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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Polyhydrido Copper Nanoclusters with a Hollow Icosahedral Core: [Cu 30 H 18 {E 2 P(OR) 2 } 12 ] (E=S or Se; R= n Pr, i Pr or i Bu)

Although atomically precise polyhydrido copper nanoclusters are of prime interest for a variety of applications, they have so far remained scarce. Here, we describe the synthesis of a dithiophosphate-protected copper(I) hydride-rich nanocluster (NC), [Cu 30 H 18 {S 2 P(O n Pr) 2 } 12 ] ( 1 H ), fully characterized by various spectroscopic methods and single-crystal X-ray diffraction. The X-ray structure of 1 H reveals an unprecedented central Cu 12 hollow icosahedron. Six faces of this icosahedron are capped by Cu 3 triangles, the whole Cu 30 core being wrapped by twelve dithiophosphate ligands and the whole cluster has ideal S 6 symmetry. The locations of the 18 hydrides in 1 H were ascertained by a single-crystal neutron diffraction study. They are composed of three types: capping μ 3 -H, interstitial μ 4 -H (seesaw) and μ 5 -H ligands (square pyramidal), in good agreement with the DFT simulations. The numbers of hydrides and ligand resonances in the 1 H NMR spectrum of 1 H are in line with their coordination environment in the solid state, retaining the S 6 symmetry in solution. Furthermore, two new Se-protected polyhydrido copper nanoclusters, [Cu 30 H 18 {Se 2 P(OR) 2 } 12 ] ( 2 H : R= i Pr 3 H : R= i Bu) were synthesized from their sulfur relative 1 H via ligand displacement reaction and their X-ray structures feature the exceptional case where both the NC shape and size are fully conserved during the course of ligand exchange. DFT and TD-DFT calculations allow understanding the bonding and optical properties of clusters 1 H – 3 H . In addition, the reaction of 1 H with [Pd(PPh 3 ) 2 Cl 2 ] in the presence of terminal alkynes led to the formation of new bimetallic Cu–Pd alloy clusters [PdCu 14 H 2 {S 2 P(O n Pr) 2 } 6 (C≡CR) 6 ] ( 4 : R=Ph; 5 : R = C 6 H 4 F).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Development of an Enzyme-Inhibitor Reaction Using Cellular Retinoic Acid Binding Protein II for One-Pot Megamolecule Assembly

This paper presents an enzyme building block for the assembly of megamolecules. The system is based on the inhibition of the human-derived cellular retinoic acid binding protein II (CRABP2) domain. We synthesized a synthetic retinoid bearing an arylfluorosulfate group, which uses sulfur fluoride exchange click chemistry to covalently inhibit CRABP2. We conjugated both the inhibitor and a fluorescein tag to an oligo(ethylene glycol) backbone and measured a second-order rate constant for the protein inhibition reaction of approximately 3,600 M -1 s -1 . We used this new enzyme-inhibitor pair to assemble multi-protein structures in one-pot reactions using three orthogonal assembly chemistries to demonstrate exact control over the placement of protein domains within a single, homogeneous molecule. This work enables a new dimension of control over specificity, orientation, and stoichiometry of protein domains within atomically precise nanostructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A historical perspective on porphyrin-based metal–organic frameworks and their applications

Porphyrins are important molecules widely found in nature in the form of enzyme active sites and visible light absorption units. Recent interest in using these functional molecules as building blocks for the construction of metal–organic frameworks (MOFs) have rapidly increased due to the ease in which the locations of, and the distances between, the porphyrin units can be controlled in these porous crystalline materials. Porphyrin-based MOFs with atomically precise structures provide an ideal platform for the investigation of their structure–function relationships in the solid state without compromising accessibility to the inherent properties of the porphyrin building blocks. Here, this review will provide a historical overview of the development and applications of porphyrin-based MOFs from early studies focused on design and structures, to recent efforts on their utilization in biomimetic catalysis, photocatalysis, electrocatalysis, sensing, and biomedical applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Computational modeling of grain boundary segregation: A review

Nearly all metals, alloys, ceramics, and their associated composites are polycrystalline in nature, with grain boundaries that separate well-defined crystalline regions that influence materials properties. In all but the most pure elemental systems, intentional solutes or impurities are present and can segregate to, or less commonly away from, the grain boundaries, in turn influencing boundary behavior, their stability, and associated materials properties. In some cases, grain-boundary segregation can also trigger “phase-like” structural transitions that dramatically alter the essential nature of the boundary. With the development of advanced electron microscopy techniques, researchers can directly observe grain-boundary structures and segregation with atomic precision. Despite such spatial resolution, the underlying mechanisms governing grain-boundary segregation remain difficult to characterize. As a result, computational modeling techniques such as density functional theory, molecular dynamics, mesoscale phase-field, continuum defect theory, and others are important complementary tools to experimental observations for studying grain-boundary segregation behavior. In conclusion, these computational methods offer the ability to explore the underlying formation mechanisms of grain-boundary segregation, elucidate complex segregation behavior, and provide insights into solutions to effectively controlling microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Underlying mechanism of structural transformation between GaSb and GaAs response to intense electronic excitation

Ion irradiation of semiconductors has emerged as a promising approach for fabricating self-organized nanosystems with high atomic precision, despite often being accompanied by undesirable phenomena. Exploring the mechanisms underlying structural transformations is crucial for assessing nanostructure array types under complex irradiation environments. By quantitatively calculating the thermodynamically driven processes and analyzing the impact of intrinsic structural parameters, distinct structural transformations in response to intense electronic excitation are systematically investigated in gallium antimonide (GaSb) and gallium arsenide (GaAs) systems. In high-energy regimes, the nanofibers layer of GaSb exhibits intriguing structural discrepancy, characterized by partial nanofibers with coherent boundaries, interspersed nanopores accompanied by antisite defects and Ga precipitates, distinguishing to a series of discontinuous latent tracks that emerged within cylindrical trajectories in GaAs. Furthermore, significant diffusion behaviors of the nanohillocks are discovered in GaAs, with higher average roughness than GaSb, driven by the gradient stress distribution influenced by the free-surface effects. The deposition energy for melting phase formation, Gibbs free energy, and Ga diffusion coefficients contribute to the distinctive structural features, evidencing relatively stable morphological configurations and higher irradiation resistance in GaAs. Consequently, special optoelectronic properties associated with structural discrepancies facilitate the design and optimization of material functionalities by irradiation technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Data-Driven Strategies for Accelerated Materials Design

The ongoing revolution of the natural sciences by the advent of machine learning and artificial intelligence sparked significant interest in the material science community in recent years. The intrinsically high dimensionality of the space of realizable materials makes traditional approaches ineffective for large-scale explorations. Modern data science and machine learning tools developed for increasingly complicated problems are an attractive alternative. An imminent climate catastrophe calls for a clean energy transformation by overhauling current technologies within only several years of possible action available. Tackling this crisis requires the development of new materials at an unprecedented pace and scale. For example, organic photovoltaics have the potential to replace existing silicon-based materials to a large extent and open up new fields of application. In recent years, organic light-emitting diodes have emerged as state-of-the-art technology for digital screens and portable devices and are enabling new applications with flexible displays. Reticular frameworks allow the atom-precise synthesis of nanomaterials and promise to revolutionize the field by the potential to realize multifunctional nanoparticles with applications from gas storage, gas separation, and electrochemical energy storage to nanomedicine. In the recent decade, significant advances in all these fields have been facilitated by the comprehensive application of simulation and machine learning for property prediction, property optimization, and chemical space exploration enabled by considerable advances in computing power and algorithmic efficiency. In this Account, we review the most recent contributions of our group in this thriving field of machine learning for material science. We start with a summary of the most important material classes our group has been involved in, focusing on small molecules as organic electronic materials and crystalline materials. Specifically, we highlight the data-driven approaches we employed to speed up discovery and derive material design strategies. Subsequently, our focus lies on the data-driven methodologies our group has developed and employed, elaborating on high-throughput virtual screening, inverse molecular design, Bayesian optimization, and supervised learning. We discuss the general ideas, their working principles, and their use cases with examples of successful implementations in data-driven material discovery and design efforts. Furthermore, we elaborate on potential pitfalls and remaining challenges of these methods. Finally, we provide a brief outlook for the field as we foresee increasing adaptation and implementation of large scale data-driven approaches in material discovery and design campaigns.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Truncating 2D Framework Materials Down to a Single Pore: Synthetic Approaches and Opportunities

Here, in this Accounts article, we summarize our recent work on truncating conjugated two-dimensional framework materials down to a single pore, or a single macrocycle. Conjugated 2D architectures have emerged as one of the most synthetically adaptable motifs for coupling semiconductivity and porosity in metal–organic frameworks (MOFs) and covalent organic frameworks (COFs). However, despite their prevalence, 2D architectures have several limitations. In particular, the strong interlayer π–π stacking can limit both processability and the accessibility of internal active sites. We have found that simple macrocycles preserve key aspects of 2D framework structure and function, including porosity and out-of-plane electrical conductivity, while providing improved processability, surface tunability, and mass transport properties. In this article, we first describe our synthetic approach and general design considerations. Specifically, we show how ditopic analogues of the tritopic ligands commonly found in the synthesis of 2D MOFs and COFs can be used to achieve a diverse library of conjugated macrocycles that resemble fragments of semiconducting frameworks in both form and function. The length of the peripheral side chains, the size of the aromatic core, and the solubility of intermediates are all key variables in favoring selective macrocycle formation over undesired linear polymers and oligomers. Next, we highlight the unique advantages that macrocycles provide, including improved processability, atomically precise surface tunability, and greater active site accessibility. In particular, the identity of the peripheral side chains dramatically impacts both solubility and colloidal stability as well as crystal size and morphology. We further show how the solution processability and nanoscale dimensions of macrocycles can simplify electronic device fabrication and improve electrochemical performance. Finally, we end with a forward-looking discussion on how macrocycles offer a unique bridge between conjugated molecules and extended frameworks, enabling new application areas and fundamental science.

charge transport↗
DOE OSTI2025

Ligand-Driven Electrochemical Tuning of Co 6 Se 8 Chevrel Clusters

Molecular “Chevrel-type” clusters of the formula Co 6 Se 8 L 6 (L = neutral ligand) are a well-studied class of clusters due to their utility as molecular analogues to the Chevrel extended solid phase and their application as subunits in hierarchical materials. However, their solution and optical properties remain relatively underexplored. Aiming to develop the fundamental relationships between the molecular and electronic structures of these clusters and their electrochemical and photophysical properties, this work reports the preparation of a series of Co 6 Se 8 (P­(C 6 H 4 R) 3 ) 6 -type clusters with R = Cl (1), F (2), H (3), CH 3 (4), and OCH 3 (5) via a stepwise synthetic approach. Solution and solid-state experimental characterization and density functional theory calculations reveal that the Co 6 Se 8 cores of 1–5 maintain consistent electronic and structural properties despite the variation of the triarylphosphine ligand para-substituent Hammett parameters (σ p ). However, cyclic voltammetry measurements indicate that the electron transfer energetics of 1–5 are strongly influenced by ligand substitution, with the E 1/2 of a given redox event spanning ∼0.5 V depending on the triarylphosphine ligand’s σ p . In conclusion, these findings support the characterization of Co 6 Se 8 clusters as atomically precise nanoclusters with both the structural robustness and the electrochemical tunability needed to act as components in larger charge transfer assemblies.

Wheaton, Amelia M. [Argonne National Laboratory (A↗
DOE OSTI2026

Ensemble Effects on Hydroxide Bond Dissociation Free Energies in Polyoxovanadate Clusters

Understanding structure-property relationships is foundational to numerous modern chemistries, such as proton-coupled electron transfer (PCET). However, an experimentally measured property is the result of the behavior from an ensemble of molecules. Neglecting ensemble effects, especially under complex chemical environments, may obfuscate these relationships and lead to discrepancies between theory and experiment. In this work, we demonstrate the impact of configurational entropy and local chemical environments on hydroxide bond dissociation free energies [BDFE- (O−H)] for a set of polyoxovanadate nanoclusters, at ambient conditions. The O−H bond strengths are investigated via density functional theory (DFT) coupled with statistical thermodynamic analysis and bilinear modeling, and compared with previous experimental results on the same systems, namely electrochemical solutions of: [V 6 O 13−x (OH) x (TRIOL R ) 2 ] −2 (x = 2, 4, 6; R = NO 2 , Me) and [V 6 O 11−x (OMe) 2 (OH) x (TRIOL NO 2 ) 2 ] −2 (x = 2, 4). Interestingly, we find that ensemble effects, even at room temperature, can account for a significant portion of the BDFE(O−H) trend with the degree of reduction via H atom binding, which cannot be fully captured by single-structure, static DFT calculations. Moreover, we find that the ensemble effects may be replicated statistically, requiring only enumeration of energetically accessible H-binding sites. With the ensemble effects resolved, we present a simple bilinear model to reconcile remaining biases between experiment and ensemble-informed theory, which corelate with clusterspecific electronic environment differences. The bilinear model achieves outstanding accuracy vs experiments with a root-mean squared error of 0.4 kcal/mol. Finally, based on the physicochemical characteristics of hydrogen interaction with polyoxometalates, we present a simple methodology that captures the BDFE(O−H) trend while dramatically reducing required DFT calculations by 98% and achieving accuracy within 1 kcal/mol. Overall, this work elucidates the roles and structural origins of configurational entropy and chemical effects on polyoxometalate hydroxide bond energies, with potential applicability to various atomically precise metal oxide systems. Importantly, it introduces models for rapid and highly accurate property calculations in connection with experiments.

Cluster chemistry↗
DOE OSTI2021

Azo(xy) vs Aniline Selectivity in Catalytic Nitroarene Reduction by Intermetallics: Experiments and Simulations

Intermetallic nanoparticles are promising catalysts in hydrogenation and fuel cell technologies. Much is known about the ability of intermetallic nanoparticles to selectively reduce nitro vs alkene, alcohol, or halide functional groups; less is known about their selectivity toward aniline vs azo or azoxy condensation products that result from the reduction of a nitro group alone. Because azo(xy)arenes bear promise as dyes, chemical stabilizers, and building blocks to functional materials but can be difficult to isolate, developing high surface area nanoparticle catalysts that display azo(xy) selectivity is desirable. To address this question, we studied a family of nanocrystalline group 10 metal (Pd, Pt)- and group 14 metal (Ge, Sn, Pb)-containing intermetallics-Pd 2 Ge, Pd 2 Sn, Pd 3 Sn 2 , Pd 3 Pb, and PtSn-in the catalytic reduction of nitroarenes. In contrast to monometallic Au, Pt, and Pd nanoparticles and "random" PdxSn1 – x nanoalloys, which are selective for aniline, nanoparticles of atomically precise intermetallic Pd 2 Ge, Pd 2 Sn, Pd 3 Sn 2 , and PtSn prefer an indirect condensation pathway and have a high selectivity for the azo(xy) products. The only exception is Pd 3 Pb, the most active among the intermetallic nanoparticles studied here, which is instead selective for aniline. Employing a novel application of molecular dynamics-based on machine learned potentials within a DeePMD framework-to heterogeneous catalysis, we are able to identify key reaction species on the different types of catalysts employed, furthering our understanding of the unique selectivity of these materials. By demonstrating how intermetallic nanoparticles can be as active yet more selective than other more traditional catalysts, this work provides new physical insights and opens new opportunities in the use of these materials in other important chemical transformations and applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Highly Asymmetric Graphene Layer Doping and Band Structure Manipulation in Rare Earth–Graphene Heterostructure by Targeted Bonding of the Intercalated Gadolinium

Heterostructures consisting of vertically stacked two-dimensional (2D) materials have recently gained large attention due to their highly controllable electronic properties and resulting quantum phases. In contrast to the mechanically stacked multilayered systems, which offer exceptional control over a stacking sequence or interlayer twist angles, the epitaxially grown 2D materials express unprecedented quality and stability over wafer-scale lengths. However, controlling the growth conditions remains a major obstacle toward the formation of complex, epitaxial heterostructures with well-defined electronic properties. Here, we synthesized a trilayer graphene heterostructure on the SiC(0001) substrate with two specific interlayer locations occupied by gadolinium. We applied multitechnique methodology based on low-temperature scanning tunneling microscopy/spectroscopy (STM/S) and angle-resolved photoelectron spectroscopy (ARPES) to determine the intercalant’s locations in the complex, epitaxial graphene heterostructure. Our approach relies on very high quality and large, micrometer-scale homogeneity of the synthesized system. The experimentally determined electronic structure is dominated by the two topmost graphene layers. Overall, our spectroscopic results show quantitative agreement between global ARPES, local STM/S, and density functional theory predictions. The characterized electronic properties primarily reflect highly anisotropic doping levels between the two corresponding graphene layers, which significantly affect the band structure topology. Two pairs of hybridized massive Dirac bands from our initial synthesis–the bilayer graphene on the SiC(0001) substrate–are transformed upon Gd intercalation into two pairs of massless Dirac bands with a new hybridization region in between. Our results open perspectives in the realization of exotic 2D quantum materials via atomically precise synthesis of epitaxial, multilayered graphene–rare earth heterostructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Exfoliation of Cu-Containing Poly(triazine imide): From Three-Dimensional to Two-Dimensional Particle Morphology

Controlling the morphological parameters of extended covalent organic frameworks remains challenging and represents an important yet often elusive metric of consideration. Typically, carbon nitride materials possess local ordering but remain largely amorphous in terms of their long-range order and orientation. This study probes the synthesis of a crystalline carbon nitride, poly(triazine imide) lithium bromide which possesses an atomically-precise extended structure, and demonstrates its exfoliation into a two-dimensional hexagonal sheet-like morphology. Furthermore, a previously unreported carbon nitride material, poly(triazine imide) copper bromide, or PTI-CuBr, was developed through an additional flux-assisted cation-exchange process and is shown to retain its internal Cu cations during solvothermal exfoliation. Characterization by dynamic light scattering and high-angle annular dark-field scanning electron microscopy reveals the morphological changes and captures the high aspect ratio of the thin carbon nitride sheets with <10 nm thickness while maintaining hundreds of nm in width. Additional characterization by energy-dispersive spectroscopy and X-ray photoelectron spectroscopy confirms that the Cu:Br:N molar ratio was maintained within the extended layers throughout the exfoliation process. This top-down synthesis approach differs from typical methods that isolate thin sheets for subsequent metal−cation coordination and illustrates the importance of maintaining oxygen-free conditions to minimize copper clustering. Thus, this new approach is demonstrated to provide a consistent and more homogeneous occupancy of the PTI pore spaces throughout the carbon nitride framework.

Exfoliation↗
DOE OSTI2020

Hyperbolic Cooper-Pair Polaritons in Planar Graphene/Cuprate Plasmonic Cavities

Hyperbolic Cooper-pair polaritons (HCP) in cuprate superconductors are of fundamental interest due to their potential for providing insights into the nature of unconventional superconductivity. In this study, we critically assess an experimental approach using near-field imaging to probe HCP in Bi 2 Sr 2 CaCu 2 O 8+x (Bi-2212) in the presence of graphene surface plasmon polaritons (SPP). Our simulations show that inherently weak HCP features in the near-field can be strongly enhanced when coupled to graphene SPP in layered graphene/hexagonal boron nitride (hBN)/Bi-2212 heterostructures. This enhancement arises from our multilayered structures effectively acting as plasmonic cavities capable of altering collective modes of a layered superconductor by modifying its electromagnetic environment. The degree of enhancement can be selectively controlled by tuning the insulating spacer thickness with atomic precision. Finally, we verify the expected renormalization of room-temperature graphene SPP using near-field infrared imaging. Our modeling, augmented with data, attests to the validity of our approach for probing HCP modes in cuprate superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Direct Observation of the Pressure-Induced Structural Variation in Gold Nanoclusters and the Correlated Optical Response

The ability to gradually modify the atomic structures of nanomaterials and directly identify such structural variation is important in nanoscience research. Here, we present the first example of a high-pressure single-crystal X-ray diffraction analysis of atomically precise metal nanoclusters. The pressure-dependent, subangstrom structural evolution of an ultrasmall gold nanoparticle, Au 25 S 18 , has been directly identified. We found that a 0.1 Å decrease of the Au–Au bond length could induce a blue-shift of 30 nm in the photoluminescence spectra of gold nanoclusters. From theoretical calculations, the origins of the blue-shift and enhanced photoluminescence under pressure are investigated, which are ascribed to molecular orbital symmetry and conformational locking, respectively. Here, the combination of the high-pressure in situ X-ray results with both theoretical and experimental optical spectra provides a direct and generalizable avenue to unveil the underlying structure–property relations for nanoclusters and nanoparticles which cannot be obtained through traditional physical chemistry measurements.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

CdSe Magic-Size Clusters Deviate from Nanocrystal-Size Scalings for Ultrafast Intraband Relaxation and Auger Recombination

The cluster regime of colloidal semiconductor quantum dots (QDs) occupies an interesting space on the continuum from molecule to bulk material and allow the study of QD properties at extreme quantum confinement limits. For typical QDs, several size-dependent property trends are well established including intraband relaxation rates and universal scaling of Auger recombination with particle volume. Advances in synthesis now allow isolation of atomically precise semiconductor magic-size clusters (MCs), which offer experimental insight regarding how electronic structure changes with particle size in the ultrasmall limit. Here, we report intraband cooling and Auger recombination for several stable CdSe MCs as a function of particle size and observe deviation from QD response in the cluster regime. We additionally show optical signatures ascribed to transient disordering 2 that appear in the single exciton regime for MCs, which point to complexities regarding their implementation.

Auger recombination↗
DOE OSTI2020

Engineering Edge States of Graphene Nanoribbons for Narrow-Band Photoluminescence

Solid-state narrow-band light emitters are on-demand for quantum optoelectronics. Current approaches based on defect engineering in low-dimensional materials usually introduce a broad range of emission centers. Here, we report narrow-band light emission from covalent heterostructures fused to the edges of graphene nanoribbons (GNRs) by controllable on-surface reactions from molecular precursors. Two types of heterojunction (HJ) states are realized by sequentially synthesizing GNRs and graphene nanodots (GNDs) and then coupling them together. HJs between armchair GNDs and armchair edges of the GNR are coherent and give rise to narrow-band photoluminescence. In contrast, HJs between the armchair GNDs and the zigzag ends of GNRs are defective and give rise to nonradiative states near the Fermi level. At low temperatures, sharp photoluminescence emissions with peak energy range from 2.03 to 2.08 eV and line widths of 2–5 meV are observed. Furthermore, the radiative HJ states are uniform, and the optical transition energy is controlled by the band gaps of GNRs and GNDs. As these HJs can be synthesized in a large quantity with atomic precision, this finding highlights a route to programmable and deterministic creation of quantum light emitters.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Automated Construction of Artificial Lattice Structures with Designer Electronic States

Manipulating matter with a scanning tunneling microscope (STM) enables the creation of atomically defined artificial structures that host designer quantum states. However, the time-consuming nature of the manipulation process, coupled with the sensitivity of the STM tip, constrains the exploration of diverse configurations and limits the size of the designed features. In this study, we present a reinforcement learning (RL)-based framework for creating artificial structures by spatially manipulating carbon monoxide (CO) molecules on a copper substrate by using the STM tip. The automated workflow combines molecule detection and manipulation, employing deep-learning-based object detection to locate CO molecules and linear assignment algorithms to allocate these molecules to designated target sites. We initially perform molecule maneuvering based on randomized parameter sampling for sample bias, tunneling current set point, and manipulation speed. This data set is then structured into an action trajectory used to train an RL agent. The model is subsequently deployed on the STM for real-time fine-tuning of the manipulation parameters during structure construction. Our approach incorporates path-planning protocols coupled with active drift compensation to enable atomically precise fabrication of structures with significantly reduced human input while realizing larger-scale artificial lattices with the desired electronic properties. Furthermore, using our approach, we demonstrate the automated construction of an extended artificial graphene lattice and confirm the existence of a characteristic Dirac point in its electronic structure. Further challenges regarding the RL-based structural assembly scalability are discussed.

Algorithms↗