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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Measuring Electronic Structure of Multiply Charged Anions to Understand their Chemistry: A Case Study on Gaseous Polyhedral closo-Borate Dianions

Research on multiply charged anions (MCAs) in the gas phase has been intensively performed during the last decades, mainly to understand fundamental molecular physics phenomena, e.g., intramolecular Coulomb repulsion and existence of the repulsive Coulomb barrier. However, the relevance of these investigations with respect to understanding MCAs’ chemistry appears often vague. Here, we discuss how insights on the electronic structure obtained from negative ion photoelectron spectroscopy (NIPES) combined with theoretical calculations and collision induced dissociation can provide fundamental understanding on the intrinsic chemical reactivity of MCAs and their fragments. This is exemplified on our studies on polyhedral closo-borate dianions [BnXn]2- (n = 6, 10, 11, 12; X = H, F-I, CN) and their fragment ions. For example, the rational design of closo-borate dianions with specific electronic properties is described, which leads to generating highly reactive fragments. Depending on the dianionic precursor, these fragments are either tuned to bind noble gases effectively or to activate small molecules like CO and N2. The intrinsic electronic properties of closo-borate dianions are further compared to their electrochemistry in solutions, revealing solvent effects on the redox potentials. Neutral host molecules such as cyclodextrins are found to bind strongly to [BnXn]2-, and gas phase NIPES provides insights on the intrinsic host-guest interactions. Finally, outlooks including the direct NIPES of molecular fragment ions which cannot be generated in the condensed phase and their utilization in preparative mass spectrometry are discussed. J.W is grateful to the Volkswagen foundation for a Freigeist Fellowship. X. B. W acknowledges support from the U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, the Division of Chemical Sciences, Geosciences and Biosciences. We are grateful to our colleagues who support our work on gas phase ion chemistry for many years. In particular we acknowledge the members of our groups, the Asmis group (Leipzig), Laskin Group (West Lafayette), the Jenne group (Wuppertal), the Finze group (Würzburg), the Grabowsky group (Bern), and the Sun group (Shanghai). We are grateful to Edoardo Apra for the many theoretical investigations on closo-borate anions. JW acknowledges support of Harald Knorke and Markus Rohdenburg with the preparation of graphical material, and XBW thanks Qinqin Yuan for the help in organizing references.

Warneke, Jonas↗
DOE OSTI2022

Understanding Lithium Local Environments in LiMn 0.5 Ni 0.5 O 2 Cathodes: A DFT-Supported 6 Li Solid-State NMR Study

LiMn 0.5 Ni 0.5 O 2 has been plagued by the structural failure driven by the irreversible phase change upon subsequent cycling and the structural degradation caused by the seemingly unavoidable Li/Ni exchange. This begs for a better understanding of the correlation between lithium local structures, synthesis conditions, and overall electrochemical properties of materials. In this study, we use density functional theory (DFT) to assist experimental 6 Li solid-state magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectroscopy to understand the nature and change in lithium local structures with extended annealing times (168 vs 15 h) synthesized at 900 °C. To correlate the NMR peak changes after different synthesis conditions, we calculated the NMR spectra of representative low-energy model configurations of LiMn 0.5 Ni 0.5 O 2 composition–zigzag, row, and flower structures–as well as the influence of Ni/Mn ordering and Li/Ni exchange on each spectrum using a supercell that is large enough to allow us to consider the effect of different relative configurations of adjacent transition metal (TM) layers. The analysis based on a combination of the calculated NMR and the experimental spectra suggests that most configurations contributing to the experimental spectra are in fact composed of a blend of configurations higher in energy than the classical well-ordered ground-state structures. Further, the extended annealing of LiMn 0.5 Ni 0.5 O 2 slightly enhances Ni/Mn and Li/Mn orderings while reducing the Li/Ni mixing ratio. This study shows how DFT calculations are crucial in providing a better understanding of the experimental characterization data and therefore local environments and domain structures in oxide materials, such as Li-ion battery cathodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Understanding Film-To-Stripe Transition of Conjugated Polymers Driven by Meniscus Instability

Meniscus instability during meniscus-guided solution coating and printing of conjugated polymers has a significant impact on the deposit morphology and the charge-transport characteristics. The lack of quantitative investigation on meniscus-instability–induced morphology transition for conjugated polymers hindered the ability to precisely control conjugated polymer deposition for desired applications. In this paper, we report a film-to-stripe morphology transition caused by stick-and-slip meniscus instability during solution coating seen in multiple donor–acceptor polymer systems. We observe the coexistence of film and stripe morphologies at the critical coating speed. Surprisingly, higher charge-carrier mobility is measured in transistors fabricated from stripes despite their same deposition condition as the films at the critical speed. To understand the origin of the morphology transition, we further construct a generalizable surface free energy model to validate the hypothesis that the morphology transition occurs to minimize the system surface free energy. As the system surface free energy varies during a stick-and-slip cycle, we focus on evaluating the maximum surface free energy at a given condition, which corresponds to the sticking state right before slipping. Indeed, we observe the increase of the maximum system surface free energy with the increase in coating speed prior to film-to-stripe morphology transition and an abrupt drop in the maximum system surface free energy post-transition when the coating speed is further increased, which is associated with the reduced meniscus length during stripe deposition. Such an energetic change originates from the competition between pinning and depinning forces on a partial wetting substrate which underpins the film-to-stripe transition. This work establishes a quantitative approach for understanding meniscus-instability–induced morphology transition during solution coating. The mechanistic understanding may further facilitate the use of meniscus instability for lithography-free patterning or to suppress instability for highly homogeneous thin film deposition.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Non‐Linear Dimensionality Reduction With a Variational Encoder Decoder to Understand Convective Processes in Climate Models

Abstract Deep learning can accurately represent sub‐grid‐scale convective processes in climate models, learning from high resolution simulations. However, deep learning methods usually lack interpretability due to large internal dimensionality, resulting in reduced trustworthiness in these methods. Here, we use Variational Encoder Decoder structures (VED), a non‐linear dimensionality reduction technique, to learn and understand convective processes in an aquaplanet superparameterized climate model simulation, where deep convective processes are simulated explicitly. We show that similar to previous deep learning studies based on feed‐forward neural nets, the VED is capable of learning and accurately reproducing convective processes. In contrast to past work, we show this can be achieved by compressing the original information into only five latent nodes. As a result, the VED can be used to understand convective processes and delineate modes of convection through the exploration of its latent dimensions. A close investigation of the latent space enables the identification of different convective regimes: (a) stable conditions are clearly distinguished from deep convection with low outgoing longwave radiation and strong precipitation; (b) high optically thin cirrus‐like clouds are separated from low optically thick cumulus clouds; and (c) shallow convective processes are associated with large‐scale moisture content and surface diabatic heating. Our results demonstrate that VEDs can accurately represent convective processes in climate models, while enabling interpretability and better understanding of sub‐grid‐scale physical processes, paving the way to increasingly interpretable machine learning parameterizations with promising generative properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Vapor kinetic energy for the detection and understanding of atmospheric rivers

Poleward water vapor transport in the midlatitudes mainly occurs in meandering filaments of intense water vapor transport, spanning thousands of kilometers long and hundreds of kilometers wide and moving eastward. The water vapor filaments are known as atmospheric rivers (ARs). They can cause extreme wind gusts, intense precipitation, and flooding along densely populated coastal regions. Many recent studies about ARs focused on the statistical analyses of ARs, but a process-level understanding of ARs remains elusive. Here we show that ARs are streams of air with enhanced vapor kinetic energy (VKE) and derive a governing equation for Integrated VKE to understand what contributes to the evolution of ARs. We find that ARs grow mainly because of potential energy conversion to kinetic energy, decay largely owing to condensation and turbulence, and the eastward movement is primarily due to horizontal advection of VKE. Our VKE framework complements the integrated vapor transport framework, which is popular for identifying ARs but lacks a prognostic equation for understanding the physical processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Molecular understanding of heteronuclear active sites in heme–copper oxidases, nitric oxide reductases, and sulfite reductases through biomimetic modelling

Heme-copper oxidases (HCO), nitric oxide reductases (NOR), and sulfite reductases (SiR) catalyze the multi-electron and multi-proton reductions of O 2 , NO, and SO 3 2- , respectively. Each of these reactions is important to drive cellular energy production through respiratory metabolism and HCO, NOR, and SiR evolved to contain heteronuclear active sites containing heme/copper, heme/nonheme iron, and heme-[4Fe-4S] centers, respectively. The complexity of the structures and reactions of these native enzymes, along with their large sizes and/or membrane associations, make it challenging to fully understand the crucial structural features responsible for the catalytic properties of these active sites. Here, we summarize progress that has been made to better understand these heteronuclear metalloenzymes at the molecular level though study of the native enzymes along with insights gained from biomimetic models comprising either small molecules or proteins. Further understanding the reaction selectivity of these enzymes is discussed through comparisons of their similar heteronuclear active sites, and we offer outlook for further investigations and areas of ongoing study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Applying neutron transmission physics and 3D statistical full-field model to understand 2D Bragg-edge imaging

Bragg-edge imaging, which is also known as neutron radiography, has recently emerged as a novel crystalline characterization technique. Modelling of this novel technique by incorporating various features of the underlying microstructure (including the crystallographic texture, the morphological texture, and the grain size) of the material remains a subject of considerable research and development. In this paper, Inconel 718 samples made by additive manufacturing were investigated by neutron diffraction and neutron radiography techniques. The specimen features strong morphological and crystallographic textures and a highly heterogeneous microstructure. A 3D statistical full-field model is introduced by taking details of the microstructure into account to understand the experimental neutron radiography results. The Bragg-edge imaging and the total cross section were calculated based on the neutron transmission physics. A good match was obtained between the model predictions and experimental results at different incident beam angles with respect to the sample build direction. The current theoretical approach has the ability to incorporate 3D spatially resolved microstructural heterogeneity information and shows promise in understanding the 2D neutron radiography of bulk samples. With further development to incorporate the heterogeneity in lattice strain in the model, it can be used as a powerful tool in the future to better understand the neutron radiography data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Understanding and predicting damage and failure at grain boundaries in BCC Ta

Understanding the effect of grain boundaries (GBs) on the deformation and spall behavior is critical to designing materials with tailored failure responses under dynamic loading. This understanding is hampered by the lack of in situ imaging capability with the optimum spatial and temporal resolution during dynamic experiments, as well as by the scarcity of a systematic data set that correlates boundary structure to failure, especially in BCC metals. To fill in this gap in the current understanding, molecular dynamics simulations are performed on a set of 74 bi-crystals in Ta with a [110] symmetric tilt axis. Our results show a correlation between GB misorientation angle and spall strength and also highlight the importance of GB structure itself in determining the spall strength. Specifically, we find a direct correlation between the ability of the GB to plasticity deform through slip/twinning and its spall strength. Additionally, a change in the deformation mechanism from dislocation-meditated to twinning-dominated plasticity is observed as a function of misorientation angles, which results in lowered spall strengths for high-angle GBs.

Chen, J. (ORCID:000000018633229X)↗
DOE OSTI2018

Many-body perturbation theory for understanding optical excitations in organic molecules and solids

Semiconductors composed of organic molecules are promising as components for flexible and inexpensive optoelectronic devices, with many recent studies aimed at understanding their electronic and optical properties. In particular, computational modeling of these complex materials has provided new understanding of the underlying properties which give rise to their excited-state phenomena. Here, this article provides an overview of recent many-body perturbation theory (MBPT) studies of optical excitations within organic molecules and solids. We discuss the accuracy of MBPT within the GW/BSE approach in predicting excitation energies and absorption spectra, and assess the impact of two commonly used approximations, the DFT starting point and the Tamm–Dancoff approximation. Moreover, we summarize studies that elucidate the role of solid-state structure on the nature of excitons in organic crystals. These studies show that a rich physical understanding of organic materials can be obtained from GW/BSE.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Understanding effects of printhead geometry in aerosol jet printing

Aerosol jet printing offers a versatile, high-resolution digital patterning capability broadly relevant to flexible and printed electronic systems. Despite its promise and numerous demonstrations, the theoretical principles driving process outputs have not been thoroughly explored. In this study, a custom-built, modular printing system is developed to provide a head-to-head comparison of two print nozzle geometries to better understand the technology. Print resolution data from a range of process parameters are analyzed using a support vector machine framework. The linear deposition rate is identified as a key variable, which can confound careful studies of printing performance. Taking this into account, a clear difference is observed between the printheads, corresponding to a difference in resolution of 57% ± 11% under typical conditions. Models to understand differences in aerodynamic and mass transport effects identify enhanced drying within the NanoJet printhead as a likely cause of this difference. Overall, this study provides improved understanding of the aerosol jet printing process, including valuable insight to inform process optimization, robust data analysis, ink formulation, and printer geometric design.

42 ENGINEERING↗
DOE OSTI2023

Advances in understanding the changes of tropical rainfall annual cycle: a review

Abstract Aided by progress in the theoretical understanding, new knowledge on tropical rainfall annual cycle changes under a global warming background has been advanced in the past decade. In this review, we focus on recent advances in understanding the changes of tropical rainfall annual cycle, including its four distinct features: amplitude, spatial pattern shift, phase and wet/dry season length changes. Here, amplitude refers to the local summer-winter rainfall contrast and phase refers to the timing of rainfall annual cycle. In a warming climate, the amplitude is enhanced, more evidently over ocean, while the phase is delayed, mainly over land. The former is explained by the wet-get-wetter mechanism and the latter is explained by the enhanced effective atmospheric heat capacity and increased convective barrier. The phase delay over land has already emerged in the past four decades. The spatial pattern shift under warming is marked by two features: equatorward shift of the ITCZ throughout the year and the land-to-ocean precipitation shift in the rainy season. The former is explained by the upped-ante mechanism and/or related to the enhanced equatorial warming in a warmer world. The latter may be caused by the opposite land and ocean surface temperature annual cycle changes in the tropics. Over tropical rainforest regions such as Amazon and Congo Basin, the dry season has lengthened in the recent decades, but the fundamental reason is still unclear. Despite the notable progress in the research of tropical rainfall annual cycle change, many gaps remain in understanding its mechanisms, quantifying and attributing its historical emergence, narrowing the inter-model uncertainty of its future projections, and evaluating its global impact, motivating future work guided by some directions proposed in this review.

Song, Fengfei (ORCID:0000000230041749)↗
DOE OSTI2023

Understanding Interfacial Electrochemical Reactions through in situ ec-STEM and IL-Cryo-STEM

A major criterion in the design of next generation materials for electrical energy storage applications is a comprehensive understanding of interfacial electrochemical reactions as well as correlating the structure and chemistry across site-specific electrode/electrolyte interfaces with electron, charge, and mass transport processes as they govern performance characteristics. Scanning transmission electron microscopy (STEM) based techniques have emerged as an indispensable materials characterization tool that provides high spatial resolution imaging and chemical analysis and has been effectively utilized to obtain an atomic to nanoscale view of the interfacial structure before and after electrochemical cycling. More recently, there have been several advances that now allows us to obtain more detailed mechanistic insight into evolving reactions through in situ ec-STEM and electrical biasing platforms such as in the understanding of the mechanisms of solid electrolyte interphase formation, lithium dendrite nucleation and growth mechanisms and ionic transport mechanisms within intercalation, conversion, and alloying electrode materials. Several major advantages of the in situ ec-STEM approach is the quantitative electrochemical measurement of charge passed during cycling with simultaneous analysis of the electrochemical processes with STEM imaging and diffraction. Here, while spectroscopic analysis of the electrochemical reactions products has been performed, there is the issue of beam sensitivity and therefore, Cryo-STEM imaging combined with electron energy loss spectroscopy (EELS) techniques have been employed to analyze the chemistry of the SEI and Li dendrites. In this talk, we discuss the potential for combining identical location (IL) STEM techniques with Cryo-EM. The advantage of using this approach is that the sample is placed on a conventional TEM grid and the exact same location of the specimen can be analyzed before and after quantitative electrochemical measurements. Moreover, since the sample is on the TEM grid, the grid itself can be prepared for further Cryo-TEM experiments by plunge freezing in liquid nitrogen then transferred to the Cryo-TEM under liquid nitrogen. Results obtain from these experiments can be used to enhance our scientific understanding of interfacial chemistry at electrode/electrolyte interfaces and may be useful in the design of new materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Understanding Complex Magnetic Spin Textures with Simulation-Assisted Lorentz Transmission Electron Microscopy

There is an increased interest in topologically nontrivial magnetic spin textures such as skyrmions and chiral domain-wall solitons, both from a point of fundamental physics understanding as well as potential technological interest in low-power memory applications. In order to control their behavior, it is necessary to understand their complex spin texture at the nanoscale. Lorentz transmission electron microscopy (LTEM) is a suitable technique for studying these systems due to its high spatial resolution and capability to simultaneously characterize magnetic texture and microstructure. In this work, we present the application of PyLorentz, an open-source software suite that we have developed, for quantitative image analysis of Neel-type skyrmions in thin-film heterostructures. PyLorentz enhances LTEM capabilities by enabling reconstruction of magnetic induction maps from experimental images, as well as simulating LTEM images using micromagnetic simulation data. We demonstrate this for simulated Neel skyrmions as well as experimental data from [Pt/Co/W] multilayer heterostructures. Finally, we also show how simulation-assisted LTEM analysis is crucial for understanding these complex magnetic spin textures, in which the reconstructed magnetic induction map (seen in the LTEM images) differs significantly from the magnetization configuration.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Filling gaps in our understanding of belowground plant traits across the world: an introduction to a Virtual Issue

The belowground world is one of the final frontiers in terrestrial ecology. The tangling of plant roots with the surrounding soil below is a lifeline for the humble forbs and towering trees above, and roots play a key role in shaping ecosystem carbon, water and nutrient cycling (Bardgett et al., 2014). Ecologists have long sought to better understand the ecosystem-scale consequences of differing plant strategies, above- and belowground, by relating plant characteristics, or traits, to plant function (Grime, 1977; Pregitzer, 2002). While developing trait–function linkages is arguably more difficult for plant traits that are hidden belowground, root and rhizosphere ecologists continue to fan out across grasslands and forests with their shovels, isotopes, and specialized cameras, seeking a better understanding of the secret lives of roots. Over the years, New Phytologist has served as a virtual town square for scientists to discuss their hard-won observations on the interplay among belowground plant traits, microbial activity, and edaphic and environmental conditions from biomes around the world (Norby & Jackson, 2000; Pregitzer, 2002; Matamala & Stover, 2013; Norby & Iversen, 2017). In this Editorial we highlight the newest papers that update and add to our understanding of the role of root and rhizosphere traits in broader ecosystem processes. We focused on papers published in New Phytologist between 1 January 2019 and 31 December 2020 and extended this window to papers still in ‘early view’ up to the time of writing. Because of the overwhelming number of papers, we did not include those with a decidedly genomic focus or that served primarily as data syntheses, reviews, insights or commentaries.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Understanding local plant extinctions before it is too late: bridging evolutionary genomics with global ecology

Understanding evolutionary genomic and population processes within a species range is key to anticipating the extinction of plant species before it is too late. However, most models of biodiversity risk under global change do not account for the genetic variation and local adaptation of different populations. Population diversity is critical to understanding extinction because different populations may be more or less susceptible to global change and, if lost, would reduce the total diversity within a species. Here, two new modeling frameworks advance our understanding of extinction from a population and evolutionary angle: Rapid climate change-driven disruptions in population adaptation are predicted from associations between genomes and local climates. Furthermore, losses of population diversity from global land-use transformations are estimated by scaling relationships of species' genomic diversity with habitat area. Overall, these global eco-evolutionary methods advance the predictability – and possibly the preventability – of the ongoing extinction of plant species.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Toward a coordinated understanding of hydro‐biogeochemical root functions in tropical forests for application in vegetation models

Summary Tropical forest root characteristics and resource acquisition strategies are underrepresented in vegetation and global models, hampering the prediction of forest–climate feedbacks for these carbon‐rich ecosystems. Lowland tropical forests often have globally unique combinations of high taxonomic and functional biodiversity, rainfall seasonality, and strongly weathered infertile soils, giving rise to distinct patterns in root traits and functions compared with higher latitude ecosystems. We provide a roadmap for integrating recent advances in our understanding of tropical forest belowground function into vegetation models, focusing on water and nutrient acquisition. We offer comparisons of recent advances in empirical and model understanding of root characteristics that represent important functional processes in tropical forests. We focus on: (1) fine‐root strategies for soil resource exploration, (2) coupling and trade‐offs in fine‐root water vs nutrient acquisition, and (3) aboveground–belowground linkages in plant resource acquisition and use. We suggest avenues for representing these extremely diverse plant communities in computationally manageable and ecologically meaningful groups in models for linked aboveground–belowground hydro‐nutrient functions. Tropical forests are undergoing warming, shifting rainfall regimes, and exacerbation of soil nutrient scarcity caused by elevated atmospheric CO 2 . The accurate model representation of tropical forest functions is crucial for understanding the interactions of this biome with the climate.

Plant Sciences↗
DOE OSTI2021

(Invited) Understanding Multi-Component Transport and Reaction Phenomena in Bipolar Membranes Used for Electrosynthesis

Bipolar membranes (BPMs), which have long seen usage in electrodialysis reactors for the generation of acid and base, have recently demonstrated potential to become critical components in electrochemical synthesis devices. Because they can operate under large pH gradients, BPMs enable favorable environments for electrocatalysis at the individual electrodes. Critical to the implementation of BPMs in these devices is understanding the kinetics of water dissociation that occurs within the BPM junction as well as the co- and counter-ion crossover through the BPM, which both present significant obstacles to developing efficient and stable BPM-devices for electrosynthesis applications. Prior work has modeled ion transport in bipolar membranes in neutral salt solutions for electrodialysis. However, no model exists for the BPM under the harsh applied pH gradients that would be present in electrosynthesis, and there is significant need to explore the effects of the internal hydration on the lifetime and performance of BPMs in such environments. Additionally, a mechanistic understanding of water dissociation catalysis will be required to develop interfacial catalysts that enable the high current density operation required for scalable electrosynthesis of fuels. In this talk, we discuss modeling methodologies and physics inherent in BPMs and present our recent model of ion transport and water dissociation catalysis in BPMs across the pH scale. Specifically, we simulate multi-ion transport for a BPM with various electrolyte combinations on each side of the membrane, demonstrating the significance of co- and counter-ion crossover in BPMs operating under harsh pH gradients. We then investigate effects caused by hydration gradients that occur due to internal ion-exchange and examine potential methods for improving performance and mitigating crossover. Finally, we examine the impact of the interfacial water dissociation catalyst and perform sensitivity analysis on the key properties (catalyst point of zero charge and pKa) that dictate catalyst performance. These results provide information that is critical to developing a comprehensive understanding of multi-component phenomena in BPMs and to informing the design and implementation of BPMs in next-generation devices for the numerous electrosynthesis chemistries that benefit from operation under an applied pH gradient.

Bui, Justin C↗
DOE OSTI2022

Progress Toward a Multiomic Understanding of Traumatic Brain Injury: A Review

Traumatic brain injury (TBI) is not a single disease state but describes an array of conditions associated with insult or injury to the brain. While some individuals with TBI recover within a few days or months, others present with persistent symptoms that can cause disability, neuropsychological trauma, and even death. Understanding, diagnosing, and treating TBI is extremely complex for many reasons, including the variable biomechanics of head impact, differences in severity and location of injury, and individual patient characteristics. Because of these confounding factors, the development of reliable diagnostics and targeted treatments for brain injury remains elusive. We argue that the development of effective diagnostic and therapeutic strategies for TBI requires a deep understanding of human neurophysiology at the molecular level and that the framework of multiomics may provide some effective solutions for the diagnosis and treatment of this challenging condition. To this end, we present here a comprehensive review of TBI biomarker candidates from across the multiomic disciplines and compare them with known signatures associated with other neuropsychological conditions, including Alzheimer’s disease and Parkinson’s disease. We believe that this integrated view will facilitate a deeper understanding of the pathophysiology of TBI and its potential links to other neurological diseases.

60 APPLIED LIFE SCIENCES↗