Bandgap Transition of 2H Transition Metal Dichalcogenides: Predictive Tuning via Inherent Interface Coupling and Strain

Phase transitions within two-dimensional transition metal dichalcogenides (TMD) promise new possibilities for engineering their properties. Using first-principles density functional theory (DFT) calculations, we systematically examined the interfacial electronic coupling between the 2H phase monolayer with its polymorphic phases in several group IV TMD, i.e., MoS₂ (MoSe₂) and WS₂ (WSe₂), inherent bilayer heterostructures. It is found that the interface coupling, augmented by in-plane strain, can greatly modify the band structure of the 2H phase to induce bandgap transition (either indirect-to-direct or direct-to-indirect). Moreover, the effects of strain on the band structure can be well understood and predicted within the framework of deformation potential theory. The present study provides important insights toward engineering optoelectronic properties of TMD-based devices

First-Principles Study of Dislocation Slips in Impurity-Doped Graphene

Employing density-functional theory (DFT) calculations, the generalized-stacking-fault energy (GSFE) curves along two crystallographic slips, glide and shuffle, for both pristine graphene and impurity of boron (B) or nitrogen (N) doped graphene were examined. The effects of B and N doping on the GSFE were clarified and correlated with local electron interactions and bonding configurations. The GSFE data were then used to analyze dislocation dipole and core structure and subsequently combined with the Peierls–Nabarro (P–N) model to examine the role of doping on several key characteristics of dislocations in graphene. We showed that the GSFE curve may be significantly altered by the presence of dopants, which subsequently leads to profound modulations of dislocation properties, such as increasing spontaneous pair-annihilation distance and reducing resistance to dislocation slip. Our results indicate that doping can play an important role in controlling dislocation density and microscopic plasticity in graphene, thereby providing critical insights for dopant-mediated defect engineering in graphene

Mitigating the High-Charge Detrimental Phase Transformation in LiNiO₂ Using Doping Engineering

Cobalt-free layered LiNiO2 has gained increased interest due to the scarcity and high cost of cobalt. However, LiNiO2 suffers from poor cycling stability, which is mainly due to oxygen loss and structural instability, especially when operating at high voltages. Herein, we present a doping strategy to mitigate the detrimental O3-to-O1 phase transformation in LiNiO2 from first-principles calculations. Temperature–composition phase diagrams of pristine and doped Li1–xNiO2 are obtained using a cluster-expansion and Monte Carlo simulation approach. We investigate the effects of dopant oxidation states, sizes, and concentrations on the dopant distribution in LiNi1–yMyO2 (M = Sb, Ti, Si, Al, and Mg) as well as the phase transitions during delithiation. We find that introducing high-valence dopants with ionic radii similar to that of Ni3+ into LiNiO2 stabilizes the O3-phase cathode bulk structure at high charge. Our results provide a general guidance on using doping engineering to realize Ni-rich, Co-free cathodes for lithium-ion batteries

Anchorage- independent growth in the presence and absence of BPA.

<p>*<i>p</i> values were computed using t-tests.</p

Scatter plots of LnBPA.

<p>Urine BPA levels are associated with PCa. The log-transformed BPA is referred to as LnBPA. Values in graph are mean ± SD of LnBPA. (A) Urine BPA levels are higher in PCa patients than in non-PCa patients. Means of LnBPA  = 1.75±1.97 in PCa (blue, n = 27) vs. 0.35±2.14 in non-PCa (red, n = 33), <i>p</i> = 0.012. (B) LnBPA in PCa vs. LnBPA in non-PCa, stratified by age = 65. Urine BPA levels are significantly higher in young PCa patients than in the respective non-PCa patients only in the age group <65 years old; <i>p</i> = 0.006. (C) Linear regression analyses of Serum PSA vs. LnBPA in patients <65 years old only (n = 30). Blue solid squares represent PCa patients; red inverse-circles represent non-PCa patients. Blue and red solid lines represent their regression lines, respectively. (D) Comparison of the geometric mean of BPA in PCa and non-PCa groups. The geometric mean (Geo) is defined as the exponential of the mean of LnBPA. Values are geometric means (95% CI) of BPA in unit of µg/g creatinine.</p

Cells grown in the absence and presence of 0.1-independent growth.

<p>Representative pictures of colonies after 2 weeks of incubation in agar. C4-2 cells in the presence of 0.1 nM BPA formed larger colonies (B, B′, 100–1200 µm diameter) compared with those grown in the absence of BPA (A, A′, 50–400 µm diameter).</p

Summary of baseline characteristics (n = 60).

<p>*Numerical variables are summarized using mean ± standard deviation (SD). Categorical variables are summarized using frequency (in %).</p>†<p><i>p</i> values are calculated from t-tests.</p><p>#Serum PSA significantly rose during follow-up.</p

Fold change in the percentage of cells with centrosomal amplification in presence of 100

<p>*Fold change is defined as % of cells with abnormal centrosomes at 0.1 nM BPA/% cells with abnormal centrosomes in untreated cells.</p>†<p><i>Post hoc</i> comparisons were performed under a fixed effect model and adjusted using Bonferroni's methods. Only the p-values of comparing NPrEC-1 to other cell lines are presented. Other comparisons between the cell lines were not statistically different.</p

Low doses of BPA have an adverse effect on centrosome numbers in prostate cancer cells.

<p>The cell lines NPrEC, RWPE1, LNCaP, C4-2, 22Rv1, and PC3 were treated with medium containing 10% CSS plus 0, 0.01 nM, 0.1 nM, 1 nM, 10 nM and 100 nM BPA for 72 h. Cells were fixed with 100% cold methanol and immunostained for centrosomes and nuclei. The number of centrosomes per cell was scored by fluorescence microscopy. The results are shown as an average determined from five separate experiments. The scatter plot was generated of the percentage of cells with an abnormal number of centrosomes in response to BPA. Analyses was performed using a fixed effect model for each cell line. <i>Post hoc</i> comparisons of means were adjusted using Bonferroni's tests. The fold change is the percentage of cells with abnormal centrosomes at 0.1 nM BPA/the percentage of cells with abnormal centrosomes at 0 nM BPA.</p

Summary of LnBPA (log-transformed BPA) values and cancer-related characteristics (n = 27) for PCa patients.

<p>Summary of LnBPA (log-transformed BPA) values and cancer-related characteristics (n = 27) for PCa patients.</p