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At least 1,099 records · Page 61

WE-DE-207A-04: Advances in Radiological Neuro-Endovascular Interventional Imaging

1. Parallels in the evolution of x-ray angiographic systems and devices used for minimally invasive endovascular therapy Charles Strother - DSA, invented by Dr. Charles Mistretta at UW-Madison, was the technology which enabled the development of minimally invasive endovascular procedures. As DSA became widely available and the potential benefits for accessing the cerebral vasculature from an endovascular approach began to be apparent, industry began efforts to develop tools for use in these procedures. Along with development of catheters, embolic materials, pushable coils and the GDC coils there was simultaneous development and improvement of 2D DSA image quality and the introduction of 3D DSA. Together, these advances resulted in an enormous expansion in the scope and numbers of minimally invasive endovascular procedures. The introduction of flat detectors for c-arm angiographic systems in 2002 provided the possibility of the angiographic suite becoming not just a location for vascular imaging where physiological assessments might also be performed. Over the last decade algorithmic and hardware advances have been sufficient to now realize this potential in clinical practice. The selection of patients for endovascular treatments is enhanced by this dual capability. Along with these advances has been a steady reduction in the radiation exposure required so that today, vascular and soft tissue images may be obtained with equal or in many cases less radiation exposure than is the case for comparable images obtained with multi-detector CT. Learning Objectives: To understand the full capabilities of today’s angiographic suite To understand how c-arm cone beam CT soft tissue imaging can be used for assessments of devices, blood flow and perfusion. Advances in real-time x-ray neuro-endovascular image guidance Stephen Rudin - Reacting to the demands on real-time image guidance for ever finer neurovascular interventions, great improvements in imaging chains are being pursued. For the highest spatial and temporal resolution, x-ray guidance with fluoroscopy and angiography although dominant are still being vastly improved. New detectors such as the Micro-Angiographic Fluoroscope (MAF) and x-ray source designs that enable higher outputs while maintaining small focal spots will be highlighted along with new methods for minimizing the radiation dose to patients. Additionally, new platforms for training and device testing that include patient-specific 3D printed vascular phantoms and new metrics such as generalized relative object detectability for objectively inter-comparing systems will be discussed. This will improve the opportunity for better evaluation of these technological advances which should contribute to the safety and efficacy of image guided minimally invasive neuro-endovascular procedures. Learning Objectives: To understand the operation of new x-ray imaging chain components such as detectors and sources To be informed about the latest testing methods, with 3D printed vascular phantoms, and new evaluation metrics for advanced imaging in x-ray image guided neurovascular interventions Advances in cone beam CT anatomical and functional imaging in angio-suite to enable one-stop-shop stroke imaging workflow Guang-Hong Chen - The introduction of flat-panel detector based cone-beam CT in clinical angiographic imaging systems enabled treating physicians to obtain three-dimensional anatomic roadmaps for bony structure, soft brain tissue, and vasculatures for treatment planning and efficacy checking after the procedures. However, much improvement is needed to reduce image artifacts, reduce radiation dose, and add potential functional imaging capability to provide four-dimensional dynamic information of vasculature and brain perfusion. In this presentation, some of the new techniques developed to address radiation dose issues, image artifact reduction and brain perfusion using C-arm cone-beam CT imaging system will be introduced for the audience. Learning Objectives: To understand the clinical need of one-stop-shop stroke imaging workflow To understand to technical challenges in cone beam CT perfusion To understand the potential technical solutions to enable one-stop-shop imaging workflow Recent advances in devices used in neuro--interventions Mattew Gounis - Over the past two decades, there has been explosive development of medical devices that have revolutionized the endovascular treatment of cerebrovascular diseases. There is now Level 1, Class A evidence that intra-arterial, mechanical thrombectomy in acute ischemic stroke is superior to medical management; and similarly that minimally invasive, endovascular repair of ruptured brain aneurysms is superior to surgical treatment. Stent-retrievers are now standard of care for emergent large vessel occlusions causing a stroke, with a number of patients need to treat for good clinical outcomes as low as 4. Recent technologies such as flow diverters and disrupters, intracranial self-expanding stents, flexible large bore catheters that can reach vessels beyond the circle of Willis, stent-retrievers, and super-compliant balloons are the result of successful miniaturization of design features and novel manufacturing technologies capable of building these devices. This is a rapidly evolving field, and the device technology enabling such advancements will be reviewed. Importantly, image-guidance technology has not kept pace in neurointervention and the ability to adequately characterize these devices in vivo remains a significant opportunity. Learning Objectives: A survey of devices used in neurointerventions, their materials and essential design characteristics Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; G. Chen, Funding received from NIH; funding received from DOD; funding received from GE Healthcare; funding received from Siemens AX.; M. Gounis, consultant for Codman Neurovascular and Stryker Neurovascular; Holds stock in InNeuroCo Inc, research grants: NIH, Medtronic Neurovascular, Microvention/Terumo, Cerevasc LLC, Gentuity, Codman Neurovascular, Philips Healthcare, Stryker Neurovascular, Tay Sachs Foundation, and InNeuroCo Inc.; S. Rudin, Supported in part by NIH Grant R01EB002873 and the Toshiba Medical System Corp.

60 APPLIED LIFE SCIENCES↗

Millikelvin-resolved ambient thermography

Thermography detects surface temperature and subsurface thermal activity of an object based on the Stefan-Boltzmann law. Impacts of the technology would be more far-reaching with finer thermal sensitivity, called noise-equivalent differential temperature (NEDT). Existing efforts to advance NEDT are all focused on improving registration of radiation signals with better cameras, driving the number close to the end of the roadmap at 20 to 40 mK. In this work, we take a distinct approach of sensitizing surface radiation against minute temperature variation of the object. The emissivity of the thermal imaging sensitizer (TIS) rises abruptly at a preprogrammed temperature, driven by a metal-insulator transition in cooperation with photonic resonance in the structure. The NEDT is refined by over 15 times with the TIS to achieve single-digit millikelvin resolution near room temperature, empowering ambient thermography for a broad range of applications such as in operando electronics analysis and early cancer screening.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An orthologous gene coevolution network provides insight into eukaryotic cellular and genomic structure and function

The evolutionary rates of functionally related genes often covary. We present a gene coevolution network inferred from examining nearly 3 million orthologous gene pairs from 332 budding yeast species spanning ~400 million years of evolution. Network modules provide insight into cellular and genomic structure and function. Examination of the phenotypic impact of network perturbation using deletion mutant data from the baker’s yeast Saccharomyces cerevisiae, which were obtained from previously published studies, suggests that fitness in diverse environments is affected by orthologous gene neighborhood and connectivity. Mapping the network onto the chromosomes of S. cerevisiae and Candida albicans revealed that coevolving orthologous genes are not physically clustered in either species; rather, they are often located on different chromosomes or far apart on the same chromosome. The coevolution network captures the hierarchy of cellular structure and function, provides a roadmap for genotype-to-phenotype discovery, and portrays the genome as a linked ensemble of genes.

59 BASIC BIOLOGICAL SCIENCES↗

A metagenomic perspective on the microbial prokaryotic genome census

Following 30 years of sequencing, we assessed the phylogenetic diversity (PD) of >1.5 million microbial genomes in public databases, including metagenome-assembled genomes (MAGs) of uncultivated microbes. As compared to the vast diversity uncovered by metagenomic sequences, cultivated taxa account for a modest portion of the overall diversity, 9.73% in bacteria and 6.55% in archaea, while MAGs contribute 48.54% and 57.05%, respectively. Therefore, a substantial fraction of bacterial (41.73%) and archaeal PD (36.39%) still lacks any genomic representation. This unrepresented diversity manifests primarily at lower taxonomic ranks, exemplified by 134,966 species identified in 18,087 metagenomic samples. Our study exposes diversity hotspots in freshwater, marine subsurface, sediment, soil, and other environments, whereas human samples yielded minimal novelty within the context of existing datasets. These results offer a roadmap for future genome recovery efforts, delineating uncaptured taxa in underexplored environments and underscoring the necessity for renewed isolation and sequencing.

59 BASIC BIOLOGICAL SCIENCES↗

Energy storage: The future enabled by nanomaterials

Lithium-ion batteries, which power portable electronics, electric vehicles, and stationary storage, have been recognized with the 2019 Nobel Prize in chemistry. The development of nanomaterials and their related processing into electrodes and devices can improve the performance and/or development of the existing energy storage systems. We provide a perspective on recent progress in the application of nanomaterials in energy storage devices, such as supercapacitors and batteries. The versatility of nanomaterials can lead to power sources for portable, flexible, foldable, and distributable electronics; electric transportation; and grid-scale storage, as well as integration in living environments and biomedical systems. To overcome limitations of nanomaterials related to high reactivity and chemical instability caused by their high surface area, nanoparticles with different functionalities should be combined in smart architectures on nano- and microscales. The integration of nanomaterials into functional architectures and devices requires the development of advanced manufacturing approaches. We discuss successful strategies and outline a roadmap for the exploitation of nanomaterials for enabling future energy storage applications, such as powering distributed sensor networks and flexible and wearable electronics.

catalysis (heterogeneous)↗

Stenotrophomonas maltophilia differential gene expression in synthetic cystic fibrosis sputum reveals shared and cystic fibrosis strain-specific responses to the sputum environment.

Stenotrophomonas maltophilia is a Gram-negative opportunistic pathogen that can infect the lungs of people with cystic fibrosis (CF). The highly viscous mucus in the CF lung, expectorated as sputum, serves as the primary nutrient source for microbes colonizing this site and induces virulence-associated phenotypes and gene expression in several CF pathogens. Here, we characterized the transcriptional responses of three S. maltophilia strains during exposure to synthetic CF sputum media (SCFM2) to gain insight into how this organism interacts with the host in the CF lung. These efforts led to the identification of 881 transcripts differentially expressed by all three strains, many of which reflect the metabolic pathways used by S. maltophilia in sputum, as well as altered stress responses. The latter correlated with increased resistance to peroxide exposure after pre-growth in SCFM2 for two of the strains. We also compared the SCFM2 transcriptomes of two S. maltophilia CF isolates to that of the acute infection strain, S. maltophilia K279a, allowing us to identify CF isolate-specific signatures in differential gene expression. Expression of genes from the accessory genomes was also differentially altered in response to SCFM2. Finally, a number of biofilm-associated genes were differentially induced in SCFM2, particularly in K279a, which corresponded to increased aggregation and biofilm formation in this strain relative to both CF strains. Collectively, this work details the response of S. maltophilia to an environment that mimics important aspects of the CF lung, identifying potential survival strategies and metabolic pathways used by S. maltophilia during infections. Importance Stenotrophomonas maltophilia is an important infecting bacterium in the airways of people with cystic fibrosis (CF). However, compared to the other CF pathogens, S. maltophilia has been relatively understudied. The significance of our research is to provide insight into the global transcriptomic changes of S. maltophilia in response to a medium that was designed to mimic important aspects of the CF lung. This work allows us to understand the overall metabolic changes that occur when S. maltophilia encounters the CF lung, and generates a roadmap of candidate genes to test using in vitro and in vivo models of CF.

59 BASIC BIOLOGICAL SCIENCES↗

The Single Cells and Cell Populations Viability Estimation in vitro by the Time-Domain Impedance Spectroscopy

In the present study, we investigate the sensitivity and applicability of the time-domain electrical impedance spectroscopy (EIS) techniques, namely Fourier-EIS and adaptive filtering based EIS (AF-EIS), for studying cells' populations and single living cells in natural physiological environment in vitro. Using ultra-violet radiation for decreasing cell life-span we demonstrate the possibility to distinguish the living cells' population from the dead cells by both Fourier-EIS and AF-EIS. However, determining the viability of the single cell requires significant sensitivity, which is inaccessible with the conventional Fourier-EIS contrary to AF-EIS. The latter result stems from the high noise immunity of the AF-EIS, which also makes it possible to provide the measurements using the safe for cells 15-mV excitation voltage and 10–100 nA current response. The developed single-cell AF-EIS approach opens a direct roadmap for creating accurate, robust, and easy to implement toxin and radiation hazard sensors with the living cell as an acting element and proposes a solution for actual ecological and healthcare problems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Software for Sparse Tensor Decomposition on Emerging Computing Architectures

In this paper, we develop software for decomposing sparse tensors that is portable to and performant on a variety of multicore, manycore, and GPU computing architectures. The result is a single code whose performance matches optimized architecture-specific implementations. The key to a portable approach is to determine multiple levels of parallelism that can be mapped in different ways to different architectures, and we explain how to do this for the matricized tensor times Khatri--Rao product (MTTKRP), which is the key kernel in canonical polyadic tensor decomposition. Our implementation leverages the Kokkos framework, which enables a single code to achieve high performance across multiple architectures that differ in how they approach fine-grained parallelism. We also introduce a new construct for portable thread-local arrays, which we call compile-time polymorphic arrays. Not only are the specifics of our approaches and implementation interesting for tuning tensor computations, but they also provide a roadmap for developing other portable high-performance codes. As a last step in optimizing performance, we modify the MTTKRP algorithm itself to do a permuted traversal of tensor nonzeros to reduce atomic-write contention. Lastly, we test the performance of our implementation on 16- and 68-core Intel CPUs and the K80 and P100 NVIDIA GPUs, showing that we are competitive with state-of-the-art architecture-specific codes while having the advantage of being able to run on a variety of architectures.

97 MATHEMATICS AND COMPUTING↗

The critical importance of software for HEP

Particle physics has an ambitious and broad global experimental programme for the coming decades. Large investments in building new facilities are already underway or under consideration. Scaling the present processing power and data storage needs by the foreseen increase in data rates in the next decade for HL-LHC is not sustainable within the current budgets. As a result, a more efficient usage of computing resources is required in order to realise the physics potential of future experiments. Software and computing are an integral part of experimental design, trigger and data acquisition, simulation, reconstruction, and analysis, as well as related theoretical predictions. A significant investment in computing and software is therefore critical. Advances in software and computing, including artificial intelligence (AI) and machine learning (ML), will be key for solving these challenges. Making better use of new processing hardware such as graphical processing units (GPUs) or ARM chips is a growing trend. This forms part of a computing solution that makes efficient use of facilities and contributes to the reduction of the environmental footprint of HEP computing. The HEP community already provided a roadmap for software and computing for the last EPPSU, and this paper updates that, with a focus on the most resource critical parts of our data processing chain.

97 MATHEMATICS AND COMPUTING↗

Navigating the maze: the impact of configurability in bioinformatics software

The bioinformatics software domain contains thousands of applications for automating tasks such as the pairwise alignment of DNA sequences, building and reasoning about metabolic models or simulating growth of an organism. Its end users range from sophisticated developers to those with little computational experience. In response to their needs, developers provide many options to customize the way their algorithms are tuned. Yet there is little or no automated help for the user in determining the consequences or impact of the options they choose. In this paper we describe our experience working with configurable bioinformatics tools. We find limited documentation and help for combining and selecting options along with variation in both functionality and performance. We also find previously undetected faults. We summarize our findings with a set of lessons learned, and present a roadmap for creating automated techniques to interact with bioinformatics software. We believe these will generalize to other types of scientific software.

McDevitt, Mikaela Cashman↗

ARQUIN: Architectures for Multinode Superconducting Quantum Computers

Many proposals to scale quantum technology rely on modular or distributed designs wherein individual quantum processors, called nodes, are linked together to form one large multinode quantum computer (MNQC). One scalable method to construct an MNQC is using superconducting quantum systems with optical interconnects. However, internode gates in these systems may be two to three orders of magnitude noisier and slower than local operations. Surmounting the limitations of internode gates will require improvements in entanglement generation, use of entanglement distillation, and optimized software and compilers. Still, it remains unclear what performance is possible with current hardware and what performance algorithms require. In this article, we employ a systems analysis approach to quantify overall MNQC performance in terms of hardware models of internode links, entanglement distillation, and local architecture. We show how to navigate tradeoffs in entanglement generation and distillation in the context of algorithm performance, lay out how compilers and software should balance between local and internode gates, and discuss when noisy quantum internode links have an advantage over purely classical links. Here, we find that a factor of 10–100× better link performance is required and introduce a research roadmap for the co-design of hardware and software towards the realization of early MNQCs. While we focus on superconducting devices with optical interconnects, our approach is general across MNQC implementations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Modeling Isotope Separation in Electrochemical Lithium Deposition

Naturally occurring Li consists of two stable isotopes, 6 Li with an abundance of about 7.5%, and 7 Li making up the remainder with 92.5%. The development of a 6 Li enrichment technique, in terms of technical reliability and environmental safety to reach 6 Li future requirements, represents a key step in the roadmap for nuclear fusion energy supply worldwide. This paper uses finite element analysis-based models to simulate electrochemical Li isotope separation, which is an attractive method in terms of simplicity, safety, and scalability. In the model, we quantitatively analyze how different electrochemical factors including thermodynamics, charge-transfer kinetics, and diffusivities affect the separation process (separation factor), together with cell parameters, such as cell length and current density. The maximum separation factor of 1.128 could be obtained with the cell under the optimal thermodynamic, kinetic, and diffusive conditions, which is among the highest separation factors ever reported. Furthermore, these results will assist in designing the actual isotope separation setup with large separation factor and appropriate timing for sample collection.

07 ISOTOPE AND RADIATION SOURCES↗

Characterization of Nanoscale Pores in Tight Gas Sandstones Using Complex Techniques: A Case Study of a Linxing Tight Gas Sandstone Reservoir

Pore structures with rich nanopores and permeability in tight gas reservoirs are poorly understood up to date. Advanced techniques are needed to be employed to accurately characterize pore structures, especially tiny pores which include micron and nanopores. In this study, various experimental techniques such as scanning electron microscopy (SEM), nuclear magnetic resonance (NMR) T 2 , nitrogen adsorption method, and NMR cryoporometry (NMRC) are combined to interrogate the complex pore systems of the tight gas reservoir in the Linxing formation, Ordos Basin, China. Results show that tight gas sandstones are primarily comprised of residual interparticle and clay-dominated pores. Clay and quartz are two dominate minerals while pyrite occupies a nontrivial amount as well. The permeability of tight gas sandstones is very low, exhibiting an extremely poor positive correlation with porosity. While pore types and relative pore contents are more influential factors on the permeability, accurate characterization of pore size distribution is critical for the permeability of tight gas sandstones. Therefore, complementary characterization methods are carried out, indicating that neither small pores with radii < 100 nm (around peak 1 in NMR T 2 distribution) nor large pores with radii > 5 μ m (around peak 3 in NMR T 2 distribution) control the permeability by analyzing the connectivity of the pores in various size ranges, but rather pores averaging approximately 350 ± X nm (around peak 2 in NMR T 2 distribution) have sufficient connectivity to host and transmit hydrocarbons. The pore size of tight gas sandstones is dominated by the clay-rich mineral assemblage. The study shows that the NMRC technique can be a very promising method, especially when referred to as a promising “roadmap” on how to interrogate tight formations such as the tight gas sands or even shale especially for the nanopore characterization.

15 GEOTHERMAL ENERGY↗

Maximum Switching Throughput Density Estimator

SAND2024-11125O The Maximum Switching Throughput Density Estimator software performs a simple analysis that estimates the maximum logic switching throughput density that’s achieved in various CMOS technology nodes on the International Roadmap for Devices and Systems. This software utilizes simple device models and optimization techniques, performing a simple sweep over a range of possible logic supply voltages, and analytically calculating the maximum switching frequency for the given logic voltage that meets the power density constraint. It does this by using simple models of power dissipation in conventional and fully adiabatic switching. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Frank, Michael↗

Urban-Scale Processes in High-Spatial-Resolution Earth System Models

Cities and their associated urban areas have a much larger impact on the environment than their spatial footprint on the Earth's surface. This is undoubtedly true at local and regional scales, but also at global scales. At this time, more than half of the world's population lives in urban areas (80% in the United States), and the global proportion is projected to climb to 70% by 2050. Therefore, numerical models to study physics, chemistry, and biology affecting the Earth system at regional and global scales must represent the effects of urban areas on climate and the effects of a changing climate on urban areas. At the same time, it is essential to develop state of the art, simple and accurate urban models to better understand the relevant processes and also to address issues related to urban security against the spectra of chemical, biological and radiological (CBR) hazards. Towards bringing urban scientific communities together, a two-and-a-half-day international workshop was held at the Argonne National Laboratory (ANL) in the Chicago area on May 22-24, 2019. This workshop brought together more than 60 national and international experts to develop a roadmap for a better understanding of the issues associated with urban areas and at enhancing the capabilities of regional and global Earth System models (ESMs) in representing the atmospheric dynamics and chemistry, unique aspects of the biosphere and land use, and human dimensions of the urban environment.

54 ENVIRONMENTAL SCIENCES↗

Advancing Urban Water Resilience: Coproducing Knowledge through Civic–Academic Global Partnerships on Water and Climate

As extreme weather events become more pronounced, the vulnerabilities associated with the urban water supply and wastewater systems in megacities are intensified in multiple interconnected dimensions. These multifaceted water challenges can benefit from enhanced cross-sectoral collaboration and sharing of critical knowledge, which are essential for sustainable and adaptive water governance frameworks. In this context, the Megacity Alliance for Water and Climate (MAWAC)–Europe and North America Region (ENAR) Working Group convened a workshop in March 2023, followed by a subsequent workshop in London, United Kingdom, from 11 to 13 September 2024. These workshops aimed to investigate and devise solutions for the cascading hazards with water systems. The solutions examined various aspects focused on climate adaptation and mitigation, stormwater management, and the governance of water and wastewater systems. Additionally, discussions highlighted the importance of community engagement, economic considerations, equity, and effective communication in addressing these pressing challenges. Over the course of 3 days, experts from academia, government agencies, and industry engaged in meaningful discussions on digital modeling for integrated water management, climate-informed urban planning, and public–private–academic partnerships (Fig. 1). Case studies from cities such as New York, Los Angeles, London, Paris, and Chicago highlighted innovative governance strategies for managing water and wastewater systems, promoting water reuse, planning infrastructure, and fostering stakeholder-driven and stakeholder-informed adaptation. The workshop participants emphasized the need for data-driven decision-making, scalable governance models, and knowledge-sharing networks to enhance urban water governance for sustainability and resilience. This workshop report presents the key takeaways from the 3-day convening, providing a roadmap for integrating scientific research, policy frameworks, and emerging technologies to address water challenges faced by megacities.

Hydrologic models↗

An assessment of thermodynamic merits for current and potential future engine operating strategies

The present work compares the fundamental thermodynamic underpinnings (i.e., working fluid properties and heat release profile) of various combustion strategies with engine measurements. The approach employs a model that separately tracks the impacts on efficiency due to differences in rate of heat addition, volume change, mass addition, and molecular weight change for a given combination of working fluid, heat release profile, and engine geometry. Comparative analysis between measured and modeled efficiencies illustrates fundamental sources of efficiency reductions or opportunities inherent to various combustion regimes. Engine operating regimes chosen for analysis include stoichiometric spark-ignited combustion and lean compression-ignited combustion including HCCI, SA-HCCI, RCCI, GCI, and CDC. Within each combustion regime, effects such as engine load, combustion duration, combustion phasing, combustion chamber geometry, fuel properties, and charge dilution are explored. Model findings illustrate that even in the absence of losses such as heat transfer or incomplete combustion, the maximum possible thermal efficiency inherent to each operating strategy varies to a significant degree. Additionally, the experimentally measured losses are observed to be unique within a given operating strategy. The findings highlight the fact that in order to create a roadmap for future directions in ICE technologies, it is important to not only compare the absolute real-world efficiency of a given combustion strategy, but to also examine the measured efficiency in context of what is thermodynamically possible with the working fluid and boundary conditions prescribed by a strategy.

33 ADVANCED PROPULSION SYSTEMS↗

Amorphous boron nitride: synthesis, properties and device application

Amorphous boron nitride (a-BN) exhibits remarkable electrical, optical, and chemical properties, alongside robust mechanical stability, making it a compelling material for advanced applications in nanoelectronics and photonics. This review comprehensively examines the unique characteristics of a-BN, emphasizing its electrical and optical attributes, state-of-the-art synthesis techniques, and device applications. Key advancements in low-temperature growth methods for a-BN are highlighted, offering insights into their potential for integration into scalable, CMOS-compatible platforms. Additionally, the review discusses the emerging role of a-BN as a dielectric material in electronic and photonic devices, serving as substrates, encapsulation layers, and gate insulators. Finally, perspectives on future challenges, including defect control, interface engineering, and scalability, are presented, providing a roadmap for realizing the full potential of a-BN in next-generation device technologies.

36 MATERIALS SCIENCE↗