Torque about electrostatically charged spheres makes them more attractive.

The strength of interparticle interactions in a granular system controls how a collection of insulating particles flow, cohere and fragment. Forces due to electrostatic charging, particularly in free-fall or low gravity environments, can dominate the static and dynamic interactions with important implications for understanding natural and industrial processes. Here we show that shaking of homogeneous, spherical particles can result in a non-uniform surface charge distribution. The measured dipole moment and torque for each particle are found to be strongly correlated. However, our model shows that to predict the torque and force requires one to consider the full surface charge distribution. This overlooked torque is not only significant, but would amplify attractive interactions through particle reorientation.

Identification of Semiconductor Nanocrystals with Bright Ground-State Excitons.

While semiconductor nanocrystals provide versatile fluorescent materials for light-emitting devices, their brightness suffers from the "dark exciton"─an optically inactive electronic state into which nanocrystals relax before emitting. Recently, a theoretical mechanism, the Rashba effect, was discovered that can overcome this limitation by inverting the lowest-lying levels and creating a bright excitonic ground state. However, no methodology is available to systematically identify materials that exhibit this inversion, hindering the development of superbright nanocrystals and their devices. Here, based on a detailed understanding of the Rashba mechanism, we demonstrate a procedure that reveals previously unknown "bright-exciton" nanocrystals. We first define physical criteria to reduce over 500,000 known solids to 173 targets. Higher-level first-principles calculations then refine this list to 28 candidates. From these, we select five with high oscillator strength and develop effective-mass models to determine the nature of their lowest excitonic state. We confirm that four of the five solids yield bright ground-state excitons in nanocrystals. Thus, our results provide a badly needed roadmap for experimental investigation of bright-exciton nanomaterials.

Functional genomics of human clear cell sarcoma: genomic, transcriptomic and chemical biology landscape for clear cell sarcoma.

BACKGROUND: Systemic therapy for metastatic clear cell sarcoma (CCS) bearing EWSR1-CREB1/ATF1 fusions remains an unmet clinical need in children, adolescents, and young adults. METHODS: To identify key signaling pathway vulnerabilities in CCS, a multi-pronged approach was taken: (i) genomic and transcriptomic landscape analysis, (ii) integrated chemical biology interrogations, (iii) development of CREB1/ATF1 inhibitors, and (iv) antibody-drug conjugate testing (ADC). The first approach encompassed DNA exome and RNA deep sequencing of the largest human CCS cohort yet reported consisting of 47 patient tumor samples and 8 cell lines. RESULTS: Sequencing revealed recurrent mutations in cell cycle checkpoint, DNA double-strand break repair or DNA mismatch repair genes, with a correspondingly low to intermediate tumor mutational burden. DNA multi-copy gains with corresponding high RNA expression were observed in CCS tumor subsets. CCS cell lines responded to the HER3 ADC patritumab deruxtecan in a dose-dependent manner in vitro, with impaired long term cell viability. CONCLUSION: These studies of the genomic, transcriptomic and chemical biology landscape represent a resource 'atlas' for the field of CCS investigation and drug development. CHK inhibitors are identified as having potential relevance, CREB1 inhibitors non-dependence of CCS on CREB1 activity was established, and the potential utility of HER3 ADC being used in CCS is found.

Lineage tracing reveals fate bias and transcriptional memory in human B cells.

We combined single-cell transcriptomics and lineage tracing to understand fate choice in human B cells. Using the antibody sequences of B cells, we tracked clones during in vitro differentiation. Clonal analysis revealed a subset of IgM+ B cells which were more proliferative than other B-cell types. Whereas the population of B cells adopted diverse states during differentiation, clones had a restricted set of fates available to them; there were two times more single-fate clones than expected given population-level cell-type diversity. This implicated a molecular memory of initial cell states that was propagated through differentiation. We then identified the genes which had strongest coherence within clones. These genes significantly overlapped known B-cell fate determination programs, suggesting the genes which determine cell identity are most robustly controlled on a clonal level. Persistent clonal identities were also observed in human plasma cells from bone marrow, indicating that these transcriptional programs maintain long-term cell identities in vivo. Thus, we show how cell-intrinsic fate bias influences differentiation outcomes in vitro and in vivo.

Collective behavior of composite active particles.

We describe simulations of active Brownian particles carried out to explore how dynamics and clustering are influenced by particle shape. Our particles are composed of four disks, held together by springs, whose relative size can be varied. These composite objects can be tuned smoothly from having a predominantly concave to a convex surface. We show that even two of these composite particles can exhibit collective motion which modifies the effective Peclet number. We then investigate how particle geometry can be used to explain the phase behavior of many such particles.

Fluid dynamics and cell-bound Psl polysaccharide allows microplastic capture, aggregation and subsequent sedimentation by Pseudomonas aeruginosa in water.

Decades after incorporating plastics into consumer markets, research shows that these polymers have spread worldwide. Fragmentation of large debris leads to smaller particles, collectively called microplastics (MPs), which have become ubiquitous in aquatic environments. A fundamental aspect of understanding the implications of MP contamination on ecosystems is resolving the complex interactions of these artificial substrates with microbial cells. Using polystyrene microparticles as model polymers, we conducted an exploratory study where these interactions are quantitatively analyzed using an in vitro system consisting of single-bacterial species capturing and aggregating MPs in water. Here we show that the production of Psl exopolysaccharide by Pseudomonas aeruginosa (PA) does not alter MPs colloidal stability but plays a key role in microspheres adhesion to the cell surface. Further aggregation of MPs by PA cells depends on bacterial mobility and the presence of sufficient flow to prevent rapid sedimentation of early MP-PA assembles. Surprisingly, cells in MP-PA aggregates are not in a sessile state despite the production of Psl, enhancing the motility of the aggregates by an order of magnitude relative to passive diffusion. The generated data could inform the creation of predictive models that accurately describe the dynamics and influence of bacterial growth on plastics debris.

Dark and Bright Excitons in Halide Perovskite Nanoplatelets.

Semiconductor nanoplatelets (NPLs), with their large exciton binding energy, narrow photoluminescence (PL), and absence of dielectric screening for photons emitted normal to the NPL surface, could be expected to become the fastest luminophores amongst all colloidal nanostructures. However, super-fast emission is suppressed by a dark (optically passive) exciton ground state, substantially split from a higher-lying bright (optically active) state. Here, the exciton fine structure in 2-8 monolayer (ML) thick Csn - 1 Pbn Br3n + 1 NPLs is revealed by merging temperature-resolved PL spectra and time-resolved PL decay with an effective mass model taking quantum confinement and dielectric confinement anisotropy into account. This approach exposes a thickness-dependent bright-dark exciton splitting reaching 32.3 meV for the 2 ML NPLs. The model also reveals a 5-16 meV splitting of the bright exciton states with transition dipoles polarized parallel and perpendicular to the NPL surfaces, the order of which is reversed for the thinnest NPLs, as confirmed by TR-PL measurements. Accordingly, the individual bright states must be taken into account, while the dark exciton state strongly affects the optical properties of the thinnest NPLs even at room temperature. Significantly, the derived model can be generalized for any isotropically or anisotropically confined nanostructure.

Correction: Rashba exciton in a 2D perovskite quantum dot.

Correction for 'Rashba exciton in a 2D perovskite quantum dot' by Michael W. Swift et al., Nanoscale, 2021, 13, 16769-16780, DOI: 10.1039/D1NR04884H.

Rashba exciton in a 2D perovskite quantum dot.

The Rashba effect has been proposed to give rise to a bright exciton ground state in halide perovskite nanocrystals (NCs), resulting in very fast radiative recombination at room temperature and extremely fast radiative recombination at low temperature. In this paper we find the dispersion of the "Rashba exciton", i.e., the exciton whose bulk dispersion reflects large spin-orbit Rashba terms in the conduction and valence bands and thus has minima at non-zero quasi-momenta. Placing Rashba excitonsin quasi-2D cylindrical quantum dots, we calculate size-dependent levels of confined excitons and their oscillator transition strengths. We consider the implications of this model for two-dimensional hybrid organic-inorganic perovskites, discuss generalizations of this model to 3D NCs, and establish criteria under which a bright ground exciton state could be realized.

Understanding carbon contamination in the proton-conducting zirconates and cerates.

Carbon contamination is a significant concern for proton-conducting oxides in the cerate and zirconate family, particularly for BaCeO3. Here, we use first-principles calculations to evaluate carbon stability in SrCeO3, BaCeO3, SrZrO3, and BaZrO3. The cerates require more carbon-poor environments to prevent carbonate formation, though this requirement can be loosened through the use of more oxygen-poor growth conditions. Carbonate formation is not the only concern, however. We find that interstitial carbon has lower formation energies in the cerates relative to the zirconates, leading to higher carbon concentrations that compete with the desired oxygen vacancy formation. We also examine the mobility of carbon interstitials, finding that both migration barriers and binding energies to acceptors are lower in the cerates. As a result, the cerates are likely to degrade when exposed to carbon at operating temperatures. Our results show definitively why the cerates are less stable than the zirconates with respect to carbon and elucidate the mechanisms contributing to their instability, thereby helping to explain why alloying with zirconium will enhance their operational efficiency.

Modeling the electrical double layer at solid-state electrochemical interfaces.

Models of the electrical double layer (EDL) at electrode/liquid-electrolyte interfaces no longer hold for all-solid-state electrochemistry. Here we show a more general model for the EDL at a solid-state electrochemical interface based on the Poisson-Fermi-Dirac equation. By combining this model with density functional theory predictions, the interconnected electronic and ionic degrees of freedom in all-solid-state batteries, including the electronic band bending and defect concentration variation in the space-charge layer, are captured self-consistently. Along with a general mathematical solution, the EDL structure is presented in various materials that are thermodynamically stable in contact with a lithium metal anode: the solid electrolyte Li7La3Zr2O12 (LLZO) and the solid interlayer materials LiF, Li2O and Li2CO3. The model further allows design of the optimum interlayer thicknesses to minimize the electrostatic barrier for lithium ion transport at relevant solid-state battery interfaces.

Optimization of the Reax force field for the lithium-oxygen system using a high fidelity charge model.

Studies using molecular dynamics (MD) have long struggled to simulate the failure modes of materials, predicting unrealistically high ductility and failing to capture brittle fracture. The primary cause of this shortcoming is an inadequate description of bond breaking. While reactive force fields such as ReaxFF show improvements compared to traditional force fields, the charge models used yield unphysical partial charges, especially during dissociation of ionic bonds. This flaw may be remedied by using the atom-condensed Kohn-Sham density functional theory (DFT) approximated to a second order (ACKS2) charge model for determining partial charges. In this work, we present a new ACKS2-enabled Reax force field for fracture simulations of lithium oxide systems, which was obtained by training against an extensive set of DFT, multireference configuration interaction (MRCI), and MRCI+Q reference data using genetic optimization techniques. This new force field significantly improves the bond breaking behavior, but still cannot fully capture the brittle fracture in MD simulations, suggesting more research is needed to improve simulation of brittle fracture.

Wavelet scattering networks for atomistic systems with extrapolation of material properties.

The dream of machine learning in materials science is for a model to learn the underlying physics of an atomic system, allowing it to move beyond the interpolation of the training set to the prediction of properties that were not present in the original training data. In addition to advances in machine learning architectures and training techniques, achieving this ambitious goal requires a method to convert a 3D atomic system into a feature representation that preserves rotational and translational symmetries, smoothness under small perturbations, and invariance under re-ordering. The atomic orbital wavelet scattering transform preserves these symmetries by construction and has achieved great success as a featurization method for machine learning energy prediction. Both in small molecules and in the bulk amorphous LiαSi system, machine learning models using wavelet scattering coefficients as features have demonstrated a comparable accuracy to density functional theory at a small fraction of the computational cost. In this work, we test the generalizability of our LiαSi energy predictor to properties that were not included in the training set, such as elastic constants and migration barriers. We demonstrate that statistical feature selection methods can reduce over-fitting and lead to remarkable accuracy in these extrapolation tasks.

Diverse homeostatic and immunomodulatory roles of immune cells in the developing mouse lung at single cell resolution.

At birth, the lungs rapidly transition from a pathogen-free, hypoxic environment to a pathogen-rich, rhythmically distended air-liquid interface. Although many studies have focused on the adult lung, the perinatal lung remains unexplored. Here, we present an atlas of the murine lung immune compartment during early postnatal development. We show that the late embryonic lung is dominated by specialized proliferative macrophages with a surprising physical interaction with the developing vasculature. These macrophages disappear after birth and are replaced by a dynamic mixture of macrophage subtypes, dendritic cells, granulocytes, and lymphocytes. Detailed characterization of macrophage diversity revealed an orchestration of distinct subpopulations across postnatal development to fill context-specific functions in tissue remodeling, angiogenesis, and immunity. These data both broaden the putative roles for immune cells in the developing lung and provide a framework for understanding how external insults alter immune cell phenotype during a period of rapid lung growth and heightened vulnerability.

Reduced Thermodynamic Description of Phase Separation in a Quasi-One-Dimensional Granular Gas.

We describe simulations of a quasi-one-dimensional, vibrated granular gas which exhibits an apparent phase separation into a liquidlike phase and a gaslike phase. In thermal equilibrium, such a phase separation in one dimension is prohibited by entropic considerations. We propose that the granular gas minimizes a function of the conserved mechanical variables alone: the particle number and volume. Simulations in small cells can be used to extract the equation of state and predict the coexisting pressure and densities, as confirmation of the minimization principle. Fluctuations in the system manifest themselves as persistent density waves but they do not destroy the phase-separated state.

First-Principles Prediction of Potentials and Space-Charge Layers in All-Solid-State Batteries.

As all-solid-state batteries (SSBs) develop as an alternative to traditional cells, a thorough theoretical understanding of driving forces behind battery operation is needed. We present a fully first-principles-informed model of potential profiles in SSBs and apply the model to the Li/LiPON/Li_{x}CoO_{2} system. The model predicts interfacial potential drops driven by both electron transfer and Li^{+} space-charge layers that vary with the SSB's state of charge. The results suggest a lower electronic ionization potential in the solid electrolyte favors Li^{+} transport, leading to higher discharge power.

Posner molecules: from atomic structure to nuclear spins.

We investigate "Posner molecules", calcium phosphate clusters with chemical formula Ca9(PO4)6. Originally identified in hydroxyapatite, Posner molecules have also been observed as free-floating molecules in vitro. The formation and aggregation of Posner molecules have important implications for bone growth, and may also play a role in other biological processes such as the modulation of calcium and phosphate ion concentrations within the mitochondrial matrix. In this work, we use a first-principles computational methodology to study the structure of Posner molecules, their vibrational spectra, their interactions with other cations, and the process of pairwise bonding. Additionally, we show that the Posner molecule provides an ideal environment for the six constituent 31P nuclear spins to obtain very long spin coherence times. In vitro, the spins could provide a platform for liquid-state nuclear magnetic resonance quantum computation. In vivo, the spins may have medical imaging applications. The spins have also been suggested as "neural qubits" in a proposed mechanism for quantum processing in the brain.

The minimization of mechanical work in vibrated granular matter.

Experiments and computer simulations are carried out to investigate phase separation in a granular gas under vibration. The densities of the dilute and the dense phase are found to follow a lever rule and obey an equation of state. Here we show that the Maxwell equal-areas construction predicts the coexisting pressure and binodal densities remarkably well, even though the system is far from thermal equilibrium. This construction can be linked to the minimization of mechanical work associated with density fluctuations without invoking any concept related to equilibrium-like free energies.

Propulsion of a Two-Sphere Swimmer.

We describe experiments and simulations demonstrating the propulsion of a neutrally buoyant swimmer that consists of a pair of spheres attached by a spring, immersed in a vibrating fluid. The vibration of the fluid induces relative motion of the spheres which, for sufficiently large amplitudes, can lead to motion of the center of mass of the two spheres. We find that the swimming speed obtained from both experiment and simulation agree and collapse onto a single curve if plotted as a function of the streaming Reynolds number, suggesting that the propulsion is related to streaming flows. There appears to be a critical onset value of the streaming Reynolds number for swimming to occur. We observe a change in the streaming flows as the Reynolds number increases, from that generated by two independent oscillating spheres to a collective flow pattern around the swimmer as a whole. The mechanism for swimming is traced to a strengthening of a jet of fluid in the wake of the swimmer.

Configurable lipid membrane gradients quantify diffusion, phase separations and binding densities.

Single-experiment analysis of phospholipid compositional gradients reveals diffusion coefficients, phase separation parameters, and binding densities as a function of localized lipid mixture. Compositional gradients are formed by directed self assembly where rapid-prototyping techniques (i.e., additive manufacturing or laser-cutting) prescribe lipid geometries that self-spread, heal and mix by diffusion.