Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “computational molecular design”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 523 records · Page 29

Enabling Open and Interoperable Science: Multi-Omics Data Processing Platform with NASA GeneLab Standardized Bioinformatics Workflows for Space and Earth Research

Multi-omics biological data continues to be generated at an astounding pace. Genomics, transcriptomics, metabolomics, and proteomics, or collectively known as multi-omics data, are used to assess biological functions, and provide invaluable insights into human, animal, plant, and environmental health both on Earth and in Space. Despite the abundance of these valuable data, the need for bioinformatics expertise, particularly as it relates to the niche filed of space biology, and a lack of accessible resources for processing these data limit their usefulness in deriving biological insights. The NASA Open Science Data Repository (OSDR) provides access to omics data from various spaceflight and analog studies. To enhance the accessibility and reusability of these data, GeneLab (part of OSDR) designs and implements standardized, community-driven, open-source bioinformatics workflows to transform raw omics data into standardized processed data. Currently, GeneLab-processed data from hundreds of space studies have been reused for meta-analyses. This has led to new insights and scientific publications that extend beyond the initial research, thereby enriching our understanding of molecular-scale biological responses to the space environment. To make these bioinformatics workflows open and accessible, GeneLab teamed up with DOE-funded initiatives, including the National Microbiome Data Collaborative (NMDC), to create the NASA EDGE [Empowering the Development of Genomics Expertise] Bioinformatics web-based platform. NASA EDGE utilizes shared compute resources to run the GeneLab standardized bioinformatics workflows, which eliminates the need for researchers to have their own high performance computing cluster. The web-based platform makes complicated biological analyses incredibly easy to perform, thus expanding the reach of these analyses to bioinformatics novices, students, and even citizen scientists enabling them to contribute to scientific discoveries and progress. The authors will demonstrate how the NASA EDGE platform can be used to process microbial omics data hosted on OSDR as well as user-generated omics datasets using GeneLab’s standard workflows.

Amanda M. Saravia-Butler↗

Trajectory Engineering with Modular Patched Conics for Entry Systems and TPS (TEMPEST)

Brief Presenter Biography (35 word limit): Bohdan Wesely is an Aerospace Engineer in the Entry Systems and Technology Division at Ames. He has worked on a variety of projects for NASA including integrated TPS (thermal protection system) flight hardware deliveries and testing services for commercial partners. Introduction: TEMPEST is a new trajectory analysis framework that is designed to fill the gap between dedicated flight mechanics tools and aerothermal and TPS sizing tools. The project started as an SJSU master’s thesis and has since evolved into a general conceptual design tool capable of studying a wide variety of entry problems. Development is ongoing in the Entry Systems and Technology Division at NASA ARC. Why TEMPEST: Space missions involving entry into a planetary atmosphere involve a series of unique requirements across multiple disciplines. Whether it is traditional entry descent and landing (EDL), or aerocapture, the vehicle must navigate to its target landing location or orbit state, and the TPS must protect the payload during entry. The design process typically involves iterative handoffs between various flight mechanics, flow solver, and material response level tools. During the early conceptual phase, a wide variety of feasible trajectories are simulated in a Monte Carlo scenario which broadly satisfy the mission or landing requirements. Next, computational fluid dynamics (CFD), direct simulation Monte Carlo (DSMC), and other flow solver analyses are performed at various key trajectory points to generate an aero-database, heating and TPS design requirements also emerge at this stage. At this point, with updated aerodynamics from the various flow solvers, trajectories can be re-run, this in turn can change the required freestream conditions for the CFD tools, and as a project progresses, these analyses converge, and uncertainty is reduced. However, there is always a “hand-off” occurring between two inherently coupled phenomena. Analysis Description: One of the goals with TEMPEST is to use a variety of first principles estimation methods coupled with an atmosphere model to predict vehicle aerothermodynamics across the entire flight regime while propagating a 3 or 6 degree of freedom (DoF) trajectory. Aerodynamics methods include modified Newtonian, Maxwell and Cercignani- Lampis-Lord (CLL) for continuum, transitional, and free molecular flow regimes. Aerothermodynamics include boundary layer and reference enthalpy methods, and Mutation++ for non-equilibrium chemistry modeling. TEMPEST is also capable of stitching multiple trajectory segments together to study mission scenarios like multi-pass aerocapture and aero-gravity assists. Most of the program is implemented in MATLAB using modern system objects, it relies on several C++ shared libraries for supporting tools like Gmsh, the Global Reference Atmospheric Model (GRAM), and Mutation++. The various first principles aerothermal estimation methods are discretized across either a structured axisymmetric panel mesh or an unstructured tri-mesh generated from an open-source tool such as Gmsh, this allows solutions on the same mesh to be compared across tools such as CB-Aero. CFD Coupling. A physics-aware, gaussian process CFD anchoring scheme is proposed to adjust the various first principles methods as a CFD database is populated. One goal for this anchoring module is to inform the project where CFD should be run. Full knowledge of the entire trajectory, atmosphere, and aerothermodynamics allows for easier identification of high sensitivity areas and uncertainty quantification. While the first principles effects are well known and proven accurate in existing tools such as CB- Aero and Cart3D, a physics aware CFD anchoring scheme increases tool credibility across a project lifecycle. Material Response Modeling. Correct TPS sizing is critical for optimizing mass for science payloads and ensuring mission success. The process typically involves a thermal analysis along the trajectory with surface heating environments as a boundary condition. Several design constraints are maximum bondline temperature and maximum recession with various margining techniques. The material response tool FIAT, developed out of NASA Ames, is currently being integrated into the TEMPEST environment. TPS recession, shape change, mass loss, and mass property alteration are all factors that can perturb an entry trajectory. For missions like Mars 2020, recession was minimal and was safely handled separately as a post process. For missions such as Jupiter Galileo with a high TPS mass fraction or asteroid entries, recession plays a major role. The proposed fully coupled scheme is to use an epoch-based approach where the trajectory integration is halted after a recession threshold, the energy balance and FIAT are solved at each panel, the mesh, aerodynamics, and mass properties are updated, and the trajectory continues. Several computational tradeoffs have been made during the development of TEMPEST to limit the cost of a single trajectory and preserve its utility as a conceptual, rapid iteration tool. Conclusion: Development of TEMPEST is ongoing and the project is still in its infancy. This talk aims to showcase its unique capabilities to support future NASA entry systems missions.

Bohdan O Wesely↗

Electron-Withdrawing meso -Substituents Turn On Magneto-Optical Activity in Porphyrins

A series of square planar metalloporphyrins (M(TPP), TPP is 5,10,15,20-tetraphenylporphyrin and M(TPFPP), TPFPP is 5,10,15,20-tetrapentafluorophenylporphyrin; M is Zn 2+ , Ni 2+ , Pd 2+ , or Pt 2+ ) with distinct meso-substituents were prepared, and their magneto-optical activity (MOA) was characterized by magnetic circular dichroism (MCD) and magneto-optical rotary dispersion spectroscopy (MORD; also known as Faraday rotation spectroscopy). MOA is crucial in the development of next-generation magneto-optical devices and quantum computing. Here, the data show that the presence of meso-pentafluorophenyl substituents results in significant increase in MOA in comparison to the homologous phenyl group. Differences in the MOA of these metalloporphyrins are rationalized using the Gouterman four-orbital model and pave the way for rational design of improved and tailorable magneto-optical materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular Mechanisms Underlying Surfactant-Based Plastics De-Inking

Surfactant-mediated binder removal is critical for de-inking pretreatment in plastics recycling, yet the molecular mechanisms governing surfactant performance remain poorly understood. We used all-atom (AA) and coarse-grained (CG) molecular dynamics (MD) simulations alongside alkaline surfactant washing experiments to investigate interactions between a series of surfactants and a polyether urethane (PEU) binder in solution and on a polyethylene (PE) surface. Experiments reveal a range of de-inking efficiencies, ranging from <25 to >95% depending upon surfactant headgroup charge and tail length. AA simulations reveal that charged surfactants reach stable levels of surfactant coverage, while nonionic surfactants aggregate on the binder. CG umbrella sampling calculations quantify the thermodynamics of binder desorption in water. In ∼0.25 M surfactant solutions, up to a 52% reduction in the free energy barrier is computed, with trends in good agreement (R 2 = 0.92, Pearson’s r = –0.96, Spearman’s ρ = –0.83) with experimental de-inking efficiencies. We find that charged surfactants are more effective than nonionic surfactants for de-inking and propose three regimes of surfactant de-inking processes: good de-inking occurs in surfactants that promote PEU desorption with a low radius of gyration (R g ); moderate de-inking occurs when surfactants stabilize PEU but increase R g ; poor de-inking occurs in surfactants that aggregate on the binder and promote extensive anchoring to the surface. Overall, these molecular-level insights have the potential to guide the design of surfactant formulations for plastics recycling applications.

ink removal↗

Multiphase tin equation of state using density functional theory

In this work, we perform density functional theory (DFT) calculations of five solid phases and the liquid phase of tin. The calculations include cold curves of the five solid phases, phonon calculations in the quasiharmonic approximation over a range of volumes for each solid phase, and DFT-based molecular dynamics (DFT-MD) simulations of the liquid phase, including those of the melt curve using the Z method. Using the DFT results, we construct a tabular multiphase sesame equation of state for tin, referred to as sesame 2162. Comparisons to experimental data are made and show a high level of agreement in isobaric data, isothermal data, shock data, and phase boundary measurements, including measurements of the melt curve. The 2162 EOS will be useful for hydrodynamics simulations and has been designed with an eye toward hydrodynamics simulations that incorporate materials strength models and allow for modeling of the kinetics of phase transitions.

3-dimensional systems↗

Pore2Chip: All-in-one python tool for soil microstructure analysis and micromodel design

The Pore2Chip Python package is designed to create 2D micromodels using extracted data from 3D X-ray computed tomography (XCT) images. This package helps analyze soil structure and function, allowing for the investigation of hydro-biogeochemical processes that impact mineral extraction and reactivity, oxygen concentrations, and nutrient availability in disturbed or managed soils. Key metrics encompass pore size distributions, pore throat size distributions, and connectivity (pore coordination numbers). The final output is a 2D scalable SVG design representing a core or aggregate. Designs can be fabricated with methods such as laser etching, 3D printing, and photolithography.

lab-on-chip↗

FPGA-Accelerated Range-Limited Molecular Dynamics

Long timescale Molecular Dynamics (MD) simulation of small molecules is crucial in drug design and basic science. To accelerate a small data set that is executed for a large number of iterations, high-efficiency is required. Recent work in this domain has demonstrated that among COTS devices only FPGA-centric clusters can scale beyond a few processors. The problem addressed here is that, as the number of on-chip processors has increased from fewer than 10 into the hundreds, previous intra-chip routing solutions are no longer viable. We find, however, that through various design innovations, high efficiency can be maintained. These include replacing the previous broadcast networks with ring-routing and then augmenting the rings with out-of-order and caching mechanisms. Others are adding a level of hierarchical filtering and memory recycling. Two novel optimized architectures emerge, together with a number of variations. These are validated, analyzed, and evaluated. We find that in the domain of interest speed-ups over GPUs are achieved. Finally, the potential impact is that this system promises to be the basis for scalable long timescale MD with commodity clusters.

97 MATHEMATICS AND COMPUTING↗

Electric-field-induced crossover of polarization reversal mechanisms in Al 1–x Sc x N ferroelectrics

Scandium-doped aluminum nitride, Al 1–x Sc x N, represents a new class of displacive ferroelectric materials with high polarization and sharp hysteresis along with high-temperature resilience, facile synthesizability and compatibility with standard CMOS fabrication techniques. The fundamental physics behind the transformation of unswitchable piezoelectric AlN into switchable Al–Sc–N ferroelectrics depends upon important atomic properties such as local structure, dopant distributions and the presence of competing mechanism of polarization switching in the presence of an applied electric-field that have not been understood. We computationally synthesize Al 1–x Sc x N to quantify the inhomogeneity of Sc distribution and phase segregation, and characterize its crystal and electronic structure as a function of Sc-doping. Nudged elastic band calculations of the potential energy surface and quantum molecular dynamics simulations of direct electric-field-driven ferroelectric switching reveal a crossover between two polarization reversal mechanisms—inhomogeneous nucleation-and-growth mechanism originating near Sc-rich regions in the limit of low applied fields and nucleation-limited-switching in the high-field regime. Finally, understanding polarization reversal pathways for these two mechanisms as well as the role of local Sc concentration on activation barriers provides design rules to identify other combinations of dopant elements, such as Zr, Mg etc. to synthesize superior AlN-based ferroelectric materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Modelling of photodegradation in solar cell modules of substrate and superstrate design made with ethylene-vinyl acetate as pottant material

A computer model was developed which can generate realistic concentration versus time profiles of the chemical species formed during photooxidation of hydrocarbon polymers using as input data a set of elementary reactions with corresponding rate constants and initial conditions. The results of computer simulation have been shown to be consistent with the general experimental observations of the photooxidation of polyethylene exposed to sunlight at ambient temperatures. The useful lifetime (5% oxidation) of the unstabilized polyethylene is predicted to vary from a few months in hot weather (100 F) to almost two years in cool weather (45 F) with an apparent net activation energy of 10 kcal/mol. Modelling studies of alternate mechanisms for stabilization of clear, amorphous, linear polyethylene suggest that the optimum stabilizer would be a molecularly dispensed additive in very low concentration which can trap peroxy radicals and also decompose hydroperoxides.

Somersall, A. C.↗

Influence of misfit dislocations on ionic conductivity at oxide interfaces

Mismatched complex oxide thin films and heterostructures have gained significant traction for use as electrolytes in intermediate temperature solid oxide fuel cells, wherein interfaces exhibit variation in ionic conductivity as compared to the bulk. Although misfit dislocations present at interfaces in these structures impact ionic conductivity, the fundamental mechanisms responsible for this effect are not well understood. To this end, a kinetic lattice Monte Carlo (KLMC) model was developed to trace oxygen vacancy diffusion at misfit dislocations in SrTiO 3 /BaZrO 3 heterostructures and elucidate the atomistic mechanisms governing ionic diffusion at oxide interfaces. The KLMC model utilized oxygen vacancy migration energy barriers computed using molecular statics. While some interfaces promote oxygen vacancy diffusion, others impede their transport. Fundamental factors such as interface layer chemistry, misfit dislocation structure, and starting and ending sites of migrating ions play a crucial role in oxygen diffusivity. Molecular dynamics (MD) simulations were further performed to support qualitative trends for oxygen vacancy diffusion. Overall, the agreement between KLMC and MD is quite good, though MD tends to predict slightly higher conductivities, perhaps a reflection of nuanced structural relaxations that are not captured by KLMC. The current framework comprising KLMC modeling integrated with molecular statics offers a powerful tool to perform mechanistic studies focused on ionic transport in thin film oxide electrolytes and facilitate their rational design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Progress Report for W911NF-23-1-0323: Development of Scalable Three-Dimensional Ion Traps for Quantum Information Processing

Trapped atomic ions are a promising platform for scalable quantum information processing. They lead in many key metrics such as single and two qubit gate fidelities, as well as quantum volume. We recently realized novel 3D ion traps with a high resolution 3D-printing process. The traps combine the scalability potential of surface chip traps with the superior trap performance of macroscopic 3D ion traps. Like photolithography, 3D-printing is a digitally defined process and hence allows for rapid iteration between design and fabrication. In contrast to photolithography, it also allows for fully defined 3D structures and, thus, is an ideal process to develop large, well-defined trap arrays with complex 3D electrode structures. Our current goal is to implement key procedures and perform critical measurements that justify incorporation of 3D-printed traps into large-scale quantum computing efforts. En route, we recently realized trapping in horizontal traps that are operating at cryogenic temperatures.

74 ATOMIC AND MOLECULAR PHYSICS↗

FY20 Proxy App Suite Release: Report for ECP Proxy App Project Milestone ADCD-504-10

Version 4.0 of the ECP Proxy App Suite is practically unchanged from the previous release. The current set of proxies has proven useful for many aspects of benchmarking and co-design and we see little reason to alter the suite. Although there have been few changes to the ECP suite, the team has been hard at work in other areas. In the area of Machine Learning (ML) we have now created a separate proxy suite dedicated to this scientific applications of ML. The suite includes: miniGAN (Generative Adversarial Networks), miniRL (Reinforcement Learning), CRADL (inline inference), Cosmoflow-Benchmark (Convolutional Neural Network), and MLPerf-DeepCam (Climate Segmentation Benchmark). Section 3 contains more information about these proxies as well as the principles that are guiding the development of the suite. We have surveyed available proxies for several application domains including Computational Fluid Dynamics, Quantum Chemistry, Quantum Computing Simulation, Molecular Dynamics, Monte Carlo Transport, and Density Functional Theory to identify gaps in proxy coverage. Several new proxy apps are either already available or will be released soon to fill these gaps. Section 4 provides full details. Finally, section 5 reports on our continued collaboration with the ECP Continuous Integration (CI) effort to use proxy apps to help identify problems and roadblocks to cross-lab CI. We have also assisted the El Capitan Center of Excellence (COE) to stand up a CI system that will be used to test releases of HPE and AMD software stacks. We hope that the COE effort can serve as a model for ECP by showing how the Proxy App Team can work with AD and ST teams identify critical features, kernels, patterns, etc. and incorporate them into a CI system that will help ensure that Frontier and Aurora will provide those needed capabilities.

97 MATHEMATICS AND COMPUTING↗

Potent Noncovalent Inhibitors of the Main Protease of SARS-CoV-2 from Molecular Sculpting of the Drug Perampanel Guided by Free Energy Perturbation Calculations

Starting from our previous finding of 14 known drugs as inhibitors of the main protease (M pro ) of SARS-CoV-2, the virus responsible for COVID-19, we have redesigned the weak hit perampanel to yield multiple noncovalent, nonpeptidic inhibitors with ca. 20 nM IC 50 values in a kinetic assay. Free-energy perturbation (FEP) calculations for M pro -ligand complexes provided valuable guidance on beneficial modifications that rapidly delivered the potent analogues. The design efforts were confirmed and augmented by determination of high-resolution X-ray crystal structures for five analogues bound to M pro . Results of cell-based antiviral assays further demonstrated the potential of the compounds for treatment of COVID-19. In addition to the possible therapeutic significance, the work clearly demonstrates the power of computational chemistry for drug discovery, especially FEP-guided lead optimization.

99 GENERAL AND MISCELLANEOUS↗

Optical Characterization of Molecular Contaminant Films

A semi-empirical method of optical characterization of thin contaminant films on surfaces of optical components has been conceived. The method was originally intended for application to films that become photochemically deposited on such optical components as science windows, lenses, prisms, thinfilm radiators, and glass solar-cell covers aboard spacecraft and satellites in orbit. The method should also be applicable, with suitable modifications, to thin optical films (whether deposited deliberately or formed as contaminants) on optical components used on Earth in the computer microchip laser communications and thin-film industries. The method is expected to satisfy the need for a means of understanding and predicting the reductions in spectral transmittance caused by contaminant films and the consequent deterioration of performances of sensitive optical systems. After further development, this method could become part of the basis of a method of designing optical systems to minimize or compensate for the deleterious effects of contaminant films. In the original outer-space application, these deleterious effects are especially pronounced because after photochemical deposition, the films become darkened by further exposure to solar vacuum ultraviolet (VUV) radiation. In this method, thin contaminant films are theoretically modeled as thin optical films, characterized by known or assumed values of thickness, index of refraction, and absorption coefficient, that form on the outer surfaces of the original antireflection coating on affected optical components. The assumed values are adjusted as needed to make actual spectral transmittance values approximate observed ones as closely as possible and to correlate these values with amounts of VUV radiation to which the optical components have been exposed. In an initial study, the method was applied in correlating measured changes in transmittance of high-purity fused silica photochemically coated with silicone films of various measured thicknesses and exposed to various measured amounts of VUV radiation. In each case, it was found to be possible to select an index of refraction and absorption coefficient that made the ultraviolet, visible, and infrared transmittance changes predicted by the model match the corresponding measured transmittance changes almost exactly.

Visentine, James T.↗

Autonomous reinforcement learning agent for chemical vapor deposition synthesis of quantum materials

Abstract Predictive materials synthesis is the primary bottleneck in realizing functional and quantum materials. Strategies for synthesis of promising materials are currently identified by time-consuming trial and error and there are no known predictive schemes to design synthesis parameters for materials. We use offline reinforcement learning (RL) to predict optimal synthesis schedules, i.e., a time-sequence of reaction conditions like temperatures and concentrations, for the synthesis of semiconducting monolayer MoS 2 using chemical vapor deposition. The RL agent, trained on 10,000 computational synthesis simulations, learned threshold temperatures and chemical potentials for onset of chemical reactions and predicted previously unknown synthesis schedules that produce well-sulfidized crystalline, phase-pure MoS 2 . The model can be extended to multi-task objectives such as predicting profiles for synthesis of complex structures including multi-phase heterostructures and can predict long-time behavior of reacting systems, far beyond the domain of molecular dynamics simulations, making these predictions directly relevant to experimental synthesis.

36 MATERIALS SCIENCE↗

The Unified Phenotype Ontology : a framework for cross-species integrative phenomics

Phenotypic data are critical for understanding biological mechanisms and consequences of genomic variation, and are pivotal for clinical use cases such as disease diagnostics and treatment development. For over a century, vast quantities of phenotype data have been collected in many different contexts covering a variety of organisms. The emerging field of phenomics focuses on integrating and interpreting these data to inform biological hypotheses. A major impediment in phenomics is the wide range of distinct and disconnected approaches to recording the observable characteristics of an organism. Phenotype data are collected and curated using free text, single terms or combinations of terms, using multiple vocabularies, terminologies, or ontologies. Integrating these heterogeneous and often siloed data enables the application of biological knowledge both within and across species. Existing integration efforts are typically limited to mappings between pairs of terminologies; a generic knowledge representation that captures the full range of cross-species phenomics data is much needed. We have developed the Unified Phenotype Ontology (uPheno) framework, a community effort to provide an integration layer over domain-specific phenotype ontologies, as a single, unified, logical representation. uPheno comprises (1) a system for consistent computational definition of phenotype terms using ontology design patterns, maintained as a community library; (2) a hierarchical vocabulary of species-neutral phenotype terms under which their species-specific counterparts are grouped; and (3) mapping tables between species-specific ontologies. This harmonized representation supports use cases such as cross-species integration of genotype-phenotype associations from different organisms and cross-species informed variant prioritization.

59 BASIC BIOLOGICAL SCIENCES↗

Hierarchical Self-Assembly Pathways of Peptoid Helices and Sheets

Peptoids (N-substituted glycines) are a class of tailorable synthetic peptidomic polymers. Amphiphilic diblock peptoids have been engineered to assemble 2D crystalline lattices with applications in catalysis and molecular separations. Assembly is induced in an organic solvent/water mixture by evaporating the organic phase, but the assembly pathways remain uncharacterized. We conduct all-atom molecular dynamics simulations of Nbrpe6Nc6 as a prototypical amphiphilic diblock peptoid comprising an NH 2 -capped block of six hydrophobic N-((4-bromophenyl)ethyl)glycine residues conjugated to a polar NH 3 (CH 2 ) 5 CO tail. We identify a thermodynamically controlled assembly mechanism by which monomers assemble into disordered aggregates that self-order into 1D chiral helical rods then 2D achiral crystalline sheets. We support our computational predictions with experimental observations of 1D rods using small-angle X-ray scattering, circular dichroism, and atomic force microscopy and 2D crystalline sheets using X-ray diffraction and atomic force microscopy. Furthermore, this work establishes a new understanding of hierarchical peptoid assembly and principles for the design of peptoid-based nanomaterials.

59 BASIC BIOLOGICAL SCIENCES↗

Integrating Experiments and Simulations to Reveal Anisotropic Growth Mechanisms and Interfaces of a One-Dimensional Zeolite

Zeolites are nanoporous crystalline materials critical for diverse industrial applications, yet their growth mechanisms are poorly understood. Here, this study presents a novel integrated framework combining experimental synthesis, high-resolution imaging, coarse-grained molecular dynamics simulations, and computer vision to uncover the mechanisms of growth of SSZ-24, a 1D channel zeolite. We demonstrate how synthesis conditions, such as temperature and reactant concentration, govern crystal anisotropy and surface roughness with growth dynamics differing markedly by crystallographic orientation. Along the channels, growth involves minimal energy barriers and rapid nucleation, resulting in rough surfaces. In contrast, growth perpendicular to the channels requires cooperative molecular organization and is highly sensitive to thermodynamic and kinetic conditions, yielding smooth anisotropic surfaces under low driving forces. By simulating transmission electron microscopy (TEM) images, we bridge molecular-scale simulations with experimental observations, identifying distinct growth mechanisms along different crystal planes. This work offers molecular-level insights into zeolite crystallization, advancing the rational design of nanoporous materials. The integration of cross-disciplinary methodologies establishes a transformative framework for optimizing zeolite synthesis, with implications for broader classes of materials.

Bertolazzo, Andressa A. [Univ. of Utah, Salt Lake ↗