Hidden spontaneous polarisation in the chalcohalide photovoltaic absorber Sn2SbS2I3

Perovskite-inspired materials aim to replicate the optoelectronic performance of lead-halide perovskites, while eliminating issues with stability and toxicity. Chalcohalides of group IV/V elements have attracted attention due to enhanced stability provided by stronger metal-chalcogen bonds, alongside compositional flexibility and ns2 lone pair cations – a performance-defining feature of halide perovskites. Following the experimental report of solution-grown tin-antimony sulfoiodide (Sn2SbS2I3) solar cells, with power conversion efficiencies above 4%, we assess the structural and electronic properties of this emerging photovoltaic material. We find that the reported centrosymmetric Cmcm crystal structure represents an average over multiple polar Cmc21 configurations. The instability is confirmed through a combination of lattice dynamics and molecular dynamics simulations. We predict a large spontaneous polarisation of 37 μC cm−2 that could be active for electron–hole separation in operating solar cells. We further assess the radiative efficiency limit of this material, calculating ηmax > 30% for film thicknesses t > 0.5 μm

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

Identifying the ground state structures of point defects in solids

Point defects are a universal feature of crystals. Their identification is addressed by combining experimental measurements with theoretical models. The standard modelling approach is, however, prone to missing the ground state atomic configurations associated with energy-lowering reconstructions from the idealised crystallographic environment. Missed ground states compromise the accuracy of calculated properties. To address this issue, we report an approach to navigate the defect configurational landscape using targeted bond distortions and rattling. Application of our workflow to eight materials (CdTe, GaAs, Sb2S3, Sb2Se3, CeO2, In2O3, ZnO, anatase-TiO2) reveals symmetry breaking in each host crystal that is not found via conventional local minimisation techniques. The point defect distortions are classified by the associated physico-chemical factors. We demonstrate the impact of these defect distortions on derived properties, including formation energies, concentrations and charge transition levels. Our work presents a step forward for quantitative modelling of imperfect solids

Low electronic conductivity of Li7La3Zr2 O12 solid electrolytes from first principles

Lithium-rich garnets such as Li7La3Zr2O12 (LLZO) are promising solid electrolytes with potential application in all-solid-state batteries that use lithium-metal anodes. The practical use of garnet electrolytes is limited by pervasive lithium-dendrite growth, which leads to short-circuiting and cell failure. One proposed mechanism of lithium-dendrite growth is the direct reduction of lithium ions to lithium metal within the electrolyte, and lithium garnets have been suggested to be particularly susceptible to this dendrite-growth mechanism due to high electronic conductivities relative to other solid electrolytes. The electronic conductivities of LLZO and other lithium-garnet solid electrolytes, however, are not yet well characterized. Here, we present a general scheme for calculating the intrinsic electronic conductivity of a nominally insulating material under variable synthesis conditions from first principles, and apply this to the prototypical lithium-garnet LLZO. Our model predicts that under typical battery operating conditions, electron and hole mobilities are low (<1cm2V-1s-1), and bulk electron and hole carrier concentrations are negligible, irrespective of initial synthesis conditions or dopant levels. These results suggest that the bulk electronic conductivity of LLZO is not sufficiently high to cause bulk lithium-dendrite growth during cell operation, and that any non-negligible electronic conductivity in lithium garnet samples is likely due to extended defects or surface contributions

Chemical Trends in the Lattice Thermal Conductivity of Li(Ni, Mn, Co)O₂ (NMC) Battery Cathodes

While the transport of ions and electrons in conventional Li-ion battery cathode materials is well understood, our knowledge of the phonon (heat) transport is still in its infancy. We present a first-principles theoretical investigation of the chemical trends in the phonon frequency dispersion, mode lifetimes, and thermal conductivity in the series of layered lithium transition-metal oxides Li(NixMnyCoz)O2 (x + y + z = 1). The oxidation and spin states of the transition metal cations are found to strongly influence the structural dynamics. Calculations of the thermal conductivity show that LiCoO2 has highest average conductivity of 45.9 W·m–1·K–1 at T = 300 K and the largest anisotropy, followed by LiMnO2 with 8.9 W·m–1·K–1 and LiNiO2 with 6.0 W·m–1·K–1. The much lower thermal conductivity of LiMnO2 and LiNiO2 is found to be due to 1–2 orders of magnitude shorter phonon lifetimes. We further model the properties of binary and ternary transition metal combinations to examine the possible effects of mixing on the thermal transport. These results serve as a guide to ongoing work on the design of multicomponent battery electrodes with more effective thermal management

Recurrent Uterine Cervical Carcinoma: Spectrum of Imaging Findings

Uterine cervical carcinoma is one of the most common malignant tumors occurring in females. After primary treatment, patients are usually followed up with CT or MRI and the findings of these modalities may be the first sign of recurrent disease. Because earlier additional treatment by chemotherapy or radiation therapy may improve the prognosis, the early detection of recurrent cervical carcinoma is clinically important. In this article, we review the CT and MR imaging findings of recurrent uterine cervical carcinoma, and assign them to one of four groups: a) recurrence at the primary site, involving the intrapelvic organs, b) extension to the pelvic side-wall, c) metastases to pelvic and extrapelvic lymph nodes, or d) metastases to distant organs. A further contribution of CT and MR imaging is the detection of hydronephrosis due to ureteral obstruction. The cases in each group are illustrated and discussed, and since an awareness of the spectrum of imaging findings of recurrent cervical carcinoma is likely to lead to its early detection, radiologists should be familiar with the information presented

Polymorph exploration of bismuth stannate using first-principles phonon mode mapping

Accurately modelling polymorphism in crystalline solids remains a key challenge in computational chemistry. In this work, we apply a theoretically-rigorous phonon mode-mapping approach to understand the polymorphism in the ternary metal oxide Bi2Sn2O7. Starting from the high-temperature cubic pyrochlore aristotype, we systematically explore the structural potential-energy surface and recover the two known low-temperature phases alongside three new metastable phases, together with the transition pathways connecting them. This first-principles lattice-dynamics method is completely general and provides a practical means to identify and characterise the stable polymorphs and phase transitions in materials with complex crystal structures

Rapid recombination by cadmium vacancies in CdTe

CdTe is currently the largest thin-film photovoltaic technology. Non-radiative electron–hole recombination reduces the solar conversion efficiency from an ideal value of 32% to a current champion performance of 22%. The cadmium vacancy (VCd) is a prominent acceptor species in p-type CdTe; however, debate continues regarding its structural and electronic behavior. Using ab initio defect techniques, we calculate a negative-U double-acceptor level for VCd, while reproducing the VCd1– hole–polaron, reconciling theoretical predictions with experimental observations. We find the cadmium vacancy facilitates rapid charge-carrier recombination, reducing maximum power-conversion efficiency by over 5% for untreated CdTe—a consequence of tellurium dimerization, metastable structural arrangements, and anharmonic potential energy surfaces for carrier capture