Performance-limiting nanoscale trap clusters at grain junctions in halide perovskites.

Halide perovskite materials have promising performance characteristics for low-cost optoelectronic applications. Photovoltaic devices fabricated from perovskite absorbers have reached power conversion efficiencies above 25 per cent in single-junction devices and 28 per cent in tandem devices1,2. This strong performance (albeit below the practical limits of about 30 per cent and 35 per cent, respectively3) is surprising in thin films processed from solution at low-temperature, a method that generally produces abundant crystalline defects4. Although point defects often induce only shallow electronic states in the perovskite bandgap that do not affect performance5, perovskite devices still have many states deep within the bandgap that trap charge carriers and cause them to recombine non-radiatively. These deep trap states thus induce local variations in photoluminescence and limit the device performance6. The origin and distribution of these trap states are unknown, but they have been associated with light-induced halide segregation in mixed-halide perovskite compositions7 and with local strain8, both of which make devices less stable9. Here we use photoemission electron microscopy to image the trap distribution in state-of-the-art halide perovskite films. Instead of a relatively uniform distribution within regions of poor photoluminescence efficiency, we observe discrete, nanoscale trap clusters. By correlating microscopy measurements with scanning electron analytical techniques, we find that these trap clusters appear at the interfaces between crystallographically and compositionally distinct entities. Finally, by generating time-resolved photoemission sequences of the photo-excited carrier trapping process10,11, we reveal a hole-trapping character with the kinetics limited by diffusion of holes to the local trap clusters. Our approach shows that managing structure and composition on the nanoscale will be essential for optimal performance of halide perovskite devices.

Anisotropic Electron-Phonon Interactions in 2D Lead-Halide Perovskites.

Two-dimensional (2D) hybrid organic-inorganic metal halide perovskites offer enhanced stability for perovskite-based applications. Their crystal structure's soft and ionic nature gives rise to strong interaction between charge carriers and ionic rearrangements. Here, we investigate the interaction of photogenerated electrons and ionic polarizations in single-crystal 2D perovskite butylammonium lead iodide (BAPI), varying the inorganic lamellae thickness in the 2D single crystals. We determine the directionality of the transition dipole moments (TDMs) of the relevant phonon modes (in the 0.3-3 THz range) by the angle- and polarization-dependent THz transmission measurements. We find a clear anisotropy of the in-plane photoconductivity, with a ∼10% reduction along the axis parallel with the transition dipole moment of the most strongly coupled phonon. Detailed calculations, based on Feynman polaron theory, indicate that the anisotropy originates from directional electron-phonon interactions.

Band Gap Narrowing by Suppressed Lone-Pair Activity of Bi3.

Post-transition metal cations with a lone pair (ns2np0) electronic configuration such as Pb2+ and Bi3+ are important components of materials for solar-to-energy conversion. As in molecules like NH3, the lone pair is often stereochemically active in crystals, associated with distorted coordination environments of these cations. In the present study, we demonstrate that suppressed lone pair stereochemical activity can be used as a tool to enhance visible light absorption. Based on an orbital interaction model, we predict that a centrosymmetric environment of the cations limits the orbital interactions with anions, deactivates the lone pair, and narrows the band gap. A high-symmetry Bi3+ site is realized by isovalent substitutions with Y3+ by considering its similar ionic radius and absence of a lone pair. The quaternary photocatalyst Bi2YO4X is singled out as a candidate for Bi substitution from a survey of the coordination environments in Y-O compounds. The introduction of Bi3+ to the undistorted Y3+ site in Bi2YO4X results in a narrowed band gap, as predicted theoretically and confirmed experimentally. The orbital interaction controlled by site symmetry engineering offers a pathway for the further development of post-transition metal compounds for optoelectronic applications.

Dynamic Local Structure in Caesium Lead Iodide: Spatial Correlation and Transient Domains.

Metal halide perovskites are multifunctional semiconductors with tunable structures and properties. They are highly dynamic crystals with complex octahedral tilting patterns and strongly anharmonic atomic behavior. In the higher temperature, higher symmetry phases of these materials, several complex structural features are observed. The local structure can differ greatly from the average structure and there is evidence that dynamic 2D structures of correlated octahedral motion form. An understanding of the underlying complex atomistic dynamics is, however, still lacking. In this work, the local structure of the inorganic perovskite CsPbI3 is investigated using a new machine learning force field based on the atomic cluster expansion framework. Through analysis of the temporal and spatial correlation observed during large-scale simulations, it is revealed that the low frequency motion of octahedral tilts implies a double-well effective potential landscape, even well into the cubic phase. Moreover, dynamic local regions of lower symmetry are present within both higher symmetry phases. These regions are planar and the length and timescales of the motion are reported. Finally, the spatial arrangement of these features and their interactions are investigated and visualized, providing a comprehensive picture of local structure in the higher symmetry phases.

A Hole-Selective Self-Assembled Monolayer for Both Efficient Perovskite and Organic Solar Cells.

Self-assembled monolayers (SAMs) emerging as promising hole-selective layers (HSLs) are advantageous for facile processability, low cost, and minimal material consumption in the fabrication of both perovskite solar cells (PSCs) and organic solar cells (OSCs). However, owing to the different nature between perovskites and organic semiconductors, few SAMs were reported to effectively accommodate both PSCs and OSCs at the same time. In this regard, a universally applicable SAM that can accommodate both perovskites and organic semiconductors could be desirable for simplifying cell manufacturing, especially from an industrial perspective. In this work, we designed a SAM, TDPA-Cl by introducing chlorinated phenothiazine as the headgroup and linking with anchor phosphonic acid through a butyl chain. The resulting dense SAM was carefully characterized in terms of molecular bonding, surface morphology, and packing density, and its functions in OSCs and PSCs were discussed from the aspects of interactions with the absorber layer, energy level alignment, and charge-selective dipoles. The PM6:Y6-based OSCs with TDPA-Cl SAM as the HSL showed a superior performance to those with PEDOT:PSS. Furthermore, the universality was proved with an efficiency of 17.4% in the D18:Y6 system. In PSCs, the TDPA-Cl-based devices delivered a better performance of 22.4% than the PTAA-based devices (20.8%) with improved processability and reproducibility. This work represents a SAM with reasonably good compromise between the differing requirements of OSCs and PSCs.

Machine learning for molecular and materials science.

Here we summarize recent progress in machine learning for the chemical sciences. We outline machine-learning techniques that are suitable for addressing research questions in this domain, as well as future directions for the field. We envisage a future in which the design, synthesis, characterization and application of molecules and materials is accelerated by artificial intelligence.

Imperfections are not 0 K: free energy of point defects in crystals.

Defects determine many important properties and applications of materials, ranging from doping in semiconductors, to conductivity in mixed ionic-electronic conductors used in batteries, to active sites in catalysts. The theoretical description of defect formation in crystals has evolved substantially over the past century. Advances in supercomputing hardware, and the integration of new computational techniques such as machine learning, provide an opportunity to model longer length and time-scales than previously possible. In this Tutorial Review, we cover the description of free energies for defect formation at finite temperatures, including configurational (structural, electronic, spin) and vibrational terms. We discuss challenges in accounting for metastable defect configurations, progress such as machine learning force fields and thermodynamic integration to directly access entropic contributions, and bottlenecks in going beyond the dilute limit of defect formation. Such developments are necessary to support a new era of accurate defect predictions in computational materials chemistry.

Microscopic Origin of Electrochemical Capacitance in Metal-Organic Frameworks.

Electroconductive metal-organic frameworks (MOFs) have emerged as high-performance electrode materials for supercapacitors, but the fundamental understanding of the underlying chemical processes is limited. Here, the electrochemical interface of Cu3(HHTP)2 (HHTP = 2,3,6,7,10,11-hexahydroxytriphenylene) with an organic electrolyte is investigated using a multiscale quantum-mechanics/molecular-mechanics (QM/MM) procedure and experimental electrochemical measurements. Our simulations reproduce the observed capacitance values and reveals the polarization phenomena of the nanoporous framework. We find that excess charges mainly form on the organic ligand, and cation-dominated charging mechanisms give rise to greater capacitance. The spatially confined electric double-layer structure is further manipulated by changing the ligand from HHTP to HITP (HITP = 2,3,6,7,10,11-hexaiminotriphenylene). This minimal change to the electrode framework not only increases the capacitance but also increases the self-diffusion coefficients of in-pore electrolytes. The performance of MOF-based supercapacitors can be systematically controlled by modifying the ligating group.

Interplay of Static and Dynamic Disorder in the Mixed-Metal Chalcohalide Sn2SbS2I3.

Chalcohalide mixed-anion crystals have seen a rise in interest as "perovskite-inspired materials" with the goal of combining the ambient stability of metal chalcogenides with the exceptional optoelectronic performance of metal halides. Sn2SbS2I3 is a promising candidate, having achieved a photovoltaic power conversion efficiency above 4%. However, there is uncertainty over the crystal structure and physical properties of this crystal family. Using a first-principles cluster expansion approach, we predict a disordered room-temperature structure, comprising both static and dynamic cation disorder on different crystallographic sites. These predictions are confirmed using single-crystal X-ray diffraction. Disorder leads to a lowering of the bandgap from 1.8 eV at low temperature to 1.5 eV at the experimental annealing temperature of 573 K. Cation disorder tailoring the bandgap allows for targeted application or for the use in a graded solar cell, which when combined with material properties associated with defect and disorder tolerance, encourages further investigation into the group IV/V chalcohalide family for optoelectronic applications.

Correction: Lone pair driven anisotropy in antimony chalcogenide semiconductors.

Correction for 'Lone pair driven anisotropy in antimony chalcogenide semiconductors' by Xinwei Wang et al., Phys. Chem. Chem. Phys., 2022, 24, 7195-7202, https://doi.org/10.1039/D1CP05373F.

Switchable Electric Dipole from Polaron Localization in Dielectric Crystals.

Ferroelectricity in crystals is associated with the displacement of ions or rotations of polar units. Here we consider the dipole created by donor doping (D^{+}) and the corresponding bound polaron (e^{-}). A dipole of 6.15 Debye is predicted, from Berry phase analysis, in the Ruddlesden-Popper phase of Sr_{3}Ti_{2}O_{7}. A characteristic double-well potential is formed, which persists for high doping densities. The effective Hubbard U interaction can vary the defect state from metallic, a two-dimensional polaron, through to a zero-dimensional polaron. The ferroelectriclike behavior reported here is localized and distinct from conventional spontaneous lattice polarization.

Concluding remarks: emerging inorganic materials in thin-film photovoltaics.

A personal perspective is given on the major results, themes and trends from the Faraday Discussion on emerging materials for solar energy technologies. This covers research progress into adamantine semiconductors, the narrowing divide between materials modelling and measurements of solar cells, as well as the control of defects in novel absorber materials that include Cu2ZnSnS4, Zn3P2, Se, GeSe, Sb2Se3 and BaZrS3. This paper is adapted from a transcript of the closing lecture.

Impact of metastable defect structures on carrier recombination in solar cells.

The efficiency of a solar cell is often limited by electron-hole recombination mediated by defect states within the band gap of the photovoltaic (PV) semiconductor. The Shockley-Read-Hall (SRH) model considers a static trap that can successively capture electrons and holes. In reality however, true trap levels vary with both the defect charge state and local structure. Here we consider the role of metastable structural configurations in capturing electrons and holes, taking the tellurium interstitial in CdTe as an illustrative example. Consideration of the defect dynamics, and symmetry-breaking, changes the qualitative behaviour and activates new pathways for carrier capture. Our results reveal the potential importance of metastable defect structures in non-radiative recombination, in particular for semiconductors with anharmonic/ionic-covalent bonding, multinary compositions, low crystal symmetries or highly-mobile defects.

Lone pair driven anisotropy in antimony chalcogenide semiconductors.

Antimony sulfide (Sb2S3) and selenide (Sb2Se3) have emerged as promising earth-abundant alternatives among thin-film photovoltaic compounds. A distinguishing feature of these materials is their anisotropic crystal structures, which are composed of quasi-one-dimensional (1D) [Sb4X6]n ribbons. The interaction between ribbons has been reported to be van der Waals (vdW) in nature and Sb2X3 are thus commonly classified in the literature as 1D semiconductors. However, based on first-principles calculations, here we show that inter-ribbon interactions are present in Sb2X3 beyond the vdW regime. The origin of the anisotropic structures is related to the stereochemical activity of the Sb 5s lone pair according to electronic structure analysis. The impacts of structural anisotropy on the electronic, dielectric and optical properties relevant to solar cells are further examined, including the presence of higher dimensional Fermi surfaces for charge carrier transport. Our study provides guidelines for optimising the performance of Sb2X3-based photovoltaics via device structuring based on the underlying crystal anisotropy.

Role of ripples in altering the electronic and chemical properties of graphene.

Ripples of graphene are known to manipulate electronic and hydrogenation properties of graphitic materials. More detailed work is needed to elucidate the structure-property relationship of these systems. In this work, the density functional theory is used to compute the energy and electronic structure of the graphene models with respect to variable curvatures and hydrogen adsorption sites. The magnitude of finite bandgap opening depends on the orientation of ripples, and the hydrogen adsorption energy depends on the local curvature of graphene. An adsorbed hydrogen alters the local curvature, resulting in relatively weakened adsorption on the neighboring three sites, which gives a rationale to experimentally observed dynamic equilibrium stoichiometry (H:C = 1:4) of hydrogenated graphene. The surface diffusion transition state energy of adsorbed hydrogen is computed, which suggests that the Eley-Rideal surface recombination mechanism may be important to establish the dynamic equilibrium, instead of the commonly assumed Langmuir-Hinshelwood mechanism.

Machine learned calibrations to high-throughput molecular excited state calculations.

Understanding the excited state properties of molecules provides insight into how they interact with light. These interactions can be exploited to design compounds for photochemical applications, including enhanced spectral conversion of light to increase the efficiency of photovoltaic cells. While chemical discovery is time- and resource-intensive experimentally, computational chemistry can be used to screen large-scale databases for molecules of interest in a procedure known as high-throughput virtual screening. The first step usually involves a high-speed but low-accuracy method to screen large numbers of molecules (potentially millions), so only the best candidates are evaluated with expensive methods. However, use of a coarse first-pass screening method can potentially result in high false positive or false negative rates. Therefore, this study uses machine learning to calibrate a high-throughput technique [eXtended Tight Binding based simplified Tamm-Dancoff approximation (xTB-sTDA)] against a higher accuracy one (time-dependent density functional theory). Testing the calibration model shows an approximately sixfold decrease in the error in-domain and an approximately threefold decrease in the out-of-domain. The resulting mean absolute error of ∼0.14 eV is in line with previous work in machine learning calibrations and out-performs previous work in linear calibration of xTB-sTDA. We then apply the calibration model to screen a 250k molecule database and map inaccuracies of xTB-sTDA in chemical space. We also show generalizability of the workflow by calibrating against a higher-level technique (CC2), yielding a similarly low error. Overall, this work demonstrates that machine learning can be used to develop a cost-effective and accurate method for large-scale excited state screening, enabling accelerated molecular discovery across a variety of disciplines.

Giant Huang-Rhys Factor for Electron Capture by the Iodine Intersitial in Perovskite Solar Cells.

Improvement in the optoelectronic performance of halide perovskite semiconductors requires the identification and suppression of nonradiative carrier trapping processes. The iodine interstitial has been established as a deep level defect and implicated as an active recombination center. We analyze the quantum mechanics of carrier trapping. Fast and irreversible electron capture by the neutral iodine interstitial is found. The effective Huang-Rhys factor exceeds 300, indicative of the strong electron-phonon coupling that is possible in soft semiconductors. The accepting phonon mode has a frequency of 53 cm-1 and has an associated electron capture coefficient of 1 × 10-10 cm3 s-1. The inverse participation ratio is used to quantify the localization of phonon modes associated with the transition. We infer that suppression of octahedral rotations is an important factor to enhance defect tolerance.

Perovskite-inspired materials for photovoltaics and beyond-from design to devices.

Lead-halide perovskites have demonstrated astonishing increases in power conversion efficiency in photovoltaics over the last decade. The most efficient perovskite devices now outperform industry-standard multi-crystalline silicon solar cells, despite the fact that perovskites are typically grown at low temperature using simple solution-based methods. However, the toxicity of lead and its ready solubility in water are concerns for widespread implementation. These challenges, alongside the many successes of the perovskites, have motivated significant efforts across multiple disciplines to find lead-free and stable alternatives which could mimic the ability of the perovskites to achieve high performance with low temperature, facile fabrication methods. This Review discusses the computational and experimental approaches that have been taken to discover lead-free perovskite-inspired materials, and the recent successes and challenges in synthesizing these compounds. The atomistic origins of the extraordinary performance exhibited by lead-halide perovskites in photovoltaic devices is discussed, alongside the key challenges in engineering such high-performance in alternative, next-generation materials. Beyond photovoltaics, this Review discusses the impact perovskite-inspired materials have had in spurring efforts to apply new materials in other optoelectronic applications, namely light-emitting diodes, photocatalysts, radiation detectors, thin film transistors and memristors. Finally, the prospects and key challenges faced by the field in advancing the development of perovskite-inspired materials towards realization in commercial devices is discussed.

Multi-phonon proton transfer pathway in a molecular organic ferroelectric crystal.

While the majority of ferroelectrics research has been focused on inorganic ceramics, molecular ferroelectrics can also combine large spontaneous polarization with high Curie temperatures. However, the microscopic mechanism of their ferroelectric switching is not fully understood. We explore proton tautomerism in the prototypical case of croconic acid, C5O5H2. In order to determine how efficiently ferroelectricity in croconic acid is described in terms of its Γ-point phonon modes, the minimum energy path between its structural ground states is approximated by projection onto reduced basis sets formed from subsets of these modes. The potential energy curve along the minimum energy path was found to be sensitive to the order of proton transfer, which requires a large subset (⪆8) of the modes to be approximated accurately. Our findings suggest rules for the construction of effective Hamiltonians to describe proton transfer ferroelectrics.

Assessment of interstitial potentials for rapid prediction of absolute band energies in crystals.

Electronic band alignment is a demanding process for first-principles simulations, but an important factor in materials selection for applications including electrocatalysis and photoelectrochemistry. Here, we revisit a bulk alignment procedure, originally developed by Frensley and Kroemer, using modern computational tools. The electrostatic potential in the interstitial region, obtained from density functional theory, with four exchange correlation functionals, is used to predict the valence band offsets of 27 zinc blende semiconductors. The results are found to be in qualitative agreement with Frensley and Kroemer's original data. In addition to absolute electron energies, the possibility of extracting effective ionic charges is investigated and compared to Bader partial charges. With further developments, such a procedure may support rapid screening of the bulk ionization potential and electron affinity of crystals, as we illustrate with an extension to rock salt and perovskite structure types.