We compute the transient dynamics of phonons in contact with high energy "hot" charge carriers in 12 polar and nonpolar semiconductors, using a first-principles Boltzmann transport framework. For ...most materials, we find that the decay in electronic temperature departs significantly from a single-exponential model at times ranging from 1 to 15 ps after electronic excitation, a phenomenon concomitant with the appearance of nonthermal vibrational modes. We demonstrate that these effects result from slow thermalization within the phonon subsystem, caused by the large heterogeneity in the time scales of electron-phonon and phonon-phonon interactions in these materials. We propose a generalized two-temperature model accounting for phonon thermalization as a limiting step of electron-phonon thermalization, which captures the full thermal relaxation of hot electrons and holes in semiconductors. A direct consequence of our findings is that, for semiconductors, information about the spectral distribution of electron-phonon and phonon-phonon coupling can be extracted from the multiexponential behavior of the electronic temperature.
Machine learning (ML) is becoming an effective tool for studying 2D materials. Taking as input computed or experimental materials data, ML algorithms predict the structural, electronic, mechanical, ...and chemical properties of 2D materials that have yet to be discovered. Such predictions expand investigations on how to synthesize 2D materials and use them in various applications, as well as greatly reduce the time and cost to discover and understand 2D materials. This tutorial review focuses on the understanding, discovery, and synthesis of 2D materials enabled by or benefiting from various ML techniques. We introduce the most recent efforts to adopt ML in various fields of study regarding 2D materials and provide an outlook for future research opportunities. The adoption of ML is anticipated to accelerate and transform the study of 2D materials and their heterostructures.
Machine learning (ML) techniques with the genetic algorithm (GA) have been applied to determine a polarizable force field parameters using only ab initio data from quantum mechanics (QM) calculations ...of molecular clusters at the MP2/6-31G(d,p), DFMP2(fc)/jul-cc-pVDZ, and DFMP2(fc)/jul-cc-pVTZ levels to predict experimental condensed phase properties (i.e., density and heat of vaporization). The performance of this ML/GA approach is demonstrated on 4943 dimer electrostatic potentials and 1250 cluster interaction energies for methanol. Excellent agreement between the training data set from QM calculations and the optimized force field model was achieved. The results were further improved by introducing an offset factor during the machine learning process to compensate for the discrepancy between the QM calculated energy and the energy reproduced by optimized force field, while maintaining the local “shape” of the QM energy surface. Throughout the machine learning process, experimental observables were not involved in the objective function, but were only used for model validation. The best model, optimized from the QM data at the DFMP2(fc)/jul-cc-pVTZ level, appears to perform even better than the original AMOEBA force field (amoeba09.prm), which was optimized empirically to match liquid properties. The present effort shows the possibility of using machine learning techniques to develop descriptive polarizable force field using only QM data. The ML/GA strategy to optimize force fields parameters described here could easily be extended to other molecular systems.
Layered molybdenum disulfide has demonstrated great promise as a low-cost alternative to platinum-based catalysts for electrochemical hydrogen production from water. Research effort on this material ...has focused mainly on synthesizing highly nanostructured molybdenum disulfide that allows the exposure of a large fraction of active edge sites. Here we report a promising microwave-assisted strategy for the synthesis of narrow molybdenum disulfide nanosheets with edge-terminated structure and a significantly expanded interlayer spacing, which exhibit striking kinetic metrics with onset potential of -103 mV, Tafel slope of 49 mV per decade and exchange current density of 9.62 × 10(-3) mA cm(-2), performing among the best of current molybdenum disulfide catalysts. Besides benefits from the edge-terminated structure, the expanded interlayer distance with modified electronic structure is also responsible for the observed catalytic improvement, which suggests a potential way to design newly advanced molybdenum disulfide catalysts through modulating the interlayer distance.
Synthetic two-dimensional polymorphs of boron, or borophene, have attracted attention because of their anisotropic metallicity, correlated-electron phenomena, and diverse superlattice structures. ...Although borophene heterostructures have been realized, ordered chemical modification of borophene has not yet been reported. Here, we synthesize "borophane" polymorphs by hydrogenating borophene with atomic hydrogen in ultrahigh vacuum. Through atomic-scale imaging, spectroscopy, and first-principles calculations, the most prevalent borophane polymorph is shown to possess a combination of two-center-two-electron boron-hydrogen and three-center-two-electron boron-hydrogen-boron bonds. Borophane polymorphs are metallic with modified local work functions and can be reversibly returned to pristine borophene through thermal desorption of hydrogen. Hydrogenation also provides chemical passivation because borophane reduces oxidation rates by more than two orders of magnitude after ambient exposure.
The formation mechanism and composition of the solid electrolyte interphase (SEI) in lithium ion batteries has been widely explored. However, relatively little is known about the function of the SEI ...as a transport medium. Such critical information is directly relevant to battery rate performance, power loss, and capacity fading. To partially bridge this gap in the case of inorganic SEI compounds, we report herein the results of first-principles calculations on the defect thermodynamics, the dominant diffusion carriers, and the diffusion pathways associated with crystalline LiF and NaF, which are stable components of the SEI in Li-ion and Na-ion batteries, respectively. The thermodynamics of common point defects are computed, and the dominant diffusion carriers are determined over a voltage range of 0–4 V, corresponding to conditions relevant to both anode and cathode SEI’s. Our analyses reveal that for both compounds, vacancy defects are energetically more favorable, therefore form more readily than interstitials, due to the close-packed nature of the crystal structures. However, the vacancy concentrations are very small for the diffusion processes facilitated by defects. Ionic conductivities are calculated as a function of voltage, considering the diffusion carrier concentration and the diffusion barriers as determined by nudged elastic band calculations. These conductivities are more than ten orders of magnitude smaller in NaF than in LiF. As compared to the diffusivity of Li in other common inorganic SEI compounds, such as Li2CO3 and Li2O, the cation diffusivity in LiF and NaF is quite low, with at least three orders of magnitude lower ionic conductivities. The results quantify the extent to which fluorides pose rate limitations in Li and Na batteries.
Silicon is of significant interest as a next-generation anode material for lithium-ion batteries due to its extremely high capacity. The reaction of lithium with crystalline silicon is known to ...present a rich range of phenomena, including electrochemical solid state amorphization, crystallization at full lithiation of a Li15Si4 phase, hysteresis in the first lithiation–delithiation cycle, and highly anisotropic lithiation in crystalline samples. Very little is known about these processes at an atomistic level, however. To provide fundamental insights into these issues, we develop and apply a first principles, history-dependent, lithium insertion and removal algorithm to model the process of lithiation and subsequent delithiation of crystalline Si. The simulations give a realistic atomistic picture of lithiation demonstrating, for the first time, the amorphization process and hinting at the formation of the Li15Si4 phase. Voltages obtained from the simulations show that lithiation of the (110) surface is thermodynamically more favorable than lithiation of the (100) or (111) surfaces, providing an explanation for the drastic lithiation anisotropy seen in experiments on Si micro- and nanostructures. Analysis of the delithiation and relithiation processes also provides insights into the underlying physics of the lithiation–delithiation hysteresis, thus providing firm conceptual foundations for future design of improved Si-based anodes for Li ion battery applications.
A lack of consensus persists regarding the origin of photoluminescence in silicon nanocrystals. Here we report pressure-dependences of X-ray diffraction and photoluminescence from alkane-terminated ...colloidal particles. We determine the diamond-phase bulk modulus, observe multiple phase transitions, and importantly find a systematic photoluminescence red shift that matches the X conduction-to-Γvalence transition of bulk crystalline silicon. These results, reinforced by calculations, suggest that the efficient photoluminescence, frequently attributed to defects, arises instead from core-states that remain highly indirect despite quantum confinement.
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