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  1. First principles band structure of interacting phosphorus and boron/aluminum δ-doped layers in silicon

    Silicon can be heavily doped with phosphorus in a single atomic layer (a δ layer), significantly altering the electronic structure of the conduction bands within the material. Recent progress has also made it possible to further dope silicon with acceptor-based δ layers using either boron or aluminum, making it feasible to create devices with interacting δ layers with opposite polarity. Using density functional theory, we calculate the electronic structure of a phosphorus-based δ layer interacting with a boron or aluminum δ layer, varying the distances between the δ layers. At separations 1 nm and smaller, the dopant potentials overlap andmore » largely cancel each other out, leading to an electronic structure closely mimicking intrinsic silicon. At separations greater than 1 nm, the two δ layers behave independently of one another, with an equivalent electronic structure to a p–n diode with an intrinsic layer taking the place of the depletion region. One mechanism for charge transfer between δ layers at larger distances could be tunneling, where we see a tunneling probability exceeding what would be seen for a standard silicon 1.1 eV triangular barrier, indicating that the interaction between delta layers may enhance tunneling compared to a traditional junction.« less
  2. First-Principles Dissociation Pathways of BCl3 on the Si(100)-2 × 1 Surface

    BCl3 is a promising acceptor precursor for atomic-precision δ-doping of silicon, as it has been observed to rapidly dissociate into boron doped into the silicon surface and surface chlorine, which can be removed upon annealing. The chemical pathway and the resulting kinetics, through which BCl3 adsorbs and dissociates on silicon, however, have only been partially explained. Here, in this work, we use density functional theory to expand the dissociation reactions of BCl3 to include reactions that take place across multiple silicon dimer rows and reactions which end in a bare B atom either at the surface, substituted for a surfacemore » silicon, or in a subsurface position. We further simulate the resulting scanning tunneling microscopy images for each of these BClx dissociation fragments, demonstrating that they often display distinct features that may allow for relatively confident experimental identification. Finally, we input the full dissociation pathway for BCl3 into a kinetic Monte Carlo model, which simulates realistic reaction pathways as a function of environmental conditions, such as the pressure and temperature of dosing. We find that BCl2 is broadly dominant at low temperatures, while high temperatures and ample space on the silicon surface for dissociation encourage the formation of bridging BCl fragments and B substitutions on the surface. This work provides the chemical mechanisms for understanding atomic-precision doping of Si with B, enabling a number of relevant quantum applications, such as bipolar nanoelectronics, acceptor-based qubits, and superconducting Si.« less
  3. How transparent is graphene? A surface science perspective on remote epitaxy

    Remote epitaxy is the synthesis of a single crystalline film on a graphene-covered substrate, where the film adopts epitaxial registry to the substrate as if the graphene is transparent. Despite many exciting applications for flexible electronics, strain engineering, and heterogeneous integration, an understanding of the fundamental synthesis mechanisms remains elusive. Here we offer a perspective on the synthesis mechanisms, focusing on the foundational assumption of graphene transparency. We identify challenges for quantifying the strength of the remote substrate potential that permeates through graphene, and propose Fourier and beating analysis as a bias-free method for decomposing the lattice potential contributions frommore » the substrate, from graphene, and from surface reconstructions, each at different frequencies. We highlight the importance of graphene-induced reconstructions on epitaxial templating, drawing comparison to moiré epitaxy. We highlight the role of the remote potential in tuning surface diffusion and adatom kinetics on graphene, which are crucial for navigating the competition between remote epitaxy and defect-seeded mechanisms like pinhole epitaxy. In light of this weak remote potential, we re-evaluate the current state-of-the-art experimental evidence, highlighting why it remains challenging to experimentally validate a ‘remote’ epitaxy mechanism that cannot be explained by alternatives, such as pinhole-seeded epitaxy or serial van der Waals epitaxy. We end with one experimental example that, to out knowledge, cannot be explained by competing mechanisms: a different long-range epitaxial relationship for GdPtSb films grown on graphene/sapphire, compared to direct epitaxy on sapphire. We suggest for future experiments that directly measure the remote potential and impact of tuneable growth kinetics.« less
  4. Optimizing temperature distributions for training neural quantum states using parallel tempering

    Parametrized artificial neural networks (ANNs) can be very expressive ansatzes for variational algorithms, reaching state-of-the-art energies on many quantum many-body Hamiltonians. Nevertheless, the training of the ANN can be slow and stymied by the presence of local minima in the parameter landscape. One approach to mitigate this issue is to use parallel tempering methods, and in this work, we focus on the role played by the temperature distribution of the parallel tempering replicas. Using an adaptive method that adjusts the temperatures in order to equate the exchange probability between neighboring replicas, we show that this temperature optimization can significantly increasemore » the success rate of the variational algorithm with negligible computational cost by eliminating bottlenecks in the replicas' random walk. Furthermore, we demonstrate this using two different neural networks, a restricted Boltzmann machine and a feedforward network, which we use to study a toy problem based on a permutation invariant Hamiltonian with a pernicious local minimum and the 𝐽1−𝐽2 model on a rectangular lattice.« less
  5. First-principles investigation of high capacity, rechargeable CFx cathode batteries based on graphdiyne and “holey” graphene carbon allotropes

    Batteries composed of CFx cathodes have high theoretical specific capacities (>860 mA h g-1). Attempts at realizing such batteries coupled with Li anodes have failed to deliver on this promise, however, due to a discharge voltage plateau below the theoretical maximum lowering the realized energy density and difficulties with recharging the system. Here, in this study, we use first-principles calculations to investigate novel carbon allotropes for these battery systems: graphdiyne and “holey” graphene. We first identify stable flourination structures and calculate their band gaps. We demonstrate that the holes in these carbon allotropes can induce the formation of an amorphousmore » LiF network within the carbon and that this formation may, in fact, be kinetically favored. For structures where amorphous LiF forms within the carbon, we predict it is easier to recharge and higher discharge voltages can be achieved. If the LiF forms outside the carbon product, however, it will be crystalline in form and lead to lower discharge voltages and more difficulty in recharging the systems. Finally, we simulate XPS spectra of representative cases, demonstrating an experimental pathway for determining the reaction pathway of these systems. Our work suggests CFx allotropes with holes in them as potential targets for high capacity, rechargeable cathodes for Li batteries, provided they lead to the formation of amorphous LiF within the C structure.« less
  6. Direct Observation of 2DEG States in Shallow Si:Sb δ-Layers

    We investigate the electronic structure of high-density layers of Sb dopants in a silicon host, so-called Si:Sb δ-layers. We show that, in spite of the known challenges in producing highly confined Sb δ-layers, sufficient confinement is created such that the lowest conduction band states (Γ states, studied in depth in other silicon δ-layers), become occupied and can be observed using angle-resolved photoemission spectroscopy. The electronic structure of the Si:Sb δ-layers closely resembles that of Si:P systems, where the observed conduction band is near-parabolic and slightly anisotropic in the k plane. The observed Γ state extends ∼1 nm in the out-of-planemore » direction, which is slightly wider than the 1/3 monolayer thick dopant distribution. This is caused by a small segregation of the dopant layer, which is nevertheless minimal when comparing with earlier published attempts. Our results serve to demonstrate that Sb is still a feasible dopant alternative for use in the semiconductor δ-layer platform, providing similar electronic functionality to Si:P systems. Additionally, it has the advantages of being less expensive, more controllable, safer to handle, and more compatible with industrial patterning techniques. Si:Sb is therefore a viable platform for emerging quantum device applications.« less
  7. Voltage-Dependent First-Principles Barriers to Li Transport within Li-Ion Battery Solid Electrolyte Interphases

    Charging a Li-ion battery requires Li-ion transport between the cathode and the anode. This Li-ion transport is dependent on (among other factors) the electrostatic environment that the ion encounters within the solid electrolyte interphase (SEI), which separates the anode from the surrounding electrolyte. A previous first-principles work has illuminated the reaction barriers through likely atomistic SEI environments but has had difficulty accurately reflecting the larger electrostatic potential landscape that an ion encounters moving through the SEI. In this work, we apply the recently developed quantum continuum approximation (QCA) technique to provide an equilibrium electronic potentiostat for first-principles interface calculations. Usingmore » QCA, we calculate the potential barrier for Li-ion transport through LiF, Li2O, and Li2CO3 SEIs along with LiF–LiF and LiF–Li2O grain boundaries, all paired with Li metal anodes. Here, we demonstrate that the SEI potential barrier is dependent on the electrochemical potentials of the anode in each system. Finally, we use these techniques to estimate the change in the diffusion barrier for a Li ion moving in a LiF SEI as a function of the anode potential. We find that properly accounting for interface and electronic voltage effects significantly lowers reaction barriers compared with previous literature results.« less
  8. Electronic structure of boron and aluminum δ-doped layers in silicon

    Recent work on atomic-precision dopant incorporation technologies has led to the creation of both boron and aluminum δ-doped layers in silicon with densities above the solid solubility limit. For this study, we use density functional theory to predict the band structure and effective mass values of such δ layers, first modeling them as ordered supercells. Structural relaxation is found to have a significant impact on the impurity band energies and effective masses of the boron layers, but not the aluminum layers. However, disorder in the δ layers is found to lead to a significant flattening of the bands in bothmore » cases. We calculate the local density of states and doping potential for these δ-doped layers, demonstrating that their influence is highly localized with spatial extents at most 4 nm. We conclude that acceptor δ-doped layers exhibit different electronic structure features dependent on both the dopant atom and spatial ordering. This suggests prospects for controlling the electronic properties of these layers if the local details of the incorporation chemistry can be fine-tuned.« less
  9. Quantum-inspired tempering for ground state approximation using artificial neural networks

    A large body of work has demonstrated that parameterized artificial neural networks (ANNs) can efficiently describe ground states of numerous interesting quantum many-body Hamiltonians. However, the standard variational algorithms used to update or train the ANN parameters can get trapped in local minima, especially for frustrated systems and even if the representation is sufficiently expressive. We propose a parallel tempering method that facilitates escape from such local minima. This methods involves training multiple ANNs independently, with each simulation governed by a Hamiltonian with a different "driver" strength, in analogy to quantum parallel tempering, and it incorporates an update step intomore » the training that allows for the exchange of neighboring ANN configurations. We study instances from two classes of Hamiltonians to demonstrate the utility of our approach using Restricted Boltzmann Machines as our parameterized ANN. The first instance is based on a permutation-invariant Hamiltonian whose landscape stymies the standard training algorithm by drawing it increasingly to a false local minimum. The second instance is four hydrogen atoms arranged in a rectangle, which is an instance of the second quantized electronic structure Hamiltonian discretized using Gaussian basis functions. We study this problem in a minimal basis set, which exhibits false minima that can trap the standard variational algorithm despite the problem’s small size. We show that augmenting the training with quantum parallel tempering becomes useful to finding good approximations to the ground states of these problem instances.« less
  10. Voltage-Dependent First-Principles Simulation of Insertion of Chloride Ions into Al/Al2O3 Interfaces Using the Quantum Continuum Approximation

    Experiments have shown that pitting corrosion can develop in aluminum surfaces at potentials > − 0.5 V relative to the standard hydrogen electrode (SHE). Until recently, the onset of pitting corrosion in aluminum has not been rigorously explored at an atomistic scale because of the difficulty of incorporating a voltage into density functional theory (DFT) calculations. We introduce the Quantum Continuum Approximation (QCA) which self-consistently couples explicit DFT calculations of the metal-insulator and insulator-solution interfaces to continuum Poisson-Boltzmann electrostatic distributions describing the bulk of the insulating region. By decreasing the number of atoms necessary to explicitly simulate with DFT bymore » an order of magnitude, QCA makes the first-principles prediction of the voltage of realistic electrochemical interfaces feasible. After developing this technique, we apply QCA to predict the formation energy of chloride atoms inserting into oxygen vacancies in Al(111)/α-Al2O3 (0001) interfaces as a function of applied voltage. We predict that chloride insertion is only favorable in systems with a grain boundary in the Al2O3 for voltages > − 0.2 V (SHE). Here our results roughly agree with the experimentally demonstrated onset of corrosion, demonstrating QCA's utility in modeling realistic electrochemical systems at reasonable computational cost.« less
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