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Parameterized 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 increase the success rate of the variational algorithm with negligible computational cost by eliminating bottlenecks in the replicas' random walk. 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.

We investigate the electronic structure of high-density layers of Sb dopants in a silicon host, so-called Si:Sb $\delta$-layers. We show that, in spite of the known challenges in producing highly confined Sb $\delta$-layers, sufficient confinement is created such that the lowest conduction band states ($\Gamma$ states, studied in depth in other silicon $\delta$-layers), become occupied and can be observed using angle-resolved photoemission spectroscopy. The electronic structure of the Si:Sb $\delta$-layers closely resembles that of Si:P systems, where the observed conduction band is near-parabolic and slightly anisotropic in the $\mathbf{k}_\parallel$ plane. The observed $\Gamma$ state extends ~ 1 nm in the out-of-plane 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 $\delta$-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.

Charging a Li ion battery requires Li ion transport between the cathode and the anode. This Li ion transport is dependent upon (among other factors) the electrostatic environment the ion encounters within the Solid Electrolyte Interphase (SEI), which separates the anode from the surrounding electrolyte. 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. Using QCA, we calculate the potential barrier for Li ion transport through LiF, Li$_2$O, and Li$_2$CO$_3$ SEIs along with LiF-LiF, and LiF-Li$_2$O grain boundaries, all paired with Li metal anodes. We demonstrate that the SEI potential barrier is dependent on the anode electrochemical potentials 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 anode potential. We find that properly accounting for interface and electronic voltage effects significantly lowers reaction barriers compared to previous literature results., Comment: 30 pages, 9 figures

Recent work on atomic-precision dopant incorporation technologies has led to the creation of both boron and aluminum $\delta$-doped layers in silicon with densities above the solid solubility limit. We use density functional theory to predict the band structure and effective mass values of such $\delta$ 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 $\delta$ layers is found to lead to significant flattening of the bands in both cases. We calculate the local density of states and doping potential for these $\delta$-doped layers, demonstrating that their influence is highly localized with spatial extents at most 4 nm. We conclude that acceptor $\delta$-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., Comment: Main text 8 pages, 6 figures + Appendices 3 pages, 2 figures

Oxides containing metals or metalloids from the {\it p}-block of the periodic table ({\it e.g.}, In, Sn, Sb, Pb, Bi) are of technological interest as transparent conductors and light absorbers for solar energy conversion due to the tunability of their electronic conductivity and optical absorption. Comparatively, these oxides have found limited applications in hydrogen photoelectrolysis primarily due to their high electronegativity, which impedes electron transfer for reducing protons into hydrogen. We have shown recently that inserting {\it s}-block cations into {\it p}-block metal oxides is effective at lowering electronegativities while affording further control of band gaps. Here, we explain the origins of this dual tunability by demonstrating the mediator role of {\it s}-block cations in modulating orbital hybridization while not contributing to frontier electronic states. From this result, we carry out a comprehensive computational study of 109 ternary oxides of {\it s}- and {\it p}-block metal elements as candidate photocatalysts for solar hydrogen generation. We downselect the most desirable materials using band gaps and band edges obtained from Hubbard-corrected density-functional theory with Hubbard parameters computed entirely from first principles, evaluate the stability of these oxides in aqueous conditions, and characterize experimentally four of the remaining materials, synthesized with high phase uniformity, to validate and further develop the computational models. We thus propose nine oxide semiconductors, including CsIn$_3$O$_5$, Sr$_2$In$_2$O$_5$, and KSbO$_2$ which, to the extent of our literature review, have not been previously considered as water-splitting photocatalysts., Comment: 14 pages, 5 figures, 1 supplemental material

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 by 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)/$\alpha$-Al$_2$O$_3$ (0001) interfaces as a function of applied voltage. We predict that chloride insertion is only favorable in systems with a grain boundary in the Al$_2$O$_3$ for voltages $> -0.2$ V (SHE). Our results roughly agree with the experimentally demonstrated onset of corrosion, demonstrating QCA's utility in modeling realistic electrochemical systems at reasonable computational cost., Comment: 20 pages, 6 figures

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 into 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., Comment: 13 pages, 6 figures. v2: updated Figs. 3, 4, and 5. v3. included two new QPT schemes. Updated format to SciPost format. 30 pages, 11 figures. v4. Fixed typo in Eqt. 10 and minor correction in Conclusion. 30 pages, 11 figures. Submission to SciPost

Atomic-precision advanced manufacturing enables the placement of dopant atoms within $\pm$1 lattice site in crystalline Si. However, it has recently been shown that reaction kinetics can introduce uncertainty in whether a single donor will incorporate at all in a minimal 3-dimer lithographic window. In this work, we explore the combined impact of lithographic variation and stochastic kinetics on P incorporation as the size of such a window is increased. We augment a kinetic model for PH$_3$ dissociation leading to P incorporation on Si(100)-2$\times$1 to include barriers for reactions across distinct dimer rows. Using this model, we demonstrate that even for a window consisting of 2$\times$3 silicon dimers, the probability that at least one donor incorporates is nearly unity. We also examine the impact of size of the lithographic window, finding that the incorporation fraction saturates to $\delta$-layer like coverage as the circumference-to-area ratio approaches zero. We predict that this incorporation fraction depends strongly on the dosage of the precursor, and that the standard deviation of the number of incorporations scales as $\sim \sqrt{n}$, as would be expected for a series of largely independent incorporation events. Finally, we characterize an array of experimentally prepared multi-donor lithographic windows and use our kinetic model to study variability due to the observed lithographic roughness, predicting a negligible impact on incorporation statistics. We find good agreement between our model and the inferred incorporation in these windows from scanning tunneling microscope measurements, indicating the robustness of atomic-precision advanced manufacturing to errors in patterning for multi-donor patches., Comment: Main text 24 pages, 5 figures + Appendecies 8 pages, 3 figures

BCl$_3$ is a promising candidate for atomic-precision acceptor doping in Si, but optimizing the electrical properties of structures created with this technique requires a detailed understanding of adsorption and dissociation pathways for this precursor. Here, we use density functional theory and scanning tunneling microscopy (STM) to identify and explore these pathways for BCl$_3$ on Si(100) at different annealing temperatures. We demonstrate that BCl$_3$ adsorbs selectively without a reaction barrier, and subsequently dissociates relatively easily with reaction barriers $\approx$1 eV. Using this dissociation pathway, we parameterize a Kinetic Monte Carlo model to predict B incorporation rates as a function of dosing conditions. STM is used to image BCl$_{3}$ adsorbates, identifying several surface configurations and tracking the change in their distribution as a function of the annealing temperature, matching predictions of the kinetic model well. This straightforward pathway for atomic-precision acceptor doping helps enable a wide range of applications including bipolar nanoelectronics, acceptor-based qubits, and superconducting Si., Comment: 20 pages, 5 figures, Main text + supporting info

Stochastic incorporation kinetics can be a limiting factor in the scalability of semiconductor fabrication technologies using atomic-precision techniques. While these technologies have recently been extended from donors to acceptors, the extent to which kinetics will impact single-acceptor incorporation has yet to be assessed. We develop and apply an atomistic model for the single-acceptor incorporation rates of several recently demonstrated precursor molecules: diborane (B$_2$H$_6$), boron trichloride (BCl$_3$), and aluminum trichloride in both monomer (AlCl$_3$) and dimer forms (Al$_2$Cl$_6$), to identify the acceptor precursor and dosing conditions most likely to yield deterministic incorporation. While all three precursors can achieve single-acceptor incorporation, we predict that diborane is unlikely to achieve deterministic incorporation, boron trichloride can achieve deterministic incorporation with modest heating (50 $^{\circ}$C), and aluminum trichloride can achieve deterministic incorporation at room temperature. We conclude that both boron and aluminum trichloride are promising precursors for atomic-precision single-acceptor applications, with the potential to enable the reliable production of large arrays of single-atom quantum devices., Comment: 10 pages, 5 figures

Scanning tunneling microscope lithography can be used to create nanoelectronic devices in which dopant atoms are precisely positioned in a Si lattice within $\sim$1 nm of a target position. This exquisite precision is promising for realizing various quantum technologies. However, a potentially impactful form of disorder is due to incorporation kinetics, in which the number of P atoms that incorporate into a single lithographic window is manifestly uncertain. We present experimental results indicating that the likelihood of incorporating into an ideally written three-dimer single-donor window is $63 \pm 10\%$ for room-temperature dosing, and corroborate these results with a model for the incorporation kinetics. Nevertheless, further analysis of this model suggests conditions that might raise the incorporation rate to near-deterministic levels. We simulate bias spectroscopy on a chain of comparable dimensions to the array in our yield study, indicating that such an experiment may help confirm the inferred incorporation rate., Comment: 20 pages, 13 figures

The production of hydrogen fuels, via water splitting, is of practical relevance for meeting global energy needs and mitigating the environmental consequences of fossil-fuel-based transportation. Water photoelectrolysis has been proposed as a viable approach for generating hydrogen, provided that stable and inexpensive photocatalysts with conversion efficiencies over 10% can be discovered, synthesized at scale, and successfully deployed (Pinaud et al., Energy Environ. Sci., 2013, 6, 1983). While a number of first-principles studies have focused on the data-driven discovery of photocatalysts, in the absence of systematic experimental validation, the success rate of these predictions may be limited. We address this problem by developing a screening procedure with co-validation between experiment and theory to expedite the synthesis, characterization, and testing of the computationally predicted, most desirable materials. Starting with 70,150 compounds in the Materials Project database, the proposed protocol yielded 71 candidate photocatalysts, 11 of which were synthesized as single-phase materials. Experiments confirmed hydrogen generation and favorable band alignment for 6 of the 11 compounds, with the most promising ones belonging to the families of alkali and alkaline-earth indates and orthoplumbates. This study shows the accuracy of a nonempirical, Hubbard-corrected density-functional theory method to predict band gaps and band offsets at a fraction of the computational cost of hybrid functionals, and outlines an effective strategy to identify photocatalysts for solar hydrogen generation.

The adsorption of AlCl$_{3}$ on Si(100) and the effect of annealing the AlCl$_{3}$-dosed substrate was studied to reveal key surface processes for the development of atomic-precision acceptor-doping techniques. This investigation was performed via scanning tunneling microscopy (STM), X-ray photoelectron spectroscopy (XPS), and density functional theory (DFT) calculations. At room temperature, AlCl$_{3}$ readily adsorbed to the Si substrate dimers and dissociated to form a variety of species. Annealing of the AlCl$_{3}$-dosed substrate at temperatures below 450 $^{\circ}$C produced unique chlorinated aluminum chains (CACs) elongated along the Si(100) dimer row direction. An atomic model for the chains is proposed with supporting DFT calculations. Al was incorporated into the Si substrate upon annealing at 450 $^{\circ}$C and above, and Cl desorption was observed for temperatures beyond 450 $^{\circ}$C. Al-incorporated samples were encapsulated in Si and characterized by secondary ion mass spectrometry (SIMS) depth profiling to quantify the Al atom concentration, which was found to be in excess of 10$^{20}$ cm$^{-3}$ across a $\sim$2.7 nm thick $\delta$-doped region. The Al concentration achieved here and the processing parameters utilized promote AlCl$_{3}$ as a viable gaseous precursor for novel acceptor-doped Si materials and devices for quantum computing., Comment: 35 pages, 8 figures

Diborane (B$_2$H$_6$) is a promising molecular precursor for atomic precision p-type doping of silicon that has recently been experimentally demonstrated [T. {\v{S}}kere{\v{n}}, \textit{et al.,} Nature Electronics (2020)]. We use density functional theory (DFT) calculations to determine the reaction pathway for diborane dissociating into a species that will incorporate as electrically active substitutional boron after adsorbing onto the Si(100)-2$\times$1 surface. Our calculations indicate that diborane must overcome an energy barrier to adsorb, explaining the experimentally observed low sticking coefficient ($< 10^{-4}$ at room temperature) and suggesting that heating can be used to increase the adsorption rate. Upon sticking, diborane has an $\sim 50\%$ chance of splitting into two BH$_3$ fragments versus merely losing hydrogen to form a dimer such as B$_2$H$_4$. As boron dimers are likely electrically inactive, whether this latter reaction occurs is shown to be predictive of the incorporation rate. The dissociation process proceeds with significant energy barriers, necessitating the use of high temperatures for incorporation. Using the barriers calculated from DFT, we parameterize a Kinetic Monte Carlo model that predicts the incorporation statistics of boron as a function of the initial depassivation geometry, dose, and anneal temperature. Our results suggest that the dimer nature of diborane inherently limits its doping density as an acceptor precursor, and furthermore that heating the boron dimers to split before exposure to silicon can lead to poor selectivity on hydrogen and halogen resists. This suggests that while diborane works as an atomic precision acceptor precursor, other non-dimerized acceptor precursors may lead to higher incorporation rates at lower temperatures., Comment: 24 pages, 6 figures

Integration of semiconducting transition metal dichalcogenides (TMDs) into functional optoelectronic circuitries requires an understanding of the charge transfer across the interface between the TMD and the contacting material. Here, we use spatially resolved photocurrent microscopy to demonstrate electronic uniformity at the epitaxial graphene/molybdenum disulfide (EG/MoS2) interface. A 10x larger photocurrent is extracted at the EG/MoS2 interface when compared to metal (Ti/Au) /MoS2 interface. This is supported by semi-local density-functional theory (DFT), which predicts the Schottky barrier at the EG/MoS2 interface to be ~2x lower than Ti/MoS2. We provide a direct visualization of a 2D material Schottky barrier through combination of angle resolved photoemission spectroscopy with spatial resolution selected to be ~300 nm (nano-ARPES) and DFT calculations. A bending of ~500 meV over a length scale of ~2-3 micrometer in the valence band maximum of MoS2 is observed via nano-ARPES. We explicate a correlation between experimental demonstration and theoretical predictions of barriers at graphene/TMD interfaces. Spatially resolved photocurrent mapping allows for directly visualizing the uniformity of built-in electric fields at heterostructure interfaces, providing a guide for microscopic engineering of charge transport across heterointerfaces. This simple probe-based technique also speaks directly to the 2D synthesis community to elucidate electronic uniformity at domain boundaries alongside morphological uniformity over large areas.

We study the surface stability of the layered bismuth-oxide Bi$_2$WO$_6$ and Bi$_2$MoO$_6$ photocatalysts, which belong to the series of Aurivillius (Bi$_2$A$_{n-1}$B$_{n}$O$_{3n+3}$) perovskites and have been proposed as efficient visible-light absorbers, due to favorable electronic hybridization induced by the Bi 6s and 6p orbitals. We present a Newton--Raphson optimization of the charge distribution at the semiconductor--solution interface using the self-consistent continuum solvation (SCCS) model to describe the influence of the aqueous environment. Our analysis provides a description of the charged interface under controlled pH and applied voltage, and offers a molecular interpretation of the competing structural and electrical factors that underlie the facet-dependent photocatalytic activity of layered Bi$_2$A$_{n-1}$B$_{n}$O$_{3n+3}$ compounds., Comment: 9 pages, 6 figures, with supporting information

We consider the factors that affect the photoactivity of silicon electrodes for the water-splitting reaction using a self-consistent continuum solvation (SCCS) model of the solid-liquid interface. This model allows us to calculate the charge-voltage response, Schottky barriers, and surface stability of different terminations while accounting for the interactions between the charge-pinning centers at the surface and the depletion region of the semiconductor. We predict that the most stable oxidized surface does not have a favorable Schottky barrier, which further explains the low solar-to-hydrogen performance of passivated silicon electrodes., Comment: 20 pages, 5 figures, plus supporting information

A wide range of electrochemical reactions of practical importance occur at the interface between a semiconductor and an electrolyte. We present an embedded density-functional theory method using the recently released self-consistent continuum solvation (SCCS) approach to study these interfaces. In this model, a quantum description of the surface is incorporated into a continuum representation of the bending of the bands within the electrode. The model is applied to understand the electrical response of silicon electrodes in solution, providing microscopic insights into the low-voltage region, where surface states determine the electrification of the semiconductor electrode., Comment: 8 pages, 5 figures