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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Amantadine interactions with phase separated lipid membranes

Amantadine, a small amphilphic organic compound that consists of an adamantane backbone and an amino group, was first recognized as an antiviral in 1963 and received approval for prophylaxis against the type A influenza virus in 1976. Since then, it has also been used to treat Parkinson’s disease-related dyskinesia and is being considered as a treatment for corona viruses. Since amantadine usually targets membrane-bound proteins, its interactions with the membrane are also thought to be important. Biological membranes are now widely understood to be laterally heterogeneous and certain proteins are known to preferentially co-localize within specific lipid domains. Does amantadine, therefore, preferentially localize in certain lipid composition domains? To address this question, here, we studied amantadine’s interactions with phase separating membranes composed of cholesterol, DSPC (1,2-distearoyl-sn-glycero-3-phosphocholine), POPC (1-palmitoyl-2-oleoyl-glycero-3-phosphocholine), and DOPC (1,2-dioleoyl-sn-glycero-3-phosphocholine), as well as single-phase DPhPC (1,2-diphytanoyl-sn-glycero-3-phos-phocholine) membranes. From Langmuir trough and differential scanning calorimetry (DSC) measurements, we determined, respectively, that amantadine preferentially binds to disordered lipids, such as POPC, and lowers the phase transition temperature of POPC/DSPC/cholesterol mixtures, implying that amantadine increases membrane disorder. Further, using droplet interface bilayers (DIBs), we observed that amantadine disrupts DPhPC membranes, consistent with its disordering properties. Finally, we carried out molecular dynamics (MD) simulations on POPC/DSPC/cholesterol membranes with varying amounts of amantadine. Consistent with experiment, MD simulations showed that amantadine prefers to associate with disordered POPC-rich domains, domain boundaries, and lipid glycerol backbones. Since different proteins co-localize with different lipid domains, our results have possible implications as to which classes of proteins may be better targets for amantadine.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1999

Nanomechanics of Carbon and CxByNz Nanotubes: Via a Quantum Molecular Dynamics Method

Nanomechanics of single-wall C, BN and BC$_3$ and B doped C nanotubes under axial compression and tension are investigated through a generalized tight-binding molecular dynamics (GTBMD) and {\it ab-initio} electronic structure methods. The dynamic strength of BN, BC$_3$ and B doped C nanotubes for small axial strain are comparable to each other. The main difference is in the critical strain at which structural collapse occurs. For example, even a shallow doping with B lowers the value of critical strain for C nanotubes. The critical strain for BN nanotube is found to be more than that for the similar C nanotube. Once the structural collapse starts to occur we find that carbon nanotubes irreversibly go into plastic deformation regime via the formation of tetrahedral (four-fold coordinated) bonds at the location of sharp pinches or kinks. This finding is considerably different from the classical MD (molecular dynamics) simulation results known so far. The energetics and electronic densities of states of the collapsed structures, investigated with {\it ab-initio) methods, will also be discussed.

Srivastava, Deepak↗
DOE OSTI2024

A transient site balance model for atomic layer etching

We present a transient site balance model of plasma-assisted atomic layer etching of silicon (Si) with alternating exposure to chlorine gas (Cl 2 ) and argon ions (Ar + ). Molecular dynamics (MD) simulation results are used to provide parameters for the model. The model couples the dynamics of a top monolayer surface region ('top layer') and a perfectly mixed subsurface region ('mixed layer'). The differential equations describing the rates of change of the Cl coverage in the two layers are transient mass balances. Model predictions include Cl coverages and rates of etching of various species from the surface as a function of Cl 2 or Ar + fluence. The simplified phenomenological model reproduces the MD simulation results well over a range of conditions. Comparing model predictions directly to experimental optical emission spectroscopy data, as reported in a previous paper, provides further evidence of the accuracy of the model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Exceptionally high spallation strength for a high-entropy alloy demonstrated by experiments and simulations

High-entropy alloys are materials with an increasing number of technological applications. Amongst them, the Cantor alloy, FeMnCoCrNi, shows desirable mechanical properties at normal loading conditions. In this study we focus on the performance of the Cantor alloy at the ultra-high deformation rates of shock waves. We study shock-induced spallation using both experiments and atomistic simulations. Experimental loading is achieved using high power laser, with VISAR to obtain velocity profiles and spall strength, followed by transmission electron microscopy of the recovered samples. Molecular Dynamics (MD) simulations of shock-induced spallation are compared with experiments. Both experiments and simulations show a high spall strength which would be beneficial for certain applications, with experiments giving ~8 GPa at ~10 7 s -1 and MD giving almost ~30 GPa at ~10 9 s -1 . The difference between experiments and simulations can be explained by the difference in strain rate. Post-mortem analysis of the experimental samples shows nanotwins near the spall plane, while MD simulations show a highly disordered region giving rise to void nucleation and spall during loading.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Molecular Picture of the Transient Nature of Lipid Rafts

In biological membranes, lipid rafts are now thought to be transient and nanoscopic. However, the mechanism responsible for these nanoscopic assemblies remains poorly understood, even in the case of model membranes. Therefore, it has proven extremely challenging to probe the physicochemical properties of lipid rafts at the molecular level. Here, we use all-atom molecular dynamics (MD) simulations and inelastic X-ray scattering (IXS), an intrinsically nanoscale technique, to directly probe the energy transfer and collective short-wavelength dynamics (phonons) of biologically relevant model membranes. We show that the nanoscale propagation of stress in lipid rafts takes place in the form of collective motions made up of longitudinal (compression waves) and transverse (shear waves) molecular vibrations. Importantly, we provide a molecular picture for the so-called van der Waals mediated "force from lipid" [Anishkin, A. et al. Proc. Natl. Acad. Sci. U.S.A. 2014, 111, 7898], a key parameter for the ionic channel mechano-transduction and the mechanism for the lipid transfer of molecular level stress [Aponte-Santamaría, C. et al. J. Am. Chem. Soc. 2017, 139, 13588]. Specifically, we describe how lipid rafts are formed and maintained through the propagation of molecular stress, lipid raft rattling dynamics, and a relaxation process. Eventually, the rafts dissipate through the self-diffusion of lipids making up the rafts. We also show that the molecular stress and viscoelastic properties of transient lipid rafts can be modulated through the use of hydrophobic biomolecules such as melatonin and tryptophan. Overall, the herein proposed mechanism describing the molecular interactions for the formation and dissolution of lipid rafts may offer insights as to how lipid rafts enable biological function.

36 MATERIALS SCIENCE↗
NASA NTRS1991

Macromolecular recognition: Structural aspects of the origin of the genetic system

Theoretical simulation of prebiotic chemical processes is an invaluable tool for probing the phenomenon of evolution of life. Using computational and modeling techniques and guided by analogies from present day systems we, seek to understand the emergence of genetic apparatus, enzymatic catalysis and protein synthesis under prebiotic conditions. In one possible scenario, the RNA enzymatic reaction plays a key role in the emergence of the self-replicating and offers a clue to the onset of enzymatic catalysis prior to the existence of the protein biosynthetic machinery. Our ultimate goal is to propose a simple RNA segment which contains the specificity and catalytic activity of the contemporary RNA enzyme and which could emerge in a primordial chemical environment. To understand the mechanism of ribozyme catalyzed reactions, ab initio and semi-empirical (ZINDO) programs were used to investigate the reaction path of transphosphorylation. A special emphasis was placed on the possible catalytic and structural roles played by the coordinated magnesium cation. Both the inline and adjacent mechanisms of transphosphorylation have been studied. Another important aspect of this reaction is the identity of the functional groups which are essential for the acid base catalysis. The structural characteristics of the target helices, particularly a possible role of G center dot T pair, is under examination by molecular dynamics (MD) simulation technique. Modeling of the ancestral aminoacyl-tRNA synthetases (aRS) may provide important clues to the emergence of the genetic code and the protein synthetic machinery. Assuming that the catalytic function evolved before the elements of specific recognition of a particular amino acid, we are exploring the minimal structural requirements for the catalysis of tRNA aminoacylation. The molecular modeling system SYBYL was used for this study based on the high resolution crystallographic structures of the present day tyrosyl-adenylate:tyrRS and tRNA(Gln): ATP:glnRS complexes. The trinucleotide CCA of the 3'-end tRNA is placed into the active site pocket of tyrRS, based on the scheme of interaction between tRNA(Gln) and glnRS, and upon the stereochemistry of the tyrRS:tRNA:Tyr-AMP transition state. This provides a model of the non-specific recognition of a tRNA's 3'-end by an aRS, which might be similar to that of the ancestral aRS's. In the next step, modeling of the rest of the acceptor stem of tRNA (Tyr) with tyrRS is carried out.

Rein, Robert↗
DOE OSTI2020

The Role of Dimer Formation in the Nucleation of Superlattice Transformations and Its Impact on Disorder

The formation of defect-free two-dimensional nanocrystal (NC) superstructures remains a challenge as persistent defects hinder charge delocalization and related device performance. Understanding defect formation is an important step toward developing strategies to mitigate their formation. However, specific mechanisms of defect formation are difficult to determine, as superlattice phase transformations that occur during fabrication are quite complex and there are a variety of factors influencing the disorder in the final structure. Here, we use Molecular Dynamics (MD) and electron microscopy in concert to investigate the nucleation of the epitaxial attachment of lead chalcogenide (PbX, where X = S, Se) NC assemblies. We use an updated implementation of an existing reactive force field in an MD framework to investigate how initial orientational (mis)alignment of the constituent building blocks impacts the final structure of the epitaxially connected superlattice. This Simple Molecular Reactive Force Field (SMRFF) captures both short-range covalent forces and long-range electrostatic forces and allows us to follow orientational and translational changes of NCs during superlattice transformation. Our simulations reveal how robust the oriented attachment is with regard to the initial configuration of the NCs, measuring its sensitivity to both in-plane and out-of-plane misorientation. We show that oriented attachment nucleates through the initial formation of dimers, which corroborate experimentally observed structures. We present high-resolution structural analysis of dimers at early stages of the superlattice transformation and rationalize their contribution to the formation of defects in the final superlattice. Collectively, the simulations and experiments presented in this paper provide insights into the nucleation of NC oriented attachment, the impact of the initial configuration of NCs on the structural fidelity of the final epitaxially connected superlattice, and the propensity to form commonly observed defects, such as missing bridges and atomic misalignment in the superlattice due to the formation of dimers. Here, we present potential strategies to mitigate the formation of superlattice defects.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Properties of carbon up to 10 million kelvin from Kohn-Sham density functional theory molecular dynamics

Accurately modeling dense plasmas over wide-ranging conditions of pressure and temperature is a grand challenge critically important to our understanding of stellar and planetary physics as well as inertial confinement fusion. In this work, we employ Kohn-Sham density functional theory (DFT) molecular dynamics (MD) to compute the properties of carbon at warm and hot dense matter conditions in the vicinity of the principal Hugoniot. In particular, we calculate the equation of state (EOS), Hugoniot, pair distribution functions, and diffusion coefficients for carbon at densities spanning 8 g/$\mathrm{cm^3}$ to 16 g/$\mathrm{cm^3}$ and temperatures ranging from 100 kK to 10 MK using the Spectral Quadrature method. Here, we find that the computed EOS and Hugoniot are in good agreement with path integral Monte Carlo results and the sesame database. Additionally, we calculate the ion-ion structure factor and viscosity for selected points. All results presented are at the level of full Kohn-Sham DFT-MD, free of empirical parameters, average-atom, and orbital-free approximations employed previously at such conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Ettringite hysteresis under sorption from molecular simulations

Highlights: • Hybrid Grand Canonical Monte Carlo (GCMC) and Molecular Dynamics (MD) simulations are performed. • Anisotropic large strain coefficient of crystal shrinkage of ettringite is provided. • Entropy increases when ettringite converts into metaettringite. • Sorption-induced stress may lead to columns collapse upon drying. • H-bonds involving OH groups in columns play a role in hysteresis. The response of ettringite under sorption is critical for the utilization of this mineral as an energy storage material and to understand the concrete durability problems associated with ettringite formation. We report molecular simulations directly sampling the osmotic ensemble to understand the sorption processes and structural changes in ettringite-metaettringite transition. Desorption branch and sorption-induced volume changes from simulations agree with the experiments. The structural changes at low relative humidity are analyzed, revealing for the first time details of metaettringite structure. The reversibility under sorption observed experimentally is captured by simulation in the ettringite domain. The reversibility in the conversion of metaettringite into ettringite is not captured by the direct simulations in the osmotic ensemble due to the large volume changes associated with ettringite desorption. Finally, we discuss the role of hydrogen bonds on the hysteresis in ettringite.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Revisited Mechanism of the Graphite-to-Diamond Transition at High Temperature

The graphite-diamond transition, under high-pressure and high-temperature conditions, has been a central subject in physical science. However, its atomistic mechanism remains under debate. Employing large-scale molecular dynamics (MD) simulations, we report a mechanism whereby the diamond nuclei in the graphite matrix propagate in two preferred directions, among which the graphite [120] is about 2.5 times faster than [001]. Consequently, cubic diamond (CD) is the kinetically favorable product, while only a few hexagonal diamonds (HDs) can exist as the twins of CDs. The coherent interface of t-(100)gr//(11-1)cd + [010]gr//[1-10]cd observed in MD simulation was confirmed by our high-resolution transmission electron microscopy experiment. This proposed mechanism not only clarifies the role of HD in graphite-diamond transition but also yields atomistic insight into strengthening synthetic diamond via microstructure engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Accuracy, transferability, and computational efficiency of interatomic potentials for simulations of carbon under extreme conditions

Large-scale atomistic molecular dynamics (MD) simulations provide an exceptional opportunity to advance the fundamental understanding of carbon under extreme conditions of high pressures and temperatures. However, the fidelity of these simulations depends heavily on the accuracy of classical interatomic potentials governing the dynamics of many-atom systems. Here, this study critically assesses several popular empirical potentials for carbon, as well as machine learning interatomic potentials (MLIPs), in their ability to simulate a range of physical properties at high pressures and temperatures, including the diamond equation of state, its melting line, shock Hugoniot, uniaxial compressions, and the structure of liquid carbon. Empirical potentials fail to accurately predict the behavior of carbon under high pressure–temperature conditions. In contrast, MLIPs demonstrate quantum accuracy, with Spectral Neighbor Analysis Potential (SNAP) and atomic cluster expansion (ACE) being the most accurate in reproducing the density functional theory results. ACE displays remarkable transferability despite not being specifically trained for extreme conditions. Furthermore, ACE and SNAP exhibit superior computational performance on graphics processing unit-based systems in billion atom MD simulations, with SNAP emerging as the fastest. In addition to offering practical guidance in selecting an interatomic potential with a fine balance of accuracy, transferability, and computational efficiency, this work also highlights transformative opportunities for groundbreaking scientific discoveries facilitated by quantum-accurate MD simulations with MLIPs on emerging exascale supercomputers.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Local conformations and heterogeneities in structures and dynamics of isotactic polypropylene adsorbed onto carbon fiber

Carbon fiber (CF) reinforced polymers (CFRPs) have experienced widespread use in various industries. One of the most important parameters that controls the macroscopic property of CFRPs is the interface between a polymer matrix and CF. There is growing evidence to suggest the formation of a bound polymer layer (BPL), i.e., polymer chains that physically adsorb on a filler surface. However, this interface is always in contact with the thicker part of a polymer matrix, rendering its understanding a difficult task. Therein, we use CF-reinforced isotactic polypropylene (iPP) as a rational CFRP. To characterize the BPL on the CF surface, we extracted it from the CFRP using solvent-rinsing with p-xylene. The physical and thermal properties of the BPL were characterized by differential scanning calorimetry and thermogravimetric analysis, while its microscopic structures and dynamics were probed by small-angle neutron scattering and quasi-elastic neutron scattering (QENS) techniques. Subsequently, we employed atomistic molecular dynamics (MD) simulations to complement the QENS results above the bulk melting temperature and reveal details that were experimentally inaccessible. In this work, we observed that the degree of crystallinity of the BPL was quite lower than the bulk, while the melting temperature of the BPL remained the same as the bulks. Within the given length and time scales probed by QENS and MD, we also observed that most of the bound chains were mobile, with the formation of a high-density region (less than 1 nm in thickness) near the CF surface. The segmental dynamics of the bound chains probed by both QENS and MD were also much faster than those of the free chains, possibly due to the presence of a free surface region at the topmost surface of the BPL. Furthermore, the MD results demonstrated that the backbone chains and side groups lie nearly flat on the CF surface, which is the driving force for the flattening process of the iPP BPL to overcome the conformational entropy loss in the total free energy.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Stabilized Electrode/Electrolyte Interphase by a Saturated Ionic Liquid Electrolyte for High-Voltage NMC532/Si-Graphite Cells

Nonaqueous electrolyte has become one of the technical barriers in enabling Li-ion battery comprising of a high voltage cathode and high capacity anode. Here, we demonstrate a saturated piperidinum bis(fluorosulfonyl)imide ionic liquid (IL) with a LiFSI salt not only supports the redox reaction on the cathode at high voltages, but also shows exceptional kinetic stability on the lithiated anode as evidenced by its improved cycling performance in a NMC532/Si-graphite full cells cycled between 4.6 and 3.0 V. On the basis of the spectroscopic/microscopic analysis and molecular dynamics (MD) simulations, the superior performance of the cells is attributed to the formation of solid-electrolyte-interphase on both electrode as well as unique solvation structure where a deadlocked coordination network is established at the saturated state, which prevents transition metal dissolution into the electrolyte via a solvation process.

25 ENERGY STORAGE↗
DOE OSTI2020

Parallel algorithms for hyperdynamics and local hyperdynamics

Hyperdynamics (HD) is a method for accelerating the timescale of standard molecular dynamics (MD). It can be used for simulations of systems with an energy potential landscape that is a collection of basins, separated by barriers, where transitions between basins are infrequent. HD enables the system to escape from a basin more quickly while enabling a statistically accurate renormalization of the simulation time, thus effectively boosting the timescale of the simulation. In [Kim, Perez, Voter, J Chem Phys, 139:144110, 2013)1, a local version of HD was formulated, which exploits the intrinsic locality characteristic typical of most systems to mitigate the poor scaling properties of standard HD as the system size is increased. In this paper, we discuss how both HD and local HD can be formulated to run efficiently in parallel. We have implemented these ideas in the LAMMPS MD code, which means HD can be used with any interatomic potential LAMMPS supports. Together, these parallel methods allow simulations of any size to achieve the time acceleration offered by HD (which can be orders of magnitude), at a cost 3-5x that of standard MD. As examples, we performed two simulations of a million-atom system to model the diffusion and clustering of Pt adatoms on a large patch of Pt(100) surface for 80 and 160 μs.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Enhanced detection of volatile organic compounds (VOCs) by caffeine modified carbon nanotube junctions

Detection of vapor phase analytes and gas molecules is primarily essential for numerous applications including medical diagnostic, environmental monitoring, chemical threat detection, food quality control, and chemical warfare agents. Here, we developed Caffeine functionalized carbon nanotubes (CNTs) random network based vapor quantum resistive sensors (vQRSs) for volatile organic compounds (VOCs) detection. The localized transmission electron microscopy (TEM) image and energy dispersive X-ray spectroscopy (EDS) confirm migration of caffeine to CNT–CNT junction (CNTj). We have recorded more than one order of magnitude higher sensitivity and unique selectivity towards selective VOCs (e.g., acetone, toluene, ethanol, methanol, etc.) with short response time (few seconds) for caffeine modified CNT junction (Caf-CNTj) vQRSs. Molecular dynamics (MD) calculations suggest that the sensitivity of the sensor is diffusion limited, with an advective contribution for ethanol. Furthermore, the designed Caf-CNTj sensors can potentially be important candidate to be a part of electronic nose used for various application such as breath analysis and food quality monitoring.

36 MATERIALS SCIENCE↗
DOE OSTI2022

NMR and Theoretical Study of In-Pore Diffusivity of Ionic Liquid–Solvent Mixtures

We report despite having a lower energy density than common batteries, electric double-layer capacitors (EDLCs) offer several advantages for high-power applications, including high power density, quick charge and discharge time, and long cycle life. Room-temperature ionic liquids (RTILs) have been intensely studied as promising electrolytes for applications in ELDCs because of their wide potential window, low volatility, as well as thermal and chemical stability. The main deficiency of neat RTILs in such applications is the sluggish diffusivity, which restricts the EDLCs’ power density. To alleviate the slow diffusivity, RTILs can be used in a mixture with organic solvents. In this study, we applied two-dimensional exchange nuclear magnetic resonance spectroscopy (2D EXSY NMR) and molecular dynamics (MD) simulations to investigate the diffusivity of anions of an RTIL, namely, 1-butyl-3-methyl-imidazolium bis(trifluoromethylsulfonyl)imide (BMIM + –TFSI – ), dissolved in five different organic solvents, in the micropores of activated carbon. We determined that the relative concentrations of ions in solutions in the micropores were higher than those in the bulk solutions and were also solvent-dependent. The ion diffusivities in the pores were found to be almost 2 orders of magnitude slower than in the bulk solutions, with methanol showing the largest relative disparity. These results suggested that the interactions of solvents with the activated carbon are critical not only to the power density of EDLCs but also to the energy density. The comparisons of ion diffusivities between the experiments and the MD simulations suggest the need to consider also the surface functionalities of activated carbon for the simulation of ion diffusion in the micropores of activated carbon.

electric double layer capacitors↗
DOE OSTI2021

Modeling of Peptides with Classical and Novel Machine Learning Force Fields: A Comparison

The replacement of classical force fields (FFs) with novel neural-network-based frameworks is an emergent topic in molecular dynamics (MD) simulations. In contrast to classical FFs, which have proven their capability to provide insights into complex soft matter systems at an atomistic resolution, the machine learning (ML) potentials have yet to demonstrate their applicability for soft materials. However, the underlying philosophy, which is learning the energy of an atom in its surrounding chemical environment, makes this approach a promising tool. In particular for the exploration of novel chemical compounds, which have not been considered in the original parametrization of classical FFs. In this article, we study the performance of the ANI-2x ML model and compare the results with those of two classical FFs, namely, CHARMM27 and the GROMOS96 43a1 FF. We explore the performance of these FFs for bulk water and two model peptides, trialanine and a 9-mer of the α-aminoisobutyric acid, in vacuum and water. The results for water describe a highly ordered water structure, with a structure similar to those using ab initio molecular dynamics simulations. The energy landscape of the peptides described by Ramachandran maps show secondary structure basins similar to those of the classical FFs but differ in the position and relative stability of the basins. Details of the sampled structures show a divergent performance of the different models, which can be related either to the short-ranged nature of the ML potentials or to shortcomings of the underlying data set used for training. These findings highlight the current state of the applicability of ANI-2x ML potential for MD simulations of soft matter systems. Simultaneously, they provide insights for future improvements of current ML potentials.

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

Additive Manufacturing with Cellulose-Based Composites: Materials, Modeling, and Applications

Recent advances in large-scale additive manufacturing (AM) with polymer-based composites have enabled efficient production of high-performance materials. Cellulose nanomaterials (CNMs) have emerged as bio-based feedstocks due to their exceptional strength and sustainability. However, challenges such as hornification and poor dispersion in polymer matrices still limit large-scale CNM–polymer composite manufacturing, requiring novel strategies. Here, this review outlines an approach starting with atomic-level simulations to link molecular composition to key parameters like bulk density, viscosity, and modulus. These simulations provide data for finite element analysis (FEA), which informs large-scale experiments and reduces the need for extensive trials. The strategy explores how atomic interactions impact the morphology, adhesion, and mechanical properties of CNM-based composites in AM processes. The review also discusses current developments in AM, along with predictions of mechanical and thermal properties for structural applications, packaging, flexible electronics, and hydrogel scaffolds. By integrating experimental findings with molecular dynamics (MD) simulations and finite element modeling (FEM), valuable insights for material design, process optimization, and performance enhancement in CNM-based AM are provided to address ongoing challenges.

36 MATERIALS SCIENCE↗