iron oxide nanorods with ferrimagnetic Fe3O4 and antiferromagnetic α-Fe2O3 are explored. Increasing annealing time under a free flow of oxygen enhanced the α-Fe2O3 volume fraction and improved the crystallinity of the Fe3O4 phase, identified in changes in the magnetization as a function of annealing time. A critical annealing time of approximately 3 h maximized the presence of both phases, as observed via an enhancement in the magnetization and an interfacial pinning effect. This is attributed to disordered spins separating the magnetically distinct phases which tend to align with the application of a magnetic field at high temperatures. The increased antiferromagnetic phase can be distinguished due to the field-induced metamagnetic transitions observed in structures annealed for more than 3 h and was especially prominent in the 9 h annealed sample. Our controlled study in determining the changes in volume fractions with annealing time will enable precise control over phase tunability in iron oxide nanorods, allowing custom-made phase volume fractions in different applications ranging from spintronics to biomedical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Engineered Glucose Oxidase‐Carbon Nanotube Conjugates for Tissue‐Translatable Glucose Nanosensors

Abstract Continuous and non‐invasive glucose monitoring and imaging is important for disease diagnosis, treatment, and management. However, glucose monitoring remains a technical challenge owing to the dearth of tissue‐transparent glucose sensors. In this study, we present the development of near‐infrared fluorescent single‐walled carbon nanotube (SWCNT) based nanosensors directly functionalized with glucose oxidase (GOx) capable of immediate and reversible glucose imaging in biological fluids and tissues. We prepared GOx‐SWCNT nanosensors by facile sonication of SWCNT with GOx in a manner that—surprisingly—does not compromise the ability of GOx to detect glucose. Importantly, we find by using denatured GOx that the fluorescence modulation of GOx‐SWCNT is not associated with the catalytic oxidation of glucose but rather triggered by glucose‐GOx binding. Leveraging the unique response mechanism of GOx‐SWCNT nanosensors, we developed catalytically inactive apo‐GOx‐SWCNT that enables both sensitive and reversible glucose imaging, exhibiting a ΔF/F 0 of up to 40 % within 1 s of exposure to glucose without consuming the glucose analyte. We finally demonstrate the potential applicability of apo‐GOx‐SWCNT in biomedical applications by glucose quantification in human plasma and glucose imaging in mouse brain slices.

Chemistry↗
DOE OSTI2021

Electron generation and multiplication at the initial stage of nanosecond breakdown in water

Electrical breakdown of liquid dielectrics under nanosecond pulsed high voltage has been investigated extensively in the last decade. Prior studies have focused on either experimental characterization of the breakdown process and discharge plasma or formulation/verification of the electrostrictive cavitation mechanism of the breakdown initiation. There remain knowledge gaps toward a clear physical picture of how the first plasma is generated in a region saturated by nanoscale cavities created by electrostrictive forces in inhomogeneous fields at the nanosecond timescale. Initial plasma results from the multiplication of primary electrons that gain energy collisionlessly in the cavities to cause collisional ionization of water molecules on the cavity walls. This paper quantitatively discusses the possible sources of primary electrons that seed the plasma discharge. Electron detachment from hydroxide is shown to be the most probable and sustainable electron source. Using numerical modeling, this study demonstrates the plausibility of an electron multiplication mechanism involving two neighboring cavities. The drift of hydrated electrons from one cavity to the next is the rate-limiting step and sets the minimum electric field requirement. Furthermore, this work will inform subsequent experimental studies and have implications in various applications such as plasma sources in biomedical applications, cavitation study, and insulation of pulsed power equipment.

42 ENGINEERING↗
DOE OSTI2021

Carbon Dioxide Conversion to Nanomaterials: Methods, Applications, and Challenges

Anthropogenic carbon dioxide (CO 2 ) emission is one of the biggest global threats that we are confronted with in the 21st century. A lack of prompt action to mitigate the atmospheric CO 2 level could lead to global catastrophic events. As a result of the significance of the aforementioned threat, multiple nations have agreed to enact carbon capture, storage, utilization, and sequestration (CCUS) technologies at academic and industrial scales with the aim of lowering the atmospheric CO 2 level. Although there are many reviews on CCUS technologies, there is a lack of comprehensive review on CO 2 conversion to more economically valuable products, such as nanomaterials. Carbon dioxide capture and conversion into nanomaterials is an interesting research topic in many ways because it contributes to our fundamental knowledge of material conversion, provides alternative ways to reduce atmospheric pollution, and yields lucrative products, which has not been explored broadly. Aside from the positive outcomes, we have a moral obligation to rectify a global threat caused by anthropogenic emission. Herein, we present current methods of converting CO 2 into organic and inorganic nanomaterials with a focus on operating conditions and challenges as well as the potential of nanomaterials in specifically biomedical applications as opposed to extensively reviewed energy-related uses. Furthermore, our review emphasizes the toxicity issues related to using such nanomaterials in biological settings based on literature and other comparable studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Covalent integration of polymers and porous organic frameworks

Covalent integration of polymers and porous organic frameworks (POFs), including metal-organic frameworks (MOFs), covalent organic frameworks (COFs) and hydrogen-bonded organic frameworks (HOFs), represent a promising strategy for overcoming the existing limitations of traditional porous materials. This integration allows for the combination of the advantages of polymers, i.e., flexibility, processability and chemical versatility etc., and the superiority of POFs, like the structural integrity, tunable porosity and the high surface area, creating a type of hybrid materials. These resulting polymer-POF hybrid materials exhibit enhanced mechanical strength, chemical stability and functional diversity, thus opening up new opportunities for applications across a large variety of fields, such as gas separation, catalysis, biomedical applications, environmental remediation and energy storage. In this review, an overview of synthetic routes and strategies on how to covalently integrate different polymers with various POFs is discussed, especially with a particular focus on methods like polymerization within, on and among POF structures. To investigate the unique properties and functions of these resultant hybrid materials, the characterization techniques, including nuclear magnetic resonance spectroscopy (NMR), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), transmission electron microscopy (TEM) and scanning electron microscopy (SEM), gas adsorption analysis (BET) and computational modeling and machine learning, are also presented. The ability of polymer-POFs to manipulate the pore environments at the molecular level affords these materials a wide range of applications, providing a versatile platform for future advancements in material science. Looking forward, to fully realize the potential of these hybrid materials, the authors highlight the scalability, green synthesis methods, and potential for stimuli-responsive polymer-POF materials as critical areas for future research.

Hossain, Md Amjad↗
DOE OSTI2026

Knowledge gaps for neuromorphic ionic computing

BACKGROUND Neuromorphic computing, inspired by the human brain’s ability to process information efficiently, represents a transformative approach to computation. In this Review, we explore the emerging field of neuromorphic ionic computing, which leverages ionic conduction and coupling to mimic neural processes, and identify critical knowledge gaps that must be addressed to realize its full potential. A central theme of the discussion is energy efficiency, a challenge that is both a limitation and an opportunity for this technology. Although complementary metal-oxide semiconductor (CMOS)–based neuromorphic technologies have made strides in scaling to billions of neurons and are increasingly applied in artificial intelligence and numerical computing, they remain orders of magnitude behind the human brain in terms of connectivity and energy efficiency. Neuromorphic ionic computing promises to overcome these limitations by leveraging the distinct architectural and operational principles of the brain. Our brains achieve this energy efficiency by combining several key features: using the same network elements to store and process information; using an incredibly complex and massively interconnected three-dimensional (3D) network of locally active elements that enables sparsity, robustness in the presence of noise, adaptation, and life-long learning; computing at comparatively low voltage and frequency; and last, taking advantage of a plethora of ions and small molecules as information carriers. Here, we propose that ionic computing systems can take advantage of similar features to achieve substantial gains in energy efficiency. ADVANCES Since the first reports of neuromorphic ionic behavior in nanofluidic channels, we have witnessed an explosion of reports that used ionic devices to produce synaptomimetic behaviors. However, achieving the goals of ionic computing requires not only implementation of much more sophisticated device functionality but also overcoming fundamental barriers in materials science, device architecture, and system integration. Current ionic devices, even those incorporating state-of-the-art materials, still suffer from limited functionality and stability, which restrict their performance and increase energy demands. Developing new materials with enhanced ionic properties is essential to overcome these limitations. Similarly, the design of neuromorphic devices must evolve to leverage the particular advantages of ionic processes. Existing architectures often follow a single-information-carrier logic of conventional electronics or are constructed of mesoscale fluidics, failing to capitalize on the energy-efficient mechanisms inherent to ionic systems or implement the multiple-information-carrier paradigm. Current neuromorphic chips focus on large-scale networks of analog memory elements based on mechanisms such as charge trap (flash), filamentary, phase change, or spin, which are built on top of a network of artificial CMOS neurons. Although such prototype networks have achieved impressive performance, it is difficult to envision how they can implement the key features such as massive connectivity, sophisticated plasticity, adaptability, sparsity, and “multichromatic” computing. Although small-scale devices have demonstrated promising results, integrating them, maintaining energy efficiency, and implementing temperature control as systems grow in complexity and size to computationally relevant scale remain major hurdles. Furthermore, interfacing neuromorphic ionic devices with existing computing technologies presents technical and conceptual challenges that will require innovative approaches that combine insights from neuroscience, materials science, and engineering. OUTLOOK Despite these challenges, the potential impact of neuromorphic ionic computing is profound with potential applications ranging from artificial intelligence to robotics and beyond. We also argue that neuromorphic ionic computing systems should not, at least in the beginning, compete with CMOS technologies but rather should focus on applications that require extreme energy efficiency with chemical and/or biological compatibility, such as biomedical applications (for example, brain-computer interfaces), environmental monitoring, and agricultural and food applications. Ultimately, this Review highlights the crucial role of interdisciplinary collaboration in advancing the field. Neuromorphic ionic computing is not merely a technological innovation; it represents a substantial step toward sustainable computation, aligning with the growing demand for energy-conscious solutions in a world that is increasingly reliant on data and computation.

Neuromorphic↗
DOE OSTI2023

Chiral Spectroscopy of Nanostructures

Chirality is ubiquitous in the universe and in living creatures over detectable length scales from the subatomic to the galactic, as exemplified in the two extremes by subatomic particles (neutrinos) and spiral galaxies. Between them are living creatures that display multiple levels of chirality emerging from hierarchically assembled asymmetric building blocks. Not too far from the bottom of this pyramid are the foundational building blocks with chiral atomic centers on sp 3 carbon atoms exemplified by L-amino acids and D-sugars that are self-assembled into higher-order structures with increasing dimensions forming highly complex, amazingly functional, and energy-efficient living systems. The organization and materials employed in their construction inspired scientists to replicate complex living systems via the self-assembly of chiral components. Multiple studies pointed to unexpected and unique electromagnetic properties of chiral structures with nanoscale and microscale dimensions, including giant circular dichroism and collective circularly polarized scattering that their constituent units did not possess. To address the wide variety of chiral geometries observed in continuous materials, singular particles, and their complex systems, multiple analytic techniques are needed. Simultaneously, their spectroscopic properties create a pathway to multiple applications. For example, mirror-asymmetric vibrations at chiral centers formed by sp 3 carbon atoms lead to optical activity for the infrared (IR) wavelength regions. At the same time, understanding the optical activity in, for example, the IR region enables biomedical applications because multiple modalities of biomedical imaging and vibrational optical activity (VOA) of biomolecules are known for IR range. In turn, VOA can be realized in both absorption and emission modalities due to large magnetic transition moments, as vibrational circular dichroism (VCD) or Raman optical activity (ROA) spectroscopy. In addition to the VOA, in the range of longer wavelengths, lattice vibrational mode or phononic behavior occurs in chiral crystals and nanoassemblies, which can be readily detected by terahertz circular dichroism (TCD) spectroscopy. Meanwhile, chiral self-assembly can induce circularly polarized light emission (CPLE) regardless of the existence of chirality in coassembled fluorophores. The CPLE from self-assembled chiral materials is particularly interesting because the CPLE can originate from both circularly polarized luminescence and circularly polarized scattering (CPS). Furthermore, because self-assembled nanostructures often exhibit stronger optical activity than their building blocks owing to dimension and resonance effects, the optical activity of single assembled nanostructures can be investigated by using microscopic technology combined with chiral optics. Here, we describe the state of the art for spectroscopic methods for the comprehensive analysis of chiral nanomaterials at various photon wavelengths, addressed with special attention given to new tools emerging both for materials with self-organized hierarchical chirality and single-particle spectroscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗