Manipulating Copper Dispersion on Ceria for Enhanced Catalysis: A Nanocrystal-Based Atom-Trapping St
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Polyoxometalates (POMs) are molecular metal oxides with distinctive electronic properties that make them promising materials for applications in energy, sensors, and memory devices. One of the most promising methods of tuning the stability, photochromic, redox, and electron-spin properties of POMs is through the substitution of the metal “addenda” atoms that, along with oxygen, constitute their cage-like structures. Because traditional synthesis methods typically produce a distribution of POMs, the isolation and characterization of multimetallic POMs with predetermined stoichiometry remains challenging. The presence of multiple energetically accessible isomers further complicates the experimental characterization and theoretical modeling of multimetallic POMs. Herein, we leverage the distinguishing mass-selection capabilities of ion soft landing to prepare stoichiometrically selected Keggin PMo x W 12-x O 40 3- (x = 0 – 6, 8, 10, and 12) POMs on self-assembled monolayer surfaces free of the solvent molecules and counterions that often confound characterization of complex species at interfaces. The structures of the supported POMs are characterized with atom-by-atom precision using in situ infrared (IR) reflection absorption spectroscopy complemented by detailed density functional theory calculations. Our joint experimental and theoretical results reveal an almost linear shift in the positions of the IR bands towards lower wavenumbers with an increase in the number of lighter molybdenum atoms compared to heavier W atoms in PMoxW 12-x O 40 3- . The theoretical calculations also indicate that numerous isomeric structures may be populated at the experimental conditions and, consequently, contribute to the overall IR spectra. In conclusion, our findings indicate that in addition to the number of substituted addenda atoms and the presence of multiple isomeric structures, interactions with the surface play an important role in determining the IR spectra and structure of supported bimetallic POMs.
We provide the ensemble of fifteen pre-trained graph foundation models (GFMs) for atomistic materials modeling applications. Each one of the fifteen GFMs has been trained on five open-source datasets that (once aggregated) amount to over 154 million atomistic structures, which cover over two-thirds of the natural elements of the periodic table and that comprises a broad set of organic and inorganic compounds. This vast set of atomistic structures comprises ground state configurations that are dynamically stable (i.e., equilibrated structures with atomic forces approximately close to zero values) as well as dynamically unstable structures (i.e., non-equilibrium structures with non-negligible non-zero values of atomic forces). The ensemble of datasets aggregated does NOT include excited states. The datasets have been curated to remove atomistic structures with spectral norm of the force tensor above 100 eV/angstrom. Moreover, a linear term of the energy was computed for each dataset using a linear regression model that uses the chemical concentration of each natural element as regressor. The linear term predicted by the linear regression model has been subtracted from each original energy value to perform a re-alignment of the energy values across different electronic structures approximation theories performed to generate the diverse multi-source, multi-fidelity datasets. The folder "ADIOS_files" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "ADIOS_files" directory contains 6 sub-directories named as follows: - ANI1x-v3.bp - MPTrj-v3.bp - OC2020-20M-v3.bp - OC2020-v3.bp - OC2022-v3.bp - qm7x-v3.bp Each sub-directory contains the pre-processed datasets converted in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used to the development, training, and performance testing of the ensemble go predictive graph foundation models. Each GFM was developed using HydraGNN (https://github.com/ORNL/HydraGNN) as underlying graph neural network (GNN) architecture. The multi-task learning (MTL) capability of HydraGNN was used to simultaneously train the GFMs on labeled values for direct predictions of energy (a total system property of an atomistic structure that measures the chemical stability) and atomic forces (an atomic level property of an atomistic structure that measures the dynamical stability). The hyper parameters of the GFM have been tuned using scalable hyperparameter optimization (HPO) algorithms implemented in the software DeepHyper (https://github.com/deephyper/deephyper). The pre-training of each HPO trial was performed using distributed data parallelism (DDP) to scale the training across 128 compute nodes of the exascale OLCF supercomputer Frontier. Each HPO trial was trained only for 10 epochs and an early stopping was performed to avoid wasting significant computational resources on GNN architectures that were clearly underperforming. For each HPO trial, the 'omnistat' tool developed by (AMD Research - Advanced Micro Device) was used to measure the total energy consumption in kWh. The ensemble of GFMs was obtained by selecting the fifteen best performing HPO trials. Four models have been selected for their clear advantage in accuracy, and these are the GFMs with IDs 229, 156, 147, 260. Additional eleven models have been selected based on judicious balance between accuracy and energy consumption needed for training, and these are the GFMs with IDs 165, 78, 137, 1, 175, 171, 181, 67, 179, 167, 351. Each selected GFM of the ensemble was continued to cumulate a total of at most 30 epochs. In some cases, the total number of epochs actually performed was les than 30 due to two combined factors: (1) the size of the GFM (i.e., the number of model parameters to train) and (2) the total wall-clock time for which the computational resources could be allocated on OLCF-Frontier. The "Ensemble_of_models" directory contains 15 sub-directories named as follows: - gfm_0.229 - gfm_0.156 - gfm_0.147 - gfm_0.260 - gfm_0.165 - gfm_0.78 - gfm_0.137 - gfm_0.1 - gfm_0.175 - gfm_0.171 - gfm_0.181 - gfm_0.67 - gfm_0.179 - gfm_0.167 - gfm_0.351 Each one of these sub-directories refers to one of the fifteen HPO trials that have been selected to continue the pre-training with at most 30 epochs. With each sub-directory associated with a specific HPO trial, the following files can be found: - config.json: file for argument parsing to develop and train an HydraGNN architecture - gfm_0.ID_epoch_N.pk: file with model parameters for HPO ID trial after N epochs of training The ensemble of fifteen GFM architectures was used for (1) ensemble averaging to stabilize the predictions of energy and atomic forces after pre-training for post-processing analysis and (2) ensemble uncertainty quantification (UQ). The code used to develop, pre-train, and load the pre-trained models for post-processing analysis is available on the ORNL-GitHub at the following link: https://github.com/ORNL/HydraGNN/tree/Predictive_GFM_2024
Here, the tuning of catalyst activity via stereoelectronic modulation of the active-site structure remains a grand challenge in heterogeneous catalysis. In homogeneous catalysis, the redox noninnocent ligands can be introduced to organometallic fragments to donate electrons to the metal center and fine-tune the catalytic activity. Analogously, lithium-ion battery materials, such as lithium manganese oxide (LMO), lithium titanium oxides (LTO), etc., can serve as redox noninnocent catalyst support to modulate the electronic structures of the active site via lithiation, hence tuning the catalytic activity of supported active sites. Experimentally, the Ni single-atom site was supported on LiMn 2 O 4 via oxidative grafting and exhibited no catalytic activity toward the hydrogenation of cyclohexene. After introducing additional Li into the catalyst support forming Li 2 Mn 2 O 4 , the Ni single-atom site becomes active, with the catalytic rates increasing as a function of the lithiation for Li/Mn ratios >0.9. In this paper, density functional theory (DFT) calculations are performed to study the Ni site structure via X-ray absorption near edge structure (XANES) simulations and investigate the electronic properties of Ni single-atom site before and after the addition of intercalated lithium in the LMO spinel structure. Furthermore, the study of the reaction mechanism is also carried out to understand the thermodynamically and kinetically favored pathways. XANES simulation suggests that the Ni single-atom site is likely to stay in the Li channel of the spinel support structure and form an octahedral structure. After Li intercalation, the Ni site becomes less positively charged, indicating the partial reduction of the Ni site. The simulated reaction energy profile over the LiMn 2 O 4 support exhibits high-energy barriers (1.07 eV) for the hydrogenation of cyclohexene; however, the Li 2 Mn 2 O 4 support is able to better stabilize low-coordinated ion sites and improve ion mobility, leading to lower overall energy barriers (0.64 eV). The reduced and low-coordinated ion site, thus, can better stabilize the reaction intermediates and promote hydrogenation reaction. Similarly, other transition metal ions (Fe, Co, and Cu) are also considered over the LiMn 2 O 4 and Li 2 Mn 2 O 4 catalyst supports for hydrogenation reaction.
Layered transition metal dichalcogenides (TMDCs) such as MoS 2 , MoSe 2 , and WSe 2 are under intense investigation because they are atomically thin semiconductors with photophysical properties that can be tuned by changing their composition or morphology. Mechanochemical processing has been proposed as a method to obtain alloyed TMDCs in the series Mo 1–x W x S y Se 2–y (x = 0–1; y = 0–2). However, elucidating the chemical transformations occurring at the atomic scale following mechanochemical processing can be challenging because the products are often amorphous or microcrystalline. To address this challenge, we probe TMDC mixing and alloying by using a combination of powder X-ray diffraction, Raman spectroscopy, diffuse reflectance spectroscopy, 77 Se solid-state nuclear magnetic resonance (SSNMR) spectroscopy, and planewave density functional theory (DFT) calculations. The nature of the milling material and reaction atmosphere are shown to be essential factors in limiting the formation of undesired oxide byproducts. We demonstrate acquisition of 77 Se SSNMR spectra using different combinations of Carr-Purcell Meiboom-Gill acquisition (CPMG) pulse sequences, magic angle spinning (MAS), and MAS dynamic nuclear polarization. Further, the combination of SSNMR with the other characterization methods clearly demonstrates that high energy impact ball milling induces molecular level alloying of Mo, W and chalcogen atoms in the family Mo 1–x W x S y Se 2–y . Gauge including projector augmented wave DFT calculations yield accurate 77 Se chemical shift (CS) tensor components. 77 Se SSNMR spectroscopy was also applied to study the structure of WSe 2 nanocrystals intercalated with ethylenediamine. The intercalated WSe 2 nanocrystals exhibit a more positive isotropic 77 Se CS as compared to bulk WSe 2 , however, the 77 Se CS anisotropy is the same, confirming the WSe 2 layers have a similar structure as in their bulk counterparts.
Since the introduction of lead halide perovskites, tremendous progress has been made regarding their stability, reproducibility and durability. However, one of the issues that remains is related to the interfacial atomic structure arrangement and structure-property relationship under optical and electrical stimuli. In this critical review, we highlight the recent progress using scanning tunneling microscopy (STM) to understand the nanoscale properties and dynamic processes occurring in these halide perovskite materials. STM is known to be a very challenging technique, which is reflected by the low number of relevant publications in the last years. These initial reports mirror the unique potential of STM to give Ångstrom-scale insight into the (opto)-electronic properties, morphology and underlying electronic structure and provide a path toward harnessing the full potential of these materials. However, care must be taken to understand the effects of the perturbations caused by STM and tailor the measurement conditions accordingly.
In situ and operando (scanning) transmission electron microscopy [(S)TEM] is a powerful characterization technique that uses imaging, diffraction, and spectroscopy to gain nano-to-atomic scale insights into the structure–property relationships in materials. This technique is both customizable and complex because many factors impact the ability to collect structural, compositional, and bonding information from a sample during environmental exposure or under application of an external stimulus. In the past two decades, in situ and operando (S)TEM methods have diversified and grown to encompass additional capabilities, higher degrees of precision, dynamic tracking abilities, enhanced reproducibility, and improved analytical tools. Much of this growth has been shared through the community and within commercialized products that enable rapid adoption and training in this approach. This tutorial aims to serve as a guide for students, collaborators, and nonspecialists to learn the important factors that impact the success of in situ and operando (S)TEM experiments and assess the value of the results obtained. As this is not a step-by-step guide, readers are encouraged to seek out the many comprehensive resources available for gaining a deeper understanding of in situ and operando (S)TEM methods, property measurements, data acquisition, reproducibility, and data analytics.
Abstract Complex concentrated alloys (CCAs) are materials comprising three or more elements in similar proportions and possessing structural but no chemical long-range order. Fascination with CCAs has grown over the last 20 years and to date, CCAs have opened a new materials design paradigm and horizon for discovery of materials to meet the demands of applications in aggressive environments. Understanding the fundamental mechanisms controlling their response, however, is challenging due to the chemical and structural variations that wildly fluctuate over fine atomic and nanoscales. This issue focuses on the experimental, computational, and theoretical investigations that aim to uncover phenomena and processes determining the structure, kinetics, mechanics, or deformation mechanisms in CCAs at the atomic scale. At the atomic scale at which they operate, chemical short-range ordering can be influential. This issue further addresses the capabilities, as well as the debatable need, to characterize, predict, and relate short-range ordering to material performance. Collectively, the articles in this issue highlight the insights, understanding, and experimental and computational tools that attempt to create property-tunable CCAs “from the atom up” by treating short-range ordering and engineering atomic-scale mechanisms. Graphical abstract
Platinum exhibits desirable catalytic properties, but it is scarce and expensive. Optimizing its use in key applications such as emission control catalysis is important to reduce our reliance on such a rare element. Supported Pt nanoparticles (NPs) used in emission control systems deactivate over time because of particle growth in sintering processes. Here, in this work, we shed light on the stability against sintering of Pt NPs supported on and encapsulated in Al 2 O 3 using a combination of nanocrystal catalysts and atomic layer deposition (ALD) techniques. We find that small amounts of alumina overlayers created by ALD on preformed Pt NPs can stabilize supported Pt catalysts, significantly reducing deactivation caused by sintering, as previously observed by others. Combining theoretical and experimental insights, we correlate this behavior to the decreased propensity of oxidized Pt species to undergo Ostwald ripening phenomena because of the physical barrier imposed by the alumina overlayers. Furthermore, we find that highly stable catalysts can present an abundance of under-coordinated Pt sites after restructuring of both Pt particles and alumina overlayers at a high temperature (800 °C) in C 3 H 6 oxidation conditions. The enhanced stability significantly improves the Pt utilization efficiency after accelerated aging treatments, with encapsulated Pt catalysts reaching reaction rates more than two times greater than those of a control supported Pt catalyst.
Using compressive mechanical forces, such as pressure, to induce crystallographic phase transitions and mesostructural changes while modulating material properties in nanoparticles (NPs) is a unique way to discover new phase behaviors, create novel nanostructures, and study emerging properties that are difficult to achieve under conventional conditions. In recent decades, NPs of a plethora of chemical compositions, sizes, shapes, surface ligands, and self-assembled mesostructures have been studied under pressure by in-situ scattering and/or spectroscopy techniques. As a result, the fundamental knowledge of pressure–structure–property relationships has been significantly improved, leading to a better understanding of the design guidelines for nanomaterial synthesis. In the present review, we discuss experimental progress in NP high-pressure research conducted primarily over roughly the past four years on semiconductor NPs, metal and metal oxide NPs, and perovskite NPs. We focus on the pressure-induced behaviors of NPs at both the atomic- and mesoscales, inorganic NP property changes upon compression, and the structural and property transitions of perovskite NPs under pressure. We further discuss in depth progress on molecular modeling, including simulations of ligand behavior, phase-change chalcogenides, layered transition metal dichalcogenides, boron nitride, and inorganic and hybrid organic–inorganic perovskites NPs. These models now provide both mechanistic explanations of experimental observations and predictive guidelines for future experimental design. Here, we conclude with a summary and our insights on future directions for exploration of nanomaterial phase transition, coupling, growth, and nanoelectronic and photonic properties.
Abstract Chemical short-range-order has been widely noticed to dictate the electrochemical properties of Li-excess cation-disordered rocksalt oxides, a class of cathode based on earth abundant elements for next-generation high-energy-density batteries. Existence of short-range-order is normally evidenced by a diffused intensity pattern in reciprocal space, however, derivation of local atomic arrangements of short-range-order in real space is hardly possible. Here, by a combination of aberration-corrected scanning transmission electron microscopy, electron diffraction, and cluster-expansion Monte Carlo simulations, we reveal the short-range-order is a convolution of three basic types: tetrahedron, octahedron, and cube. We discover that short-range-order directly correlates with Li percolation channels, which correspondingly affects Li transport behavior. We further demonstrate that short-range-order can be effectively manipulated by anion doping or post-synthesis thermal treatment, creating new avenues for tailoring the electrochemical properties. Our results provide fundamental insights for decoding the complex relationship between local chemical ordering and properties of crystalline compounds.
Here, we present comprehensive phononic and charge density wave properties (CDW) of rare-earth van der Waals tritellurides through temperature dependent angle-resolved Raman spectroscopy measurements. All the possible rare-earth tritellurides (RTe3) ranging from R = La–Nd, Sm, Gd–Tm were synthesized through a chemical vapor transport technique to achieve high quality crystals with excellent CDW characteristics. Raman spectroscopy studies successfully identify the emergence of the CDW state and transition temperature (TCDW), which offers a non-destructive method to identify their CDW response with micron spatial resolution. Temperature dependent Raman measurements further correlate how the atomic mass of metal cations and the resulting chemical pressure influence its CDW properties and offer detailed insight into the strength of CDW amplitude mode-phonon coupling during the CDW transition. Angle-resolved Raman measurements offer the first insights into the CDW-phonon symmetry interplay by monitoring the change in the symmetry of phonon mode across the CDW transition. Overall results introduce the library of RTe3 CDW materials and establish their characteristics through the non-destructive angle-resolved Raman spectroscopy technique.
CONSPECTUS: Photoelectrochemical water-splitting is a promising and sustainable way to store the energy of the sun in chemical bonds and use it to produce hydrogen gas, a clean fuel. The key components in photoelectrochemical cells (PECs) are photoelectrodes, including a photocathode that reduces water to hydrogen gas and a photoanode that oxidizes water to oxygen gas. Materials used in photoelectrodes for PECs must effectively absorb sunlight, yield photogenerated carriers, and exhibit electronic properties that enable the efficient shuttling of carriers to the surface to participate in relevant water-splitting reactions. Discovering and understanding the key characteristics of optimal photoelectrode materials is paramount to the realization of PEC technologies. Oxide-based photoelectrodes can satisfy many of these materials requirements, including stability in aqueous environments, band edges with reasonable alignment with the redox potentials for water splitting, and ease of synthesis. However, oxide photoelectrodes generally suffer from poor charge transport properties and considerable bulk electron-hole separation, and they have relatively large band gaps. Numerous strategies have been proposed to improve these aspects and understand how these improvements are reflected in the photoelectrochemical performance. Unfortunately, the structural and compositional complexity of multinary oxides accompanied by the inherent complexity of photoelectrochemical processes makes it challenging to understand the individual effects of composition, structure, and defects in the bulk and on the surface on a material's photoelectrochemical properties. The integration of experiment and theory has great potential to increase our atomic-level understanding of structure-composition-property relationships in oxide photoelectrodes. In this Account, we describe how integrating experiment and theory is beneficial for achieving scientific insights at the microscopic scale. We highlight studies focused on understanding the role of (i) bulk composition via solid-state solutions, intercalation, and comparison with isoelectronic compounds, (ii) dopants for both the anion and cation and their interactions with oxygen vacancies, and (iii) surface/interface structure in the photocurrent generation and photoelectrochemical performance in oxide photoelectrodes. In each instance, we outline strategies and considerations for integrating experiment and theory and describe how this integration led to valuable insights and new directions in uncovering structure-composition-property relationships. Our aim is to demonstrate the unique value of combining experiment and theory in studying photoelectrodes and to encourage the continued effort to bring experiment and theory in closer step with each other.
Understanding the complex temporal and spatial correlations of ions in disordered perovskite oxides is critical to rationalize their functional properties. Here, in this study, we provide new insights into the longstanding controversy regarding the off-centering of transition metal ions in the archetypal ferroelectric alloy KTa 1-x Nb x O 3 (KTN). By mapping the full energy (E) and wavevector (Q) dependence of the dynamical structure factor S(Q, E) using neutron scattering, and rationalizing our observations with atomistic simulations leveraging machine learning, we fully resolve the static vs dynamic nature of diffuse scattering sheets, as well as their composition (x) and temperature dependence. Our first-principles simulations, extended with machine-learning molecular dynamics, reproduce both inelastic neutron spectra and diffuse features, and establish how dynamically-correlated transition metal off-centerings couple to phonons, unifying local and collective viewpoints. This study sheds new light into an exemplary ferroelectric systems and shows the importance of mapping the full S(Q, E) to reveal critical spatio-temporal correlations of atomic disorder from which functional properties emerge.
Alloy partitioning during heat treatment in a lightweight precipitation hardened steel was investigated using transmission electron microscopy and atom probe tomography. The mechanical properties are discussed as a function of the effect of solution treatment temperature and aging time, giving rise to variations in chemical modulation. A wrought lightweight steel alloy with a nominal composition of Fe-30Mn-9Al-1Si-1C-0.5Mo (wt. %) was solution-treated between 1173–1273 K and aged at 773 K. Lower solution treatment temperatures retained a finer grain size and accelerated age hardening response that also produced an improved work hardening behavior with a tensile strength of -1460 MPa at 0.4 true strain. Atom probe tomography indicated these conditions also had reduced modulation in the Si and Al content due to the reduced aging time preventing silicon from diffusing out of the κ-carbide into the austenite. This work provides the framework for heat-treating lightweight, age hardenable steels with high strength and improved energy absorption.
CeTe 3 is a 2-dimensional (2D) Van der Waals (VdW) material with incommensurate charge density waves (CDW), extremely high transition temperature (T CDW ), and a large momentum-dependent CDW gap that leaves a significant portion of the Fermi surface intact. It is also considered to be a weak Kondo system, a property unexpected for a material with incommensurate CDW, where each atomic site is slightly different. Here, we study the properties of the CDW state in several RTe3 (R is rare earth) materials and examine the hybridization of itinerant states with the localized Ce 4f multiplet in CeTe 3 by using angle resolved photoemission spectroscopy. We find that the renormalization of the itinerant states originating from the hybridization with the deeper localized 4f states at −260 meV is k−dependent and extends to the Fermi level. As these localized states are far from the Fermi level, the observed hybridization affects the effective masses only marginally and does not lead to heavy fermions. However, since the same renormalizing mechanism normally leads to the heavy fermion physics when the localized 4f states are near the Fermi level, our observation of its strong k−dependence suggests that this could be the reason for discrepancy between the heavy masses in specific heat and light ones in Shubnikov de Haas oscillations, often observed in heavy fermions.
It is easy to miss the scientific implications of our recent work on Triboelectricity. Everyone knows that rubbing and contact can produce static electricity; less appreciated is that the thermodynamic driver has been an open question since static electricity was first observed by Thales of Miletus around 585 BC. People think they understand it, for instance one common explanation that can still be found in the current literature is that differences in the work function drives charge transfer, often called the Volta-Helmholtz hypothesis. As summarized in 1967 by Harper, this fails to explain many experimental observations, for instance that charging can occur when two pieces of the same material are rubbed against each other. We are the first to place triboelectricity on a solid foundation rooted in quantum mechanics – the flexoelectric effect. We were able to explain a significant number of previously unexplained phenomena: 1) Bipolar tribocurrents associated with stick-slip, due to the change in sign of the strain gradients. 2) A one-third power scaling of tribocurrents with indentation force. 3) Tribocharging when two identical materials are used, these being due to local variations in the asperities so there are usually local potential differences. 4) Inhomogeneous charging of insulators, related to the statistical nature of asperities. 5) An experimentally observed reversal in the sign of charge transfer for negative and positive curvature, which is related to a change in the sign of the strain gradient. Exploiting our DOE prior funded work on flexoelectricity, we obtained semi-quantitative matching to existing experimental measurements of the surface charge in triboelectric experiments. The work has been well received in the literature. The work has been the focus of a number of popular science press articles, and also formed the basis for a Podcast for children 6-10 “The Rise and Fall of Static Man” posted in December 2019 by NPR as part of their “Wow in the World” series. I was also briefly interviewed by the Chicago PBS station in January 2020. This work are significant for a wide range of energy applications; to quote from an independent source: "Triboelectric power has plenty of potential, says Wenzhuo Wu, an assistant professor of engineering at Purdue. If the basics of static electricity are better understood, we could maximize the efficiency of wind or wave power generators, Wu says. The body's own movement could be used to power internal medical devices. Imagine being able to create a roof shaped to harness the power of a raindrop — the friction of the rain passing over the surface — to generate triboelectricity, powering the building below it." This is the start of new science, some of which we already partially understand such as the role of band bending in charge transfer. We need to understand charge transfer combining elasticity, quantum mechanics, band bending and defect states. These directly involve several of the DOE Grand Challenges: "How do we control material processes at the level of electrons? How do remarkable properties of matter emerge from complex correlations of the atomic or electronic constituents and how can we control these properties? How do we characterize and control matter away—especially very far away— from equilibrium?" I will argue that this work truly falls into the class of disruptive science; it is not just a simple extension, linear science. Not everyone will accept the approach. Since we explain far more about triboelectricity than anyone before, the preponderance of evidence supports the model. The feedback I have received is that many agree with the work, to quote: "The model makes sense, says Michael McAlpine, a professor of engineering at the University of Minnesota. "It's such a simple explanation, I was surprised I didn't put my finger on that," McAlpine says." The proposal received strong reviews. It was also publicized on the Department of Energy Web Site.
Abstract Materials keeping thickness in atomic scale but extending primarily in lateral dimensions offer properties attractive for many emerging applications. However, compared to crystalline counterparts, synthesis of atomically thin films in the highly disordered amorphous form, which avoids nonuniformity and defects associated with grain boundaries, is challenging due to their metastable nature. Here we present a scalable and solution-based strategy to prepare large-area, freestanding quasi-2D amorphous carbon nanomembranes with predominant sp 2 bonding and thickness down to 1–2 atomic layers, from coal-derived carbon dots as precursors. These atomically thin amorphous carbon films are mechanically strong with modulus of 400 ± 100 GPa and demonstrate robust dielectric properties with high dielectric strength above 20 MV cm −1 and low leakage current density below 10 −4 A cm −2 through a scaled thickness of three-atomic layers. They can be implemented as solution-deposited ultrathin gate dielectrics in transistors or ion-transport media in memristors, enabling exceptional device performance and spatiotemporal uniformity.