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Organic photovoltaic (OPV) materials are promising candidates for cheap, printable solar cells. However, there are a very large number of potential donors and acceptors, making selection of the best materials difficult. Here, we show that machine-learning approaches can leverage computationally expensive DFT calculations to estimate important OPV materials properties quickly and accurately. We generate quantitative relationships between simple and interpretable chemical signature and one-hot descriptors and OPV power conversion efficiency (PCE), open circuit potential (Voc), short circuit density (Jsc), highest occupied molecular orbital (HOMO) energy, lowest unoccupied molecular orbital (LUMO) energy, and the HOMO–LUMO gap. The most robust and predictive models could predict PCE (computed by DFT) with a standard error of ±0.5 for percentage PCE for both the training and test set. This model is useful for pre-screening potential donor and acceptor materials for OPV applications, accelerating design of these devices for green energy applications. [ABSTRACT FROM AUTHOR]

The absorption spectra of congenetic wurtzite (WZ) and zincblende (ZB) CdS magic-sized clusters are investigated. We demonstrate that the exciton peak positions can be tuned by up to 500 meV by varying the strong coupling between X-type ligands and the semiconductor cores, while the addition of L-type ligands primarily affects cluster midgap states. When Z-type ligands are displaced by L-type ligands, red shifts in the absorption spectra are observed, despite the fact there is a small decrease in cluster size. Density functional theory calculations are used to explain these findings and they reveal the importance of Cd and S dangling bonds on the midgap states during the Z- to L-type ligand exchange process. Overall, ZB CdS clusters show higher chemical stability than WZ clusters but their optical properties exhibit greater sensitivity to the solvent. Conversely, WZ CdS clusters are not stable in a Lewis base-rich environment, resulting in various changes in their spectra. Our findings enable researchers to select capping ligands that modulate the optical properties of semiconductor clusters while maintaining precise control over their solvent interactions. [ABSTRACT FROM AUTHOR]

Liquid metals (LMs) are emerging as unique fluids for a variety of applications, but their nanoscale solvation properties remain largely understudied. In this work, a combination of atomic force microscopy (AFM) and molecular dynamics (MD) simulations are used to investigate the structure of the interface between the bulk room temperature liquid metal (RTLM) and the LM oxide in nanodroplet systems of gallium, EGaIn (75.5% gallium, 24.5% indium), and Galinstan (68.5% gallium, 21.5% indium, 10% tin). Field's metal (51% indium, 32.5% bismuth, 16.5% tin) is also investigated, which melts at ≈62 °C, as a contrast to the other systems. AFM measurements reveal distinct sub‐oxide nanostructured layering in all three RTLM systems, and Field's metal above the melting point, to differing degrees. EGaIn and Galinstan show multiple penetration events between 20 and 30 nm, with smaller, less complex events in Ga. MD simulations suggest that this layering is a result of the near‐surface ordering of LM atoms beneath the oxide layer. Importantly, the atoms in this region do not behave as solids but are more ordered than in a pure disordered liquid system. The surface nanostructure elucidated here significantly expands the understanding of LM systems and their behavior at interfaces. [ABSTRACT FROM AUTHOR]

Crystallization of alloys from a molten state is a fundamental process underpinning metallurgy. Here the direct imaging of an intermetallic precipitation reaction at equilibrium in a liquid‐metal environment is demonstrated. It is shown that the outer layers of a solidified intermetallic are surprisingly unstable to the depths of several nanometers, fluctuating between a crystalline and a liquid state. This effect, referred to herein as crystal interface liquefaction, is observed at remarkably low temperatures and results in highly unstable crystal interfaces at temperatures exceeding 200 K below the bulk melting point of the solid. In general, any liquefaction process would occur at or close to the formal melting point of a solid, thus differentiating the observed liquefaction phenomenon from other processes such as surface pre‐melting or conventional bulk melting. Crystal interface liquefaction is observed in a variety of binary alloy systems and as such, the findings may impact the understanding of crystallization and solidification processes in metallic systems and alloys more generally. [ABSTRACT FROM AUTHOR]

[Display omitted] • Halide perovskite phosphor with high quantum efficiency. • Machine learning model for material design. • Enhancing self-trapped exciton emission by tuning ion radius. • White light LED with commercial potential. The outstanding emission of halide perovskites make them ideal candidates for white emission light-emitting diodes (LEDs) for lighting applications. However, many perovskites contain toxic or scarce elements and have unsatisfactory stability. Here, we report a target-driven approach, based on active learning (AL) techniques, to discover halide perovskites suitable for commercial LED applications. Based on the similarity between halide and oxide perovskites, a model trained on an oxide perovskite dataset plus six AL-selected halide perovskites exhibited excellent performance for photoluminescence quantum yield (PLQY) predictions of oxide and halide perovskites. The model proposed a strong relationship between ionic radii and PLQY, postulated to be due to the self-trap excitons derived from the Jahn-Teller deformation. A novel halide perovskite phosphor, Cs 4 Zn(Bi 0.85 Sb 0.15) 2 Cl 12 :0.01Mn, was designed and synthesized with the aid of the model. It exhibited an 88 % PLQY and outstanding thermal and luminescent stability. A simple white LED was fabricated from this material, exemplifying its commercial potential. This study demonstrates how machine learning techniques can accelerate discovery of next-generation phosphors for high performance single emitter-based white-light emitting devices. [ABSTRACT FROM AUTHOR]

For photovoltaic materials, properties such as band gap E g are critical indicators of the material's suitability to perform a desired function. Calculating E g is often performed using Density Functional Theory (DFT) methods, although more accurate calculation are performed using methods such as the GW approximation. DFT software often used to compute electronic properties includes applications such as VASP, CRYSTAL, CASTEP or Quantum Espresso. Depending on the unit cell size and symmetry of the material, these calculations can be computationally expensive. In this study, we present a new machine learning platform for the accurate prediction of properties such as E g of a wide range of materials. [ABSTRACT FROM AUTHOR]

Inorganic lead‐free halide perovskites, devoid of toxic or rare elements, have garnered considerable attention as photocatalysts for pollution control, CO2 reduction and hydrogen production. In the extensive perovskite design space, factors like substitution or doping level profoundly impact their performance. To address this complexity, a synergistic combination of machine learning models and theoretical calculations were used to efficiently screen substitution elements that enhanced the photoactivity of substituted Cs2AgBiBr6 perovskites. Machine learning models determined the importance of d10 orbitals, highlighting how substituent electron configuration affects electronic structure of Cs2AgBiBr6. Conspicuously, d10‐configured Zn2+ boosted the photoactivity of Cs2AgBiBr6. Experimental verification validated these model results, revealing a 13‐fold increase in photocatalytic toluene conversion compared to the unsubstituted counterpart. This enhancement resulted from the small charge carrier effective mass, as well as the creation of shallow trap states, shifting the conduction band minimum, introducing electron‐deficient Br, and altering the distance between the B‐site cations d band centre and the halide anions p band centre, a parameter tuneable through d10 configuration substituents. This study exemplifies the application of computational modelling in photocatalyst design and elucidating structure–property relationships. It underscores the potential of synergistic integration of calculations, modelling, and experimental analysis across various applications. [ABSTRACT FROM AUTHOR]

Organic–inorganic perovskite solar cells (PSCs) are promising candidates for next‐generation, inexpensive solar panels due to their commercially competitive cost and high power conversion efficiencies. However, PSCs suffer from poor stability. A new and vast subset of PSCs, quasi‐two‐dimensional Ruddlesden–Popper PSCs (quasi‐2D RP PSCs), has improved photostability and superior resilience to environmental conditions compared to three‐dimensional metal‐halide PSCs. To accelerate the search for new quasi‐2D RP PSCs, this work reports a combinatorial, machine learning (ML) enhanced high‐throughput perovskite film fabrication and optimization study. This work designs a bespoke experimental strategy and produces perovskite films with a range of different compositions using only spin‐coating free, reproducible robotic fabrication processes. The performance and characterization data of these solar cells are used to train a ML model that allow materials parameters to be optimized and direct the design of improved materials. The new, ML‐optimized, drop‐cast quasi‐2D RP perovskite films yield solar cells with power conversion efficiencies of up to 16.9%. [ABSTRACT FROM AUTHOR]

Miniaturization and energy consumption by computational systems remain major challenges to address. Optoelectronics based synaptic and light sensing provide an exciting platform for neuromorphic processing and vision applications offering several advantages. It is highly desirable to achieve single‐element image sensors that allow reception of information and execution of in‐memory computing processes while maintaining memory for much longer durations without the need for frequent electrical or optical rehearsals. In this work, ultra‐thin (<3 nm) doped indium oxide (In2O3) layers are engineered to demonstrate a monolithic two‐terminal ultraviolet (UV) sensing and processing system with long optical state retention operating at 50 mV. This endows features of several conductance states within the persistent photocurrent window that are harnessed to show learning capabilities and significantly reduce the number of rehearsals. The atomically thin sheets are implemented as a focal plane array (FPA) for UV spectrum based proof‐of‐concept vision system capable of pattern recognition and memorization required for imaging and detection applications. This integrated light sensing and memory system is deployed to illustrate capabilities for real‐time, in‐sensor memorization, and recognition tasks. This study provides an important template to engineer miniaturized and low operating voltage neuromorphic platforms across the light spectrum based on application demand. [ABSTRACT FROM AUTHOR]

This work presents algorithms for the efficient enumeration of configuration spaces following Boltzmann-like statistics, with example applications to the calculation of non-radiative rates, and an open-source implementation. Configuration spaces are found in several areas of physics, particularly wherever there are energy levels that possess variable occupations. In bosonic systems, where there are no upper limits on the occupation of each level, enumeration of all possible configurations is an exceptionally hard problem. We look at the case where the levels need to be filled to satisfy an energy criterion, for example, a target excitation energy, which is a type of knapsack problem as found in combinatorics. We present analyses of the density of configuration spaces in arbitrary dimensions and how particular forms of kernel can be used to envelope the important regions. In this way, we arrive at three new algorithms for enumeration of such spaces that are several orders of magnitude more efficient than the naive brute force approach. Finally, we show how these can be applied to the particular case of internal conversion rates in a selection of molecules and discuss how a stochastic approach can, in principle, reduce the computational complexity to polynomial time. [ABSTRACT FROM AUTHOR]

Perylene diimide (PDI) derivatives are widely used materials for luminescent solar concentrator (LSC) applications due to their attractive optical and electronic properties. In this work, we study aggregation-induced exciton quenching pathways in four PDI derivatives with increasing steric bulk, which were previously synthesized. We combine molecular dynamics and quantum chemical methods to simulate the aggregation behavior of chromophores at low concentration and compute their excited state properties. We found that PDIs with small steric bulk are prone to aggregate in a solid state matrix, while those with large steric volume displayed greater tendencies to isolate themselves. We find that for the aggregation class of PDI dimers, the optically accessible excitations are in close energetic proximity to triplet charge transfer (CT) states, thus facilitating inter-system crossing and reducing overall LSC performance. While direct singlet fission pathways appear endothermic, evidence is found for the facilitation of a singlet fission pathway via intermediate CT states. Conversely, the insulation class of PDI does not suffer from aggregation-induced photoluminescence quenching at the concentrations studied here and therefore display high photon output. These findings should aid in the choice of PDI derivatives for various solar applications and suggest further avenues for functionalization and study. [ABSTRACT FROM AUTHOR]

Gallium nitride (GaN) technology has matured and commercialised for optoelectronic devices in the ultraviolet (UV) spectrum over the last few decades. Simultaneously, atomically thin materials with unique features have emerged as contenders for device miniaturization. However, the lack of successful techniques to produce ultra‐thin GaN prevents access to these new predicted properties. Here, this important gap is addressed by printing millimeter‐large ultra‐thin GaN nanosheets (NS) (≈1.4 nm) using a simple two‐step process that simultaneously introduces nitrogen point defects. This extends the photoelectrical spectral response from UV (280 nm) to near infrared (NIR) (1080 nm). The GaN‐based photodetectors display excellent figures of merit, having a responsivity (2.72 × 104 A W−1) up to four orders of magnitude higher than the commercial photodetectors at room temperature, despite being 102–103 times thinner. The photodetectors exhibit fast switching, with rise and decay time in the range of microseconds. The state‐of‐the‐art device performance originates from the ultra‐thin nature of GaN NS coupled with nitrogen point vacancies in the synthesis process. This work presents the opportunity to significantly expand the reach of GaN semiconductor technology and may lead to applications in high‐performance miniaturized imaging systems, spectroscopy, communication, and integrated optoelectronic circuits. [ABSTRACT FROM AUTHOR]

[Display omitted] • Imide-substituted naphthalene diimide (NDI) derivatives with increasing sidechain steric bulk were synthesized and their photophysical properties were investigated. • Photophysical properties of the NDI derivative were strongly modulated by solvation in electron-rich aromatic solvents with broadening of their UV–vis absorption spectrum as well as enhanced broad, red-shifted emission in some cases. • When dispersed in polystyrene matrix, both chromophore-matrix association and chromophore-chromophore aggregation contributed to the observed photophysical properties. • With the support of theoretical models, it was evident that variation in photophysical properties was a result of explicit chromophore-media interactions. Naphthalene diimides (NDIs) are a common class of chromophores used in photon harvesting applications due to their functional malleability through substitution of the NDI core. However, some derivatives with substitution at the imide position of the NDI core only become emissive in electron-rich aromatic solvents. This study examines this phenomenon from both an experimental and theoretical perspective, in order to understand how NDIs interact with each other and the surrounding medium upon photoexcitation. We report the photophysical properties of cyclohexyl and several aromatic imide-substituted NDI derivatives, and show that fluorescence properties are strongly influenced by solvation in more electron-rich aromatic solvents (e.g. toluene, xylene, mesitylene). Theoretical modeling supports strong interactions, including ground state charge-transfer complexation, with aromatic solvents. In solid poly(methyl methacrylate) (PMMA) and poly(styrene) (PS) film media, both aggregation and complexation are shown to contribute to absorption and emission properties. The results also demonstrate that aromatic imide substituents not only act to provide steric bulk to the NDI chromophore but participate in interactions with the surrounding medium that affect the overall photophysical properties. [ABSTRACT FROM AUTHOR]

We have performed DFT calculations using both plane wave-pseudopotential and Gaussian basis set approaches on the (1 1 1) and (2 1 0) surfaces of pyrite (FeS2). Our calculations indicate that the (1 1 1) surface is more stable than the (2 1 0) surface, which is predicted to have a higher surface energy. The (2 1 0) surface is predicted to be essentially bulk terminated, with a relatively small amount of surface relaxation. Bridging S atoms on the (1 1 1) surface undergo significant lateral displacement to coordinate to neighbouring undercoordinated surface Fe atoms. Electrostatic effects induced by loss of coordination at surface Fe atoms are likely to be responsible for surface ionic displacements. Our calculations indicate that surface Fe states dominate at the Fermi level on the (2 1 0) surface, but that surface S states make significant contributions to the valence band on the (1 1 1) surface. On the (2 1 0) surface, Fe atoms of 4-fold coordination are spin polarized and therefore paramagnetic, while 5-fold coordinated Fe are diamagnetic. For the (1 1 1) surface, both 5- and 6-fold coordinated Fe atoms are predicted to be spin polarized, although nominally the unpaired electrons are expected to be localised on the surface S− species. This is likely to be due to the removal of spin polarization from the surface S by charge transfer from the surface Fe. [Copyright &y& Elsevier]

We have performed density-functional theory calculations using both plane wave-pseudopotential and Gaussian basis set approaches on the (1 0 0), planar (1 1 0) and microfacetted (1 1 0) surfaces of pyrite (FeS2). Our calculations indicate that the (1 0 0) surface is more stable than the planar (1 1 0) surface, which is predicted to have a higher surface energy. Creation of microfacets on the (1 1 0) surface resulted in a lower surface energy. Relatively small differences in calculated surface energy between the ideal and relaxed (1 0 0) and (1 1 0) surfaces were found. The (1 0 0) and (1 1 0) surfaces are predicted to be essentially bulk-terminated, with a relatively small amount of relaxation. Electrostatic effects induced by loss of coordination at surface Fe atoms are likely to be responsible for surface ionic displacements. Our calculations indicate that surface Fe atoms of fourfold coordination, present on the (1 1 0) surfaces, are spin polarized, while those of fivefold coordination are fully spin-paired. These results suggest that magnetic species, such as O2, are more prone to react at low Fe coordination defect sites on real FeS2 (1 0 0) surfaces. [Copyright &y& Elsevier]

We introduce a nonclassical model for nanocrystal nucleation in solution which centers on the dynamic interplay of chemical bond breakage and formation coupled with the desolvation of precursor molecules, which we term the molecular chemistry (MC) model. Departing from classical theory, our model employs the bond count as the key variable rather than particle size, thereby redefining the role of supersaturation and its role in determining the so-called critical nucleus size. We apply the model to CdSe nanocrystal formation in nonpolar solvents and showcase its efficacy in predicting solvent dynamics, precursor characteristics, crystal phase, stoichiometry, "magic number" behavior, and transition states. While the coupled-cluster method is used to determine the bond energy, we show that it is possible to derive reaction pathways by reducing the calculations to algebraic approximations for the nucleation energy. This singular set of bond energy parameters allows nanocrystal nucleation and growth to be conceptualized as a straightforward chemical reaction.

Sodium (Na) doping is a well-established technique employed in chalcopyrite and kesterite solar cells. While various improvements can be achieved in crystalline quality, electrical properties, or defect passivation of the absorber materials by incorporating Na, a comprehensive demonstration of the desired Na distribution in CZTSSe is still lacking. Herein, a straightforward Na doping approach by dissolving NaCl into the CZTS precursor solution is proposed. It is demonstrated that a favorable Na ion distribution should comprise a precisely controlled Na + concentration at the front surface and an enhanced distribution within the bottom region of the absorber layer. These findings demonstrated that Na ions play several positive roles within the device, leading to an overall power conversion efficiency of 12.51%., (© 2024 Wiley‐VCH GmbH.)

The emergence of ferroelectricity in two-dimensional (2D) metal oxides is a topic of significant technological interest; however, many 2D metal oxides lack intrinsic ferroelectric properties. Therefore, introducing asymmetry provides access to a broader range of 2D materials within the ferroelectric family. Here, the generation of asymmetry in 2D SnO by doping the material with Hf 0.5 Zr 0.5 O 2 (HZO) is demonstrated. A liquid metal process as a doping strategy for the preparation of 2D HZO-doped SnO with robust ferroelectric characteristics is implemented. This technology takes advantage of the selective interface enrichment of molten Sn with HZO crystallites. Molecular dynamics simulations indicate a strong tendency of Hf and Zr atoms to migrate toward the surface of liquid metal and embed themselves within the growing oxide layer in the form of HZO. Thus, the liquid metal-based harvesting/doping technique is a feasible approach devised for producing novel 2D metal oxides with induced ferroelectric properties, represents a significant development for the prospects of random-access memories., (© 2024 The Authors. Small published by Wiley‐VCH GmbH.)

Low-melting liquid metals are emerging as a new group of highly functional solvents due to their capability to dissolve and alloy various metals in their elemental state to form solutions as well as colloidal systems. Furthermore, these liquid metals can facilitate and catalyze multiple unique chemical reactions. Despite the intriguing science behind liquid metals and alloys, very little is known about their fundamental structures in the nanometric regime. To bridge this gap, this work employs small angle neutron scattering and molecular dynamics simulations, revealing that the most commonly used liquid metal solvents, EGaIn and Galinstan, are surprisingly structured with the formation of clusters ranging from 157 to 15.7 Å. Conversely, noneutectic liquid metal alloys of GaSn or GaIn at low solute concentrations of 1, 2, and 5 wt%, as well as pure Ga, do not exhibit these structures. Importantly, the eutectic alloys retain their structure even at elevated temperatures of 60 and 90 °C, highlighting that they are not just simple homogeneous fluids consisting of individual atoms. Understanding the complex soft structure of liquid alloys will assist in comprehending complex phenomena occurring within these fluids and contribute to deriving reaction mechanisms in the realm of synthesis and liquid metal-based catalysis., (© 2024 The Author(s). Advanced Materials published by Wiley‐VCH GmbH.)

Two-dimensional (2D) organic-inorganic metal halide perovskites have gained immense attention as alternatives to three-dimensional (3D) perovskites in recent years. The hydrophobic spacers in the layered structure of 2D perovskites make them more moisture-resistant than 3D perovskites. Moreover, they exhibit unique anisotropic electrical transport properties due to a structural confinement effect. In this study, four lead-free Dion-Jacobson (DJ) Sn-based phase perovskite single crystals, 3AMPSnI 4 , 4AMPSnI 4 , 3AMPYSnI 4 , and 4AMPYSnI 4 [AMP = (aminomethyl)-piperidinium, AMPY = (aminomethyl)pyridinium] are reported. Results reveal structural differences between them impacting the resulting optical properties. Namely, higher octahedron distortion results in a higher absorption edge. Density functional theory (DFT) is also performed to determine the trends in energy band diagrams, exciton binding energies, and formation energies due to structural differences among the four single crystals. Finally, a field-effect transistor (FET) based on 4AMPSnI 4 is demonstrated with a respectable hole mobility of 0.57 cm 2 V -1 s -1 requiring a low threshold voltage of only -2.5 V at a drain voltage of -40 V. To the best of our knowledge, this is the third DJ-phase perovskite FET reported to date.

The use of liquid gallium as a solvent for catalytic reactions has enabled access to well-dispersed metal atoms configurations, leading to unique catalytic phenomena, including activation of neighbouring liquid atoms and mobility-induced activity enhancement. To gain mechanistic insights into liquid metal catalysts, here we introduce a GaSn 0.029 Ni 0.023 liquid alloy for selective propylene synthesis from decane. Owing to their mobility, dispersed atoms in a Ga matrix generate configurations where interfacial Sn and Ni atoms allow for critical alignments of reactants and intermediates. Computational modelling, corroborated by experimental analyses, suggests a particular reaction mechanism by which Sn protrudes from the interface and an adjacent Ni, below the interfacial layer, aligns precisely with a decane molecule, facilitating propylene production. We then apply this reaction pathway to canola oil, attaining a propylene selectivity of ~94.5%. Our results offer a mechanistic interpretation of liquid metal catalysts with an eye to potential practical applications of this technology., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Two-dimensional (2D) metal organic framework (MOF) or metalloporphyrin nanosheets with a stable metal-N 4 complex unit present the metal as a single-atom catalyst dispersed in the 2D porphyrin framework. First-principles calculations on the 3d-transition metals in M-TCPP are investigated in this study for their surface-dependent electronic properties including work function and d-band center. Crystal orbital Hamiltonian population (-pCOHP) analysis highlights a higher contribution of the bonding state in the M-N bond and antibonding state in the N-N bond to be essential for N-N bond activation. A linear relationship between Δ G max and surface electronic properties, N-N bond strength, and Bader charge has been found to influence the rate-determining potential for nitrogen reduction reaction (NRR) in M-TCPP MOFs. 2D Ti-TCPP MOF, with a kinetic energy barrier of 1.43 eV in the final protonation step of enzymatic NRR, shows exclusive NRR selectivity over competing hydrogen reduction (HER) and nitrogenous compounds (NO and NO 2 ). Thus, Ti-TCPP MOF with an NRR limiting potential of -0.35 V in water solvent is proposed as an attractive candidate for electrocatalytic NRR.

Inorganic CsPbX 3 (X = Cl, Br, I) perovskite nanocrystals (NCs) possess many advantageous optoelectronic properties, making them an attractive candidate for light emitting diodes, lasers, or photodetector applications. Such perovskite NCs can form extended assemblies that further modify their bandgap and emission wavelength. In this article, a facile direct synthesis of CsPbX 3 NC assemblies that are 1 μm in size and are composed of 10 nm-sized NC building blocks is reported. The direct synthesis of these assemblies with a conventional hot-injection method of the NCs is achieved through the judicious selection of the solvent, ligands, and reaction stoichiometry. Only under selective reaction conditions where the surface ligand environment is tuned to enhance the hydrophobic interactions between ligand chains of neighbouring NCs is self-assembly achieved. These assemblies possess narrow and red-shifted photoluminescence compared to their isolated NC counterparts, which further expands the colour gamut that can be rendered from inorganic perovskites. This is demonstrated through simple down-converting light emitters.

Two-dimensional (2D) layered metal dichalcogenides constitute a promising class of materials for photodetector applications due to their excellent optoelectronic properties. The most common photodetectors, which work on the principle of photoconductive or photovoltaic effects, however, require either the application of external voltage biases or built-in electric fields, which makes it challenging to simultaneously achieve high responsivities across broad-band wavelength excitation─especially beyond the material's nominal band gap─while producing low dark currents. In this work, we report the discovery of an intricate phonon-photon-electron coupling─which we term the acoustophotoelectric effect─in SnS 2 that facilitates efficient photodetection through the application of 100 MHz order propagating surface acoustic waves (SAWs). This effect not only reduces the band gap of SnS 2 but also provides the requisite momentum for indirect band gap transition of the photoexcited charge carriers, to enable broad-band photodetection beyond the visible light range, while maintaining pA-order dark currents─ without the need for any external voltage bias. More specifically, we show in the infrared excitation range that it is possible to achieve up to 8 orders of magnitude improvement in the material's photoresponsivity compared to that previously reported for SnS 2 -based photodetectors, in addition to exhibiting superior performance compared to most other 2D materials reported to date for photodetection.

Gating logical operations through high-lying electronic excited states presents opportunities for developing ultrafast, subnanometer computational devices. A lack of molecular systems with sufficiently long-lived higher excited states has hindered practical realization of such devices, but recent studies have reported intriguing photophysics from high-lying excited states of perylene. In this work, we use femtosecond spectroscopy supported by quantum chemical calculations to identify and quantify the relaxation dynamics of monomeric perylene's higher electronic excited states. The 2 1 B 2u state is accessed through single-photon absorption at 250 nm, while the optically dark 2 1 A g state is excited via the 1 1 B 3u state. Population of either state results in subpicosecond relaxation to the 1 1 B 3u state, and we quantify 2 1 A g and 2 1 B 2u state lifetimes of 340 and 530 fs, respectively. These lifetimes are significantly longer than the singlet fission time constant from the perylene 2 1 B 2u state, suggesting that the higher electronic states of perylene may be useful for gating logical operations.

The first order and second order corrected photoluminescence quantum yields are computed and compared to experiment for naphthalene in this manuscript discussing negative results. Results for anthracene and tetracene are recalled from previous work (Manian et al. in J Chem Phys 155:054108, 2021), and the results for all three polyacenes are juxtaposed to each other. While at the Franck-Condon point, each of the three noted polyacenes were found to possess a quantum yield near unity. Following the consideration of Herzberg-Teller effects, quantum yields stabilised for anthracene and tetracene to 0.19 and 0.08, respectively. Conversely, the second order corrected quantum yield for naphthalene was found to be 0.91. Analysis of this result showed that while the predicted non-radiative pathways correlate well with what should be expected, the approximation used to calculate second order corrected fluorescence, which yielded very positive results for many other molecular systems, here is unable to account for strong second order contributions, resulting in a grossly overestimated rate of fluorescence. However, substitution of an experimental radiative rate results in a quantum yield of 0.33. This work extols the importance of Herzberg-Teller terms in photophysical descriptions of chromophores, and highlights those cases in which a treatment beyond the above approximation is required., (© 2022. The Author(s).)

Establishing a data-driven pipeline for the discovery of novel materials requires the engineering of material features that can be feasibly calculated and can be applied to predict a material's target properties. Here we propose a new class of descriptors for describing crystal structures, which we term Robust One-Shot Ab initio (ROSA) descriptors. ROSA is computationally cheap and is shown to accurately predict a range of material properties. These simple and intuitive class of descriptors are generated from the energetics of a material at a low level of theory using an incomplete ab initio calculation. We demonstrate how the incorporation of ROSA descriptors in ML-based property prediction leads to accurate predictions over a wide range of crystals, amorphized crystals, metal-organic frameworks and molecules. We believe that the low computational cost and ease of use of these descriptors will significantly improve ML-based predictions., (© 2022. The Author(s).)

Insights into metal-matrix interactions in atomically dispersed catalytic systems are necessary to exploit the true catalytic activity of isolated metal atoms. Distinct from catalytic atoms spatially separated but immobile in a solid matrix, here we demonstrate that a trace amount of platinum naturally dissolved in liquid gallium can drive a range of catalytic reactions with enhanced kinetics at low temperature (318 to 343 K). Molecular simulations provide evidence that the platinum atoms remain in a liquid state in the gallium matrix without atomic segregation and activate the surrounding gallium atoms for catalysis. When used for electrochemical methanol oxidation, the surface platinum atoms in the gallium-platinum system exhibit an activity of [Formula: see text] three orders of magnitude higher than existing solid platinum catalysts. Such a liquid catalyst system, with a dynamic interface, sets a foundation for future exploration of high-throughput catalysis., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Catalytic solvent regeneration has attracted broad interest owing to its potential to reduce energy consumption in CO 2 separation, enabling industry to achieve emission reduction targets of the Paris Climate Accord. Despite recent advances, the development of engineered acidic nanocatalysts with unique characteristics remains a challenge. Herein, we establish a strategy to tailor the physicochemical properties of metal-organic frameworks (MOFs) for the synthesis of water-dispersible core-shell nanocatalysts with ease of use. We demonstrate that functionalized nanoclusters (Fe 3 O 4 -COOH) effectively induce missing-linker deficiencies and fabricate mesoporosity during the self-assembly of MOFs. Superacid sites are created by introducing chelating sulfates on the uncoordinated metal clusters, providing high proton donation capability. The obtained nanomaterials drastically reduce the energy consumption of CO 2 capture by 44.7% using only 0.1 wt.% nanocatalyst, which is a ∽10-fold improvement in efficiency compared to heterogeneous catalysts. This research represents a new avenue for the next generation of advanced nanomaterials in catalytic solvent regeneration., (© 2022. The Author(s).)

Lead-based halide perovskite nanocrystals (NCs) are recognized as emerging emissive materials with superior photoluminescence (PL) properties. However, the toxicity of lead and the swift chemical decomposition under atmospheric moisture severely hinder their commercialization process. Herein, we report the first colloidal synthesis of lead-free Cs 4 CuIn 2 Cl 12 layered double perovskite NCs via a facile moisture-assisted hot-injection method stemming from relatively nontoxic precursors. Although moisture is typically detrimental to NC synthesis, we demonstrate that the presence of water molecules in Cs 4 CuIn 2 Cl 12 synthesis enhances the PL quantum yield (mainly in the near-UV range), induces a morphological transformation from 3D nanocubes to 2D nanoplatelets, and converts the dark transitions to radiative transitions for the observed self-trapped exciton relaxation. This work paves the way for further studies on the moisture-assisted synthesis of novel lead-free halide perovskite NCs for a wide range of applications.

It is well-understood that during the liquid-to-solid phase transition of alloys, elements segregate in the bulk phase with the formation of microstructures. In contrast, we show here that in a Bi-Ga alloy system, highly ordered nanopatterns emerge preferentially at the alloy surfaces during solidification. We observed a variety of transition, hybrid and crystal-defect-like patterns, in addition to lamellar and rod-like structures. Combining experiments and molecular dynamics simulations, we investigated the influence of the superficial Bi and Ga 2 O 3 layers during surface solidification and elucidated the pattern-formation mechanisms, which involve surface-catalysed heterogeneous nucleation. We further demonstrated the dynamic nature and robustness of the phenomenon under different solidification conditions and for various alloy systems. The surface patterns we observed enable high-spatial-resolution nanoscale-infrared and surface-enhanced Raman mapping, which reveal promising potential for surface- and nanoscale-based applications.

Geometries and electronic structures of germanium trimer clusters doped with titanium TiGe 3 -/0 were studied making use of the complete active space self-consistent field followed by second-order perturbation theory explicitly correlated coupled cluster singles and doubles method with perturbative triples corrections CCSD(T)-F12 and Tao-Perdew-Staroverov-Scuseria methods. Two electronic states ( 2 A' and 2 A″) of the anion (pyramid shape) were determined to be nearly degenerate and energetically competing for the anionic ground state of TiGe 3 - . These two anionic states are believed to be concurrently populated in the experiment and induce six observed anion photoelectron bands. Total 14 electronic transitions starting from the 2 A' and 2 A″ states were assigned to five out of six visible bands in the experimental anion photoelectron spectrum of TiGe 3 - . Each band was proven to be caused by multiple one-electron detachments from two populated anionic states. The last experimental band with the highest detachment energy is believed to be the result of various inner one-electron removals.

This work presents a method of grouping the electron spinors and the phonon modes of metal oxide crystals such as vanadium dioxide into an SU(2) gauge theory. The gauge "charge" is the electron spin, which is assumed to couple to the transverse acoustic phonons on the basis of spin ordering phenomena in [Formula: see text]- and [Formula: see text]-[Formula: see text], while the longitudinal mode is neutral. A generalization of the Peierls Mechanism is presented based on the discrete gauge invariance of crystals and the corresponding Ward-Takahashi identity. The introduction of a band index results in violation of this discrete Ward-Takahashi identity for interband transitions, resulting in scattering from the longitudinal component. Thus both the spinors and the bosons acquire mass and an electronic band gap and optical phonon modes result: a symmetry-breaking metal-insulator transition, which can manifest concurrent spin-ordering.

The predicted strong piezoelectricity for monolayers of group IV monochalcogenides, together with their inherent flexibility, makes them likely candidates for developing flexible nanogenerators. Within this group, SnS is a potential choice for such nanogenerators due to its favourable semiconducting properties. To date, access to large-area and highly crystalline monolayer SnS has been challenging due to the presence of strong inter-layer interactions by the lone-pair electrons of S. Here we report single crystal across-the-plane and large-area monolayer SnS synthesis using a liquid metal-based technique. The characterisations confirm the formation of atomically thin SnS with a remarkable carrier mobility of ~35 cm 2 V -1 s -1 and piezoelectric coefficient of ~26 pm V -1 . Piezoelectric nanogenerators fabricated using the SnS monolayers demonstrate a peak output voltage of ~150 mV at 0.7% strain. The stable and flexible monolayer SnS can be implemented into a variety of systems for efficient energy harvesting.

Novel physical phenomena emerge in ultra-small sized nanomaterials. We study the limiting small-size-dependent properties of MoS 2 monolayer rhombic nanoflakes using density-functional theory on structures of size up to Mo 35 S 70 (1.74 nm). We investigate the structural and electronic properties as functions of the lateral size of the nanoflakes, finding zigzag is the most stable edge configuration, and that increasing size is accompanied by greater stability. We also investigate passivation of the structures to explore realistic settings, finding increased HOMO-LUMO gaps and energetic stability. Understanding the size-dependent properties will inform efforts to engineer electronic structures at the nano-scale.

We report the multi-scale modeling and design of a gate-defined single-electron transistor in a MoS 2 bilayer. By combining density-functional theory and finite-element analysis, we design a surface gate structure to electrostatically define and tune a quantum dot and its associated tunnel barriers in the MoS 2 bilayer. Our approach suggests new pathways for the creation of novel quantum electronic devices in two-dimensional materials.

At a relatively low loading concentration (≈0.02 wt%) of 2D MoS 2 flakes in PDMS, the composite membrane is able to almost completely block the permeation of NO2 gas molecules at ppm levels. This major reduction is ascribed to the strong physisorption of NO2 gas molecules onto the 2D MoS2 flake basal planes., (© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Ternary glass structures are notoriously difficult to model accurately, and yet prevalent in several modern endeavors. Here, a novel combination of Reverse Monte Carlo (RMC) modeling and ab initio molecular dynamics (MD) is presented, rendering these complicated structures computationally tractable. A case study (Ge6.25As32.5Se61.25 glass) illustrates the effects of ab initio MD quench rates and equilibration temperatures, and the combined approach's efficacy over standard RMC or random insertion methods. Submelting point MD quenches achieve the most stable, realistic models, agreeing with both experimental and fully ab initio results. The simple approach of RMC followed by ab initio geometry optimization provides similar quality to the RMC-MD combination, for far fewer resources.

Previous experimental studies have indicated that the controlled formation of anisotropic pyrite nanoparticles, such as nanorods or nanowires, is dependent on the right combination of solution chemistry and temperature. Similarly, the morphology of the individual nanocrystals during intracellular biomineralization of single nanocrystals has been attributed to the local environmental conditions, as well as the species of the micro-organism. Although there are obvious similarities, using the lessons from biomineralization to assist the laboratory synthesis of anisotropic pyrite nanostructures, and in the anticipation of environmental stability, requires a more detailed understanding of the role played by individual environmental parameters. In the present study we use a multi-scale thermodynamic model, combined with parameters obtained from first principles calculations, to investigate the formation and stability of pyrite nanorods as a function of temperature and chemical environment. The results of our systematic modeling of parameter space predict that the morphology of pyrite nanorods grown in the laboratory, or associated with biomineralization, is more likely to be a function of surface ligands and the biology of the organisms than a function of simpler environmental parameters such as temperature, pressure, concentration of sulfur and adsorption of water.

Recently a method termed constrained fluid lambda-integration was proposed for calculating the free energy difference between bulk solid and liquid reference states via the construction of a reversible thermodynamic integration path; coupling the two states in question. The present work shows how the application of the constrained fluid lambda-integration concept to solid/liquid slab simulation cells makes possible a generally applicable computer simulation methodology for calculating the free energy of any surface and/or surface defect structure, including surfaces requiring variations in surface atom or density number, such as the (1 x 5) Au(100) or (1 x 2) missing row Au(110) reconstructed surfaces or excess adatom/vacancy/step populated surfaces. We evaluate the methodology by calculating the free energy of various disordered high temperature Au(110) embedded atom method surfaces constrained to differing excess surface atom numbers [including those corresponding to the (1 x 2) missing row reconstructed surface] and obtained the interesting result that at 1000 K (as distinct from lower temperatures) the free energy difference between these surfaces is reduced to zero; a result which is consistent with an expected order-disorder phase transition for the Au(110) surface at such high temperatures.