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JournalISSN: 2041-6520

Chemical Science 

Royal Society of Chemistry
About: Chemical Science is an academic journal published by Royal Society of Chemistry. The journal publishes majorly in the area(s): Medicine & Chemistry. It has an ISSN identifier of 2041-6520. It is also open access. Over the lifetime, 12341 publications have been published receiving 508940 citations.


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Journal ArticleDOI
TL;DR: In this paper, a qualitative method for predicting the ligand architectures that will generate magnetic anisotropy for a variety of f-element ions is presented to guide the design of stronger single-molecule magnets incorporating the f-elements.
Abstract: Scientists have long employed lanthanide elements in the design of materials with extraordinary magnetic properties, including the strongest magnets known, SmCo5 and Nd2Fe14B. The properties of these materials are largely a product of fine-tuning the interaction between the lanthanide ion and the crystal lattice. Recently, synthetic chemists have begun to utilize f-elements—both lanthanides and actinides—for the construction of single-molecule magnets, resulting in a rapid expansion of the field. The desirable magnetic characteristics of the f-elements are contingent upon the interaction between the single-ion electron density and the crystal field environment in which it is placed. This interaction leads to the single-ion anisotropies requisite for strong single-molecule magnets. Therefore, it is of vital importance to understand the particular crystal field environments that could lead to maximization of the anisotropy for individual f-elements. Here, we summarize a qualitative method for predicting the ligand architectures that will generate magnetic anisotropy for a variety of f-element ions. It is hoped that this simple model will serve to guide the design of stronger single-molecule magnets incorporating the f-elements.

1,663 citations

Journal ArticleDOI
TL;DR: A reversible photo-induced instability has been found in mixed-halide photovoltaic perovskites that limits the open circuit voltage in solar cells.
Abstract: We report on reversible, light-induced transformations in (CH3NH3)Pb(BrxI1−x)3. Photoluminescence (PL) spectra of these perovskites develop a new, red-shifted peak at 1.68 eV that grows in intensity under constant, 1-sun illumination in less than a minute. This is accompanied by an increase in sub-bandgap absorption at ∼1.7 eV, indicating the formation of luminescent trap states. Light soaking causes a splitting of X-ray diffraction (XRD) peaks, suggesting segregation into two crystalline phases. Surprisingly, these photo-induced changes are fully reversible; the XRD patterns and the PL and absorption spectra revert to their initial states after the materials are left for a few minutes in the dark. We speculate that photoexcitation may cause halide segregation into iodide-rich minority and bromide-enriched majority domains, the former acting as a recombination center trap. This instability may limit achievable voltages from some mixed-halide perovskite solar cells and could have implications for the photostability of halide perovskites used in optoelectronics.

1,549 citations

Journal ArticleDOI
TL;DR: A large scale benchmark for molecular machine learning consisting of multiple public datasets, metrics, featurizations and learning algorithms.
Abstract: Molecular machine learning has been maturing rapidly over the last few years. Improved methods and the presence of larger datasets have enabled machine learning algorithms to make increasingly accurate predictions about molecular properties. However, algorithmic progress has been limited due to the lack of a standard benchmark to compare the efficacy of proposed methods; most new algorithms are benchmarked on different datasets making it challenging to gauge the quality of proposed methods. This work introduces MoleculeNet, a large scale benchmark for molecular machine learning. MoleculeNet curates multiple public datasets, establishes metrics for evaluation, and offers high quality open-source implementations of multiple previously proposed molecular featurization and learning algorithms (released as part of the DeepChem open source library). MoleculeNet benchmarks demonstrate that learnable representations are powerful tools for molecular machine learning and broadly offer the best performance. However, this result comes with caveats. Learnable representations still struggle to deal with complex tasks under data scarcity and highly imbalanced classification. For quantum mechanical and biophysical datasets, the use of physics-aware featurizations can be more important than choice of particular learning algorithm.

1,277 citations

Journal ArticleDOI
TL;DR: Dialkylbiaryl phosphines are a valuable class of ligand for Pd-catalyzed amination reactions and have been applied in a range of contexts and this review attempts to aid the reader in the selection of the best choice of reaction conditions and ligand.
Abstract: Dialkylbiaryl phosphines are a valuable class of ligand for Pd-catalyzed amination reactions and have been applied in a range of contexts. This perspective attempts to aid the reader in the selection of the best choice of reaction conditions and ligand of this class for the most commonly encountered and practically important substrate combinations.

1,241 citations

Journal ArticleDOI
TL;DR: Amorphous molybdenum sulfide films are efficient hydrogen evolution catalysts in water as mentioned in this paper, achieving significant geometric current densities at low overpotentials (e.g., 15 mA cm−2 at η = 200 mV) using these catalysts.
Abstract: Amorphous molybdenum sulfide films are efficient hydrogen evolution catalysts in water. The films are prepared via simple electro-polymerization procedures and are characterized by XPS, electron microscopy and electronic absorption spectroscopy. Whereas the precatalysts could be MoS3 or MoS2, the active form of the catalysts is identified as amorphous MoS2. Significant geometric current densities are achieved at low overpotentials (e.g., 15 mA cm−2 at η = 200 mV) using these catalysts. The catalysis is compatible with a wide range of pHs (e.g., 0 to 13). The current efficiency for hydrogen production is quantitative. A 40 mV Tafel slope is observed, suggesting a rate-determining ion+atom step. The turnover frequency per active site is calculated. The amorphous molybdenum sulfide films are among the most active non-precious hydrogen evolution catalysts.

1,197 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
2023856
20221,779
20211,590
20201,418
20191,283
20181,033