The search for metallic boron allotropes has attracted great attention in the past decades and recent theoretical works predict the existence of metallicity in monolayer boron. Here, we synthesize the β12-sheet monolayer boron on a Ag(111) surface and confirm the presence of metallic boronderived bands using angle-resolved photoemission spectroscopy. The Fermi surface is composed of one electron pocket at the S point and a pair of hole pockets near the X point, which is supported by the first-principles calculations. The metallic boron allotrope in β12-sheet opens novel physics and chemistry in material science.

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Light‐induced interlayer ultrafast charge transfer in 2D heterostructures provides a new platform for optoelectronic and photovoltaic applications. The charge separation process is generally hypothesized to be dependent on the interlayer stackings and interactions, however, the quantitative characteristic and detailed mechanism remain elusive. Here, a systematical study on the interlayer charge transfer in model MoS2/WS2 bilayer system with variable stacking configurations by time‐dependent density functional theory methods is demonstrated. The results show that the slight change of interlayer geometry can significantly modulate the charge transfer time from 100 fs to 1 ps scale. Detailed analysis further reveals that the transfer rate in MoS2/WS2 bilayers is governed by the electronic coupling between specific interlayer states, rather than the interlayer distances, and follows a universal dependence on the state‐coupling strength. The results establish the interlayer stacking as an effective freedom to control ultrafast charge transfer dynamics in 2D heterostructures and facilitate their future applications in optoelectronics and light harvesting.

We have performed polarized Raman scattering measurements on WTe2, for which an extremely large positive magnetoresistance has been reported recently. We observe 5 A1 phonon modes and 2 A2 phonon modes out of 33 Raman active modes, with frequencies in good accordance with firstprinciples calculations. The angular dependence of the intensity of the peaks observed is consistent with the Raman tensors of the C2v point group symmetry attributed to WTe2. Although the phonon spectra suggest neither strong electron-phonon nor spin-phonon coupling, the intensity of the A1 phonon mode at 160.6 cm −1 shows an unconventional decrease with temperature decreasing, for which the origin remains unclear.PACS numbers: 74.70. Xa, 75.47.De, 74.25.Kc Giant magnetoresistance is at the core of several important applications, notably for the storage of information. The recent discovery of extremely large positive magnetoresistance (XMR) in layered WTe 2 [1] triggered sudden interest for this material. In particular, the nonsaturating XMR in WTe 2 has been attributed to perfectly balanced electron-hole populations [1,2], similar as in pure bismuth and graphite [3,4]. Interestingly, this effect is strongly affected by external pressure [5], and pressure-induced superconductivity has even been reported [6,7], which questions the importance of the interactions between the electronic structure and the lattice in WTe 2 , and offers additional possibilities for development of devices. Unfortunately, literature still lacks of report on the dynamical properties of the lattice in this system.In this letter, we use Raman scattering spectroscopy to characterize the phonons of WTe 2 single-crystals. We observe 7 out of 33 Raman active modes, with frequencies in good accordance with our first-principles calculations. The angular dependence of the Raman intensity of these modes is consistent with their symmetry assignments in terms of the C 2v point group symmetry of WTe 2 . In contrast to our expectation, none of the phonons observed shows evidence for an electron-phonon coupling. However, the intensity of a A 1 phonon peak at 160.6 cm −1 exhibits an unusual decrease upon cooling, whose origin remains unclear.The WTe 2 single crystals used in our Raman scattering measurements were grown by solid-state reactions. The resistivity of the samples was measured with a Quantum Design physical properties measurement system (PPMS). The crystals were cleaved in air to obtain flat surfaces and then transferred into a low-temperature cryostat ST500 (Janis) for the Raman measurements between 5 and 300 * These two authors contributed equally to this work.† p.richard@iphy.ac.cn ‡ dingh@iphy.ac.cn K with a working vacuum better than 8 × 10 −7 mbar. Raman scattering measurements were performed using a 514.5 nm excitation laser in a back-scattering microRaman configuration, with a triple-grating spectrometer (Horiba Jobin Yvon T64000) equipped with a nitrogencooled CCD camera. In this manuscript, we define x and y as the directions along the a axis (W-W chains) a...

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An efficient and state-of-the-art real-time time-dependent density functional theory (rt-TDDFT) method is presented, as implemented in the time-dependent ab initio package (TDAP), which aims at performing accurate simulations of the interaction between laser fields and solid-state materials. The combination of length-gauge and velocity-gauge electromagnetic field has extended the diversity of materials under consideration, ranging from low dimensional systems to periodic solids. Meanwhile, by employing a local basis presentation, systems of a large size are simulated for long electronic propagation time, with moderate computational cost while maintaining a relatively high accuracy. Non-perturbative phenomena in materials under a strong laser field and linear responses in a weak field can be simulated, either in the presence of ionic motions or not. Several quintessential works are introduced as examples for applications of this approach, including photoabsorption properties of armchair graphene nanoribbon, hole-transfer ultrafast dynamics between MoS 2 /WS 2 interlayer heterojunction, laser-induced nonthermal melting of silicon, and high harmonic generation in monolayer MoS 2 . The method demonstrates great potential for studying ultrafast electron-nuclear dynamics and nonequilibrium phenomena in a wide range of quantum systems.ultrafast dynamics and phenomena either in perturbative or non-perturbative regimes. [3][4][5][6][7][8] Therefore, it has been a unique ab initio quantum method applicable for the exploring of strong field physics beyond linear response theory, for instance, high harmonic generation [9,10] and ultrafast photoelectron emission. [11] Recently, the scope of rt-TDDFT applications has greatly extended from treating isolated atomic and molecular systems to condensed phase materials. In most previous works, numerical implementations of rt-TDDFT that aim at handling solid materials were built on real-space grids, [12,13] including some well-known program packages such as OCTOPUS [9,14] and SALMON. [15,16] Real-time TDDFT has also been implemented in plane wave codes, for example, the ELK FP-LAPW [17] and FPSID, [18] whose encouraging results have shown the effectiveness of the rt-TDDFT approaches. However, if one is interested in high energy excitation that is on the energy scale of tens to hundreds of electron volts (eV), extremely dense real-space grids and high kinetic energy of plane waves are indispensable. Meanwhile, to describe a system with N a atoms, 10 3 to 10 4 × N a real-space grids or plane waves have to be used, which makes the simulation of large-size systems impractical using computer resources available at the present stage. The above two factors will significantly increase the computational cost and in turn limit the practicability of the rt-TDDFT methods.Here we introduce a real-time ab initio approach based on local atomic basis for simulating electron-nuclear dynamics under laser excited conditions. This approach has been successfully implemented in the time-dependent ab initi...

The origin of charge density waves (CDWs) in TiSe has long been debated, mainly due to the difficulties in identifying the timescales of the excitonic pairing and electron–phonon coupling (EPC). Without a time-resolved and microscopic mechanism, one has to assume simultaneous appearance of CDW and periodic lattice distortions (PLD). Here, we accomplish a complete separation of ultrafast exciton and PLD dynamics and unravel their interplay in our real-time time-dependent density functional theory simulations. We find that laser pulses knock off the exciton order and induce a homogeneous bonding–antibonding transition in the initial 20 fs, then the weakened electronic order triggers ionic movements antiparallel to the original PLD. The EPC comes into play after the initial 20 fs, and the two processes mutually amplify each other leading to a complete inversion of CDW ordering. The self-amplified dynamics reproduces the evolution of band structures in agreement with photoemission experiments. Hence we resolve the key processes in the initial dynamics of CDWs that help elucidate the underlying mechanism.

We present the first application of machine learning on per-and polyfluoroalkyl substances (PFAS) for predicting and rationalizing carbon−fluorine (C−F) bond dissociation energies to aid in their efficient treatment and removal. Using a variety of machine learning algorithms (including Random Forest, Least Absolute Shrinkage and Selection Operator Regression, and Feed-forward Neural Networks), we were able to obtain extremely accurate predictions for C−F bond dissociation energies (with deviations less than 0.70 kcal/mol) that are within chemical accuracy of the PFAS reference data. In addition, we show that our machine learning approach is extremely efficient, requiring less than 10 min to train the data and less than a second to predict the C−F bond dissociation energy of a new compound. Most importantly, our approach only needs knowledge of the simple chemical connectivity in a PFAS structure to yield reliable resultswithout recourse to a computationally expensive quantum mechanical calculation or a threedimensional structure. Finally, we present an unsupervised machine learning algorithm that can automatically classify and rationalize chemical trends in PFAS structures that would otherwise have been difficult to humanly visualize or process manually. Collectively, these studies (1) comprise the first application of machine learning techniques for PFAS structures to predict/rationalize C−F bond dissociation energies and (2) show immense promise for assisting experimentalists in the targeted defluorination of specific bonds in PFAS structures (or other unknown environmental contaminants) of increasing complexity.