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At least 325 records · Page 18

Dependence of Convective Cloud Microphysical Properties on Environmental Conditions during the TRACER and ESCAPE Field Campaigns: A Synergistic Approach of Observations, Machine Learning and Parcel Models

The sensitivity of convective clouds to aerosols and their interactions with environment, combined with limited observational constraints in parameterizations, introduces significant uncertainties in atmospheric models. Here, this study investigates the dependence of convective cloud microphysical properties on environmental conditions using a synergistic approach that combines unique observations from the TRACER and ESCAPE field campaigns, machine learning techniques, and parcel model simulations with a super-droplet microphysics scheme. A random forest algorithm identifies in-situ vertical velocity (w), temperature (T), and surface fine-mode aerosol mass concentration as the three most important environmental conditions influencing cloud properties including liquid water content (LWC), number concentration for particles with D max < 50 μm (N c ,<50), 50 μm ≤ D max ≤ 3000 μm (N c,50–3000 ), and droplet effective diameter (D e ). Results show that LWC, N c,<50 , and N c,50–3000 significantly increase with w in updrafts. Across w bins, as T decreases, LWC, D e , and N c,50–3000 increase, while N c,<50 decreases, which are closely linked to the distance above cloud bases. Warmer cloud bases yield higher LWC, greater N c,50–3000 , and smaller N c,<50 , while polluted environments produce greater N c,<50 . Parcel model simulations successfully replicate these observed dependencies. The simulation results indicate that warmer cloud bases enhance condensation generating larger droplets, and differences in droplet sizes are then amplified through collision-coalescence, resulting in a greater N c,50–3000 . Polluted conditions result in a greater N c,<50 primarily due to enhanced cloud condensation nuclei activation despite increased collision-coalescence rates compared to pristine conditions. This study provides observed quantitative patterns characterizing cloud microphysical properties as a function of key environmental parameters, offering valuable constraints for improving physics parameterizations and numerical models.

54 ENVIRONMENTAL SCIENCES↗

Observing Profiles of Derived Kinematic Field Quantities Using a Network of Profiling Sites

Abstract Observations of thermodynamic and kinematic parameters associated with derivatives of the thermodynamics and wind fields, namely, advection, vorticity, divergence, and deformation, can be obtained by applying Green’s theorem to a network of observing sites. The five nodes that comprise the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) profiling network, spaced 50–80 km apart, are used to obtain measurements of these parameters over a finite region. To demonstrate the applicability of this technique at this location, it is first applied to gridded model output from the High-Resolution Rapid Refresh (HRRR) numerical weather prediction model, using profiles from the locations of ARM network sites, so that values calculated from this method can be directly compared to finite difference calculations. Good agreement is found between both approaches as well as between the model and values calculated from the observations. Uncertainties for the observations are obtained via a Monte Carlo process in which the profiles are randomly perturbed in accordance with their known error characteristics. The existing size of the ARM network is well suited to capturing these parameters, with strong correlations to model values and smaller uncertainties than a more closely spaced network, yet it is small enough that it avoids the tendency for advection to go to zero over a large area.

54 ENVIRONMENTAL SCIENCES↗

Long-Term Science Goals with In Situ Observations at the Sun-Earth Lagrange Point L4

The Korean heliospheric community, led by the Korea Astronomy and Space Science Institute (KASI), is currently assessing the viability of deploying a spacecraft at the Sun-Earth Lagrange Point L4 in collaboration with National Aeronautics and Space Administration (NASA). The aim of this mission is to utilize a combination of remote sensing and in situ instruments for comprehensive observations, complementing the capabilities of the L1 and L5 observatories. The paper outlines long-term scientific objectives, underscoring the significance of multi-point in-situ observations to better understand critical heliospheric phenomena. These include coronal mass ejections, magnetic flux ropes, heliospheric current sheets, kinetic waves and instabilities, suprathermal electrons and solar energetic particle events, as well as remote detection of solar radiation phenomena. Furthermore, the mission’s significance in advancing space weather prediction and space radiation exposure assessment models through the integration of L4 observations is discussed. This article is concluded with an emphasis on the potential of L4 observations to propel advancements in heliospheric science.

79 ASTRONOMY AND ASTROPHYSICS↗

Using radar observations to evaluate 3-D radar echo structure simulated by the Energy Exascale Earth System Model (E3SM) version 1

Abstract. The Energy Exascale Earth System Model (E3SM) developed by the Department of Energy has a goal of addressing challenges in understanding the global water cycle. Success depends on correct simulation of cloud and precipitation elements. However, lack of appropriate evaluation metrics has hindered the accurate representation of these elements in general circulation models. We derive metrics from the three-dimensional data of the ground-based Next-Generation Radar (NEXRAD) network over the US to evaluate both horizontal and vertical structures of precipitation elements. We coarsened the resolution of the radar observations to be consistent with the model resolution and improved the coupling of the Cloud Feedback Model Intercomparison Project Observation Simulator Package (COSP) and E3SM Atmospheric Model Version 1 (EAMv1) to obtain the best possible model output for comparison with the observations. Three warm seasons (2014–2016) of EAMv1 simulations of 3-D radar reflectivity features at an hourly scale are evaluated. A general agreement in domain-mean radar reflectivity intensity is found between EAMv1 and NEXRAD below 4 km altitude; however, the model underestimates reflectivity over the central US, which suggests that the model does not capture the mesoscale convective systems that produce much of the precipitation in that region. The shape of the model-estimated histogram of subgrid-scale reflectivity is improved by correcting the microphysical assumptions in COSP. Different from previous studies that evaluated modeled cloud top height, we find the model severely underestimates radar reflectivity at upper levels – the simulated echo top height is about 5 km lower than in observations – and this result is not changed by tuning any single physics parameter. For more accurate model evaluation, a higher-order consistency between the COSP and the host model is warranted in future studies.

58 GEOSCIENCES↗

2.2.5.401 - Ocean Observing Prize

The Powering the Blue Economy: Ocean Observing Prize is a $2.4M contest that challenges innovators to develop solutions that integrate marine renewable energy with ocean observation platforms to revolutionize our ability to monitor, manage, and understand the ocean. Competitors are challenged to design, build, and test novel, wave-powered, self-charging autonomous underwater vehicle (AUV) systems that could be suitable for a 6-month deployment in the Atlantic Ocean to monitor hurricane formation. Through engagement with the end user ocean observing community, the team identified challenges in a lack of data on storm intensity, endangering coastal communities. This challenge could be addressed by collecting data before, during, and after a hurricane develops and strengthens at sea. Amassing this data, however, requires an ocean observing system that can be deployed at sea for long periods, waiting for approaching storms. To help solve this problem, competitors are working to integrate wave energy capture with AUV systems to collect this data, helping to better protect coastal communities from oncoming storms. Solutions developed through this prize aim to enable long-term collection of data before, during, and after a hurricane that will help better forecast storm intensity. The prize mechanism provides an environment to accelerate technology development for innovators and helps to improve awareness of marine energy and its ability to provide power to blue economy applications.

coastal communities↗

Robustness of the Ensemble Score Filter to the Type of Assimilated Observation Networks

Recent advances in data assimilation (DA) have focused on developing more flexible approaches that can better accommodate nonlinearities in models and observations. However, it remains unclear how the performance of these advanced methods depends on the observation network characteristics. In this study, we present initial experiments with the surface quasi‐geostrophic model, in which we compare a recently developed ensemble filter using score‐based diffusion models with the standard Local Ensemble Transform Kalman Filter (LETKF). Our results show that the analysis solutions respond differently to the number, spatial distribution, and nonlinear fraction of assimilated observations. We also find notable changes in the multiscale characteristics of the analysis errors. Given that standard DA techniques will eventually be replaced by more advanced methods, we hope this study sets the ground for future efforts to reassess the value of Earth observing systems in the context of newly emerging algorithms.

97 MATHEMATICS AND COMPUTING↗

Observation of flow vector fluctuations in p–Pb collisions at \(\sqrt{{s}_{NN}}=5.02\) TeV

Measurements of transverse momentum (pT) and pseudorapidity (η) dependent flow vector fluctuations in p–Pb collisions at $$\sqrt{{s}_{NN}}=5.02$$ TeV at the CERN Large Hadron Collider are presented. By studying long-range two-particle correlations with a template fit method, potential biases from non-flow effects such as jets and resonance decays are effectively suppressed. Significant pT- and η-dependent fluctuations of the second-harmonic flow vector are observed with more than 5σ confidence in p–Pb collisions, similar to the observations in Pb–Pb collisions. The influence of residual non-flow effects has been evaluated and cannot account for the observed fluctuations, thereby confirming the observation of flow vector fluctuations in small collision systems at the LHC. Comparisons to model calculations from 3DGlauber+MUSIC+UrQMD and the parton transport model from AMPT are also presented. The measurements provide constraints on the theoretical modelling of the three-dimensional initial geometry and its event-by-event fluctuations, offering critical insights into the origin of collective flow in small collision systems at the LHC.

Abdallah, D A H↗

Pure quark and gluon observables in collinear drop

We construct a class of pure quark and gluon observables by using the collinear drop grooming technique. The construction is based on linear combinations of multiple cumulative distributions of the jet mass in collinear drop, whose specific weights are fully predicted perturbatively. This yields observables which obtain their values purely from quarks (or purely from gluons) in a wide region of phase space. We demonstrate this by showing that these observables are effective in two phase space regions, one dominated by perturbative resummation and one dominated by nonperturbative effects. The nonperturbative effects are included using shape functions which only appear as a common factor in the linear combinations constructed. We test this construction using a numerical analysis with next-to-leading logarithmic resummation and various shape function models, as well as analyzing these observables with PYTHIA and VINCIA. Choices for the collinear drop parameters are optimized for experimental use.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Absolute entropy and the observer’s no-boundary state

We investigate the no-boundary proposal for closed universes with an observer. We argue that the observer’s no-boundary state is the identity operator on the physical Hilbert space, i.e., the maximum entropy state and show this explicitly in Jackiw-Teitelboim gravity. Geometrically, the no-boundary state is a bra-ket wormhole. Expectation values in the no-boundary state provide a trace for the observer’s algebra, which allows one to define von Neumann entropy for observers in different universes as the relative entropy with respect to the no-boundary state. This result is consistent with all previously discussed cases of traces for invariantly defined regions.

Cosmological models↗

Evaluating ecosystem water use efficiency and recovery dynamics during flash droughts: insights from observations and model simulations

Flash droughts (FD), rapidly emerging in a warming future, disrupt ecosystems, agriculture, and water security. Ecosystem water use efficiency (WUE), the ratio of gross primary production (GPP) to actual evapotranspiration (AET), balances carbon assimilation and water loss. FD rapidly disrupts this balance, making WUE critical for assessing plant stress and recovery. Here, this study investigates the dynamics of landscape-scale WUE, and the components of GPP and AET under FD utilizing both observed data from the Missouri Ozark AmeriFlux site (US-MOz) and version 2 of the U.S. Department of Energy’s Earth, Energy, Exascale System Model (E3SM) Land Model (ELMv2). Observations and simulations reveal GPP as dominant for WUE during earlier FD events (2005, 2007, 2012), shifting to AET in recent events (2014, 2018). This agreement indicates that the ELM can capture the shifting dynamics of GPP and AET in regulating WUE under FD conditions. However, the ELM systematically underestimates both GPP and AET and does so in a manner that does not preserve their ratio. As a result, WUE is also underestimated, suggesting that GPP is more strongly underestimated than AET. Furthermore, the ELM also underestimates the speed of GPP recovery, producing an artificially prolonged GPP recovery time following FD events. Observed environmental drivers such as vapor pressure deficit (VPD), soil moisture (SM), and predawn leaf water potential (PLWP) effectively predict WUE, but ELM primarily highlights SM, underestimating VPD’s role. This study demonstrates that relying solely on soil moisture fails to capture the rapid hydraulic recovery observed in PLWP, underscoring the necessity of integrating plant hydraulics into land surface models to improve flash drought predictability.

Evapotranspiration↗

On the role of joint probability distributions of incompatible observables in Bell and Kochen–Specker Theorems

Highlights: •Bell and Kochen–Specker theorems rule out local or noncontextual realist models. •Still, they assume a joint probability distribution for incompatible observables. •Those joint probability distributions do not exist in quantum mechanics. •Realist models without joint distributions for incompatible observables are given. •A reformulation of Bell and Kochen–Specker arguments is provided to rule them out. -- Abstract: We analyze the validity of Bell and Kochen–Specker theorems under local (or noncontextual) realism but avoiding an assumption of the existence of a joint probability distribution for incompatible observables. We formulate a realist model which complies with this requirement. This is obtained by employing divergent sequences that nevertheless have marginals which are convergent. We find that under standard reasonable assumptions this possibility does not lead to a loophole of those theorems, by deriving a short of CHSH inequality valid for any finite size ensemble. Moreover, we analyze a Hardy’s paradox setting where noncontextual realism imposes the existence of joint probabilities for incompatible observables.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Equation of state constraints from multi-messenger observations of neutron star mergers

The very first detection of gravitational waves from a neutron star binary merger, GW170817, exceeded all expectations. The event was relatively nearby, which may point to a relatively high merger rate. It was possible to extract finite-size effects from the gravitational-wave signal, which constrains the nuclear equation of state. Also, an electromagnetic counterpart was detected at many wavebands from radio to gamma rays marking the begin of a new multi-messenger era involving gravitational waves. We describe how multi-messenger observations of GW170817 are employed to constrain the nuclear equation of state. Combining the information from the optical emission and the mass measurement through gravitational waves leads to a lower limit on neutron star radii. According to this conservative analysis, which employs a minimum set of assumptions, the radii of neutron stars with typical masses should be larger than about 10.7 km. This implies a lower limit on the tidal deformability of about 210, while much stronger lower bounds are not supported by the data of GW170817. The multi-messenger interpretation of GW170817 rules out very soft nuclear matter and complements the upper bounds on NS radii which are derived from the measurement of finite-size effects during the pre-merger phase. We highlight the future potential of multi-messenger observations and of GW measurements of the postmerger phase for constraining the nuclear equation of state. Finally, we propose an observing strategy to maximize the scientific yield of future multi-messenger observations.

79 ASTRONOMY AND ASTROPHYSICS↗

Intra-annual variations of regional total column ozone, aerosol optical depth, and water vapor from ground-based, satellite-based and model-based observations

The Microtops II ozonometer has been deployed to continuously measure the total column ozone (TCO), pre-cipitable water content (PWC) and aerosol optical thickness (AOT) at Atigre village (16.74° N, 74.37° E, 604 m above sea level, masl) located on the southeastern slope of Indian western Ghats. The Microtops II ozonometer measurements during the period from September 2017 to June 2018 were analyzed along with the retrieved products of Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellites and also the ERA-interim reanalysis model. We found that the TCO (or PWC) data from the OMI (or MODIS) and the ERA reanalysis model data products are in good agreement. The mea-surements showed strong seasonal variability such that TCO was lowest in the winter season but increased in the summer season, and both PWC and AOT were lowest in the post-monsoon season and increased in the summer season. In continuous ERA-interim reanalysis TCO observations, we found the three types of periodicities in the daily mean TCO as well as PWC (i) The weekly (7 days), (ii) quasi-biweekly (14 to 16 days), (iii) Madden Julian Oscillations (MJO) (30–60 days) oscillations. These oscillations depend on the periodic weather changes in the troposphere. We also observe that the average day to day variability in daily mean TCO observations in the observational period is about 1.4%, 1.1%, 2.62% in the Microtops II ozonometer, ERA-interim reanalysis, and OMI data respectively. We found the positive correlation between daily mean AOT and PWC in all seasons (except monsoon), which is maximum in the winter season, showing the hygroscopic nature of aerosols. The sources of water vapor and aerosol at our location are also studied using back-trajectory analysis.

Nade, Dada R.↗

The CosmoVerse White Paper: Addressing observational tensions in cosmology with systematics and fundamental physics.

The standard model of cosmology has provided a good phenomenological description of a wide range of observations both at astrophysical and cosmological scales for several decades. This concordance model is constructed by a universal cosmological constant and supported by a matter sector described by the standard model of particle physics and a cold dark matter contribution, as well as very early-time inflationary physics, and underpinned by gravitation through general relativity. There have always been open questions about the soundness of the foundations of the standard model. However, recent years have shown that there may also be questions from the observational sector with the emergence of differences between certain cosmological probes. In this White Paper, we identify the key objectives that need to be addressed over the coming decade together with the core science projects that aim to meet these challenges. These discordances primarily rest on the divergence in the measurement of core cosmological parameters with varying levels of statistical confidence. These possible statistical tensions may be partially accounted for by systematics in various measurements or cosmological probes but there is also a growing indication of potential new physics beyond the standard model. After reviewing the principal probes used in the measurement of cosmological parameters, as well as potential systematics, we discuss the most promising array of potential new physics that may be observable in upcoming surveys. We also discuss the growing set of novel data analysis approaches that go beyond traditional methods to test physical models. These new methods will become increasingly important in the coming years as the volume of survey data continues to increase, and as the degeneracy between predictions of different physical models grows. There are several perspectives on the divergences between the values of cosmological parameters, such as the model-independent probes in the late Universe and model-dependent measurements in the early Universe, which we cover at length. The White Paper closes with a number of recommendations for the community to focus on for the upcoming decade of observational cosmology, statistical data analysis, and fundamental physics developments.

Dienes, Keith [Univ. of Arizona, Tucson, AZ (Unite↗

High-Resolution South American Wind Resource Data Downscaled with Generative Machine Learning Conditioned on Near-Surface Observations

High-resolution historical wind data was developed for the entirety of South America using the innovative Super-Resolution for Renewable Resource Data (sup3r) machine learning framework. The publicly available Sup3rWind South America dataset represents a significant advancement in wind resource data generation, leveraging generative machine learning conditioned on near-surface observations from the Meteorological Assimilation Data Ingest System (MADIS) to efficiently and accurately downscale coarse reanalysis data from the European Centre for Medium-Range Weather Forecasts (ERA5). This approach produces fine-scale, spatially and temporally coherent wind and meteorological fields hundreds of times more computationally efficient than traditional numerical weather modeling methods, enabling access to high-fidelity wind information across both continental and offshore regions. Sup3rWind South America builds on the earlier Sup3rWind Ukraine dataset through improvements in model architecture and outputs conditioned on near-surface observation inputs. As with the Ukraine data release, this dataset includes wind speed, wind direction, temperature, relative humidity, and pressure at a horizontal resolution of ~2 km, representing a 15x spatial enhancement relative to the 31 km ERA5 grid. Wind speed and direction are provided at 5-minute resolution, a 12x temporal refinement compared to the hourly ERA5 data, while temperature, relative humidity, and pressure remain at hourly resolution. The data covers all years from 2005 to 2024. Before downscaling, ERA5 inputs were bias-corrected using long-term monthly means and a limited number of quality-controlled observations to align large-scale statistics with regional conditions. The resulting dataset is the first publicly available high-resolution timeseries wind record that provides full spatial coverage of South America. Model validation demonstrates strong agreement with observations across several statistical metrics, consistent with other state-of-the-art high-resolution wind resource datasets. The potential applications of Sup3rWind South America span renewable energy resource assessment, energy system modeling, and grid resilience analysis. The 20-year record and high spatial and temporal resolution support accurate estimation of long-term energy yield and the economic feasibility of potential wind development sites. Continuous coverage across both continental and offshore regions enables comprehensive site prospecting within exclusive economic zones. The 2 km, 5-minute resolution data provide the spatial and temporal variability required for power system simulation, operational planning, and regional risk assessments.

17 WIND ENERGY↗

Quantifying the Contributions of Aerosol- and Snow-Produced ClNO 2 through Observations and 1D Modeling

Nitryl chloride (ClNO 2 ) is a radical reservoir that forms and accumulates in the nocturnal atmospheric boundary layer influenced by combustion emissions and chloride (e.g., sea salt and road salt). Upon sunrise, ClNO 2 rapidly photolyzes to generate highly reactive chlorine radicals (Cl • ) that affect the air quality by generating secondary air pollutants. Recent studies have shown road salt aerosols and saline snowpack to be sources of ClNO 2 in the wintertime urban environment; however, the quantitative contributions of each chloride source are not known. In this study, we examine the vertically resolved contributions of aerosol particles and saline snowpack as sources of ClNO 2 by using an observationally constrained snow–atmosphere coupled one-dimensional model applied to wintertime Kalamazoo, Michigan, U.S. Model simulations show that ClNO 2 emitted from urban snowpack can be vertically transported throughout the entire atmospheric boundary layer and can be a significant source of ClNO 2 , contributing up to ~60% of the ClNO 2 budget near the surface. Here, modeled snowpack ClNO 2 emission rates were 6 (±7) times higher than the observationally derived emission rates, suggesting that not all snow chloride is available for reaction. ClNO 2 production from both aerosol particles and snow emissions are required to best simulate the observed surface-level ClNO 2 . Using the traditional bulk parameterization for ClNO 2 produced from particles significantly overestimated ClNO 2 due to the assumption of having equivalent dinitrogen pentoxide (N 2 O 5 ) uptake and chloride availability for the entire particle population. In comparison, the chemically resolved surface area-based parameterization slightly underestimated the observations and had uncertainties deriving from ClNO 2 production from residential wood burning particles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemical Trapping of CO2 by Clay Minerals at Reservoir Conditions: Two Mechanisms Observed by In Situ High Pressure and Temperature Experiments

The reaction of clay minerals in sedimentary rocks with supercritical CO2-rich fluids is poorly understood, but has potential implications for enhanced oil and gas production and geological C-sequestration. Experiments performed in situ at temperature and pressure relevant to reservoir conditions (T = 323 K and Pfluid = 90 bar) show that trioctahedral clay minerals can react with supercritical CO2 to produce carbonate phases by both ion exchange/precipitation reactions and dissolution/reprecipitation on a timescale of hours under certain conditions. The dissolution/reprecipitation reactions were observed in a synthetic, high surface area/high edge site surface area smectite (laponite) exchanged with Ca2+, Cs+, and tetramethyl ammonium (TMA+), and the ion exchange/precipitation mechanism was observed for a Pb-exchanged natural smectite (hectorite). Novel X-ray diffraction and NMR and infrared spectroscopic tools provide in situ observation of the reactions in real time supported by a suite of ex situ analyses. For the laponites, IR data show that HCO3- ion forms at water contents as small as ~5 H2O molecules/exchangeable cation. When the exchangeable cation is Ca2+, the IR data show the formation of carbonate as well, and the NMR results show formation of amorphous calcium carbonate at low water contents in addition to HCO3-. Laponites equilibrated at 100% R.H. at atmospheric conditions and then exposed to scCO2 generate additional, more mobile HCO3- ion and exhibit evidence of clay dissolution leading to a poorly crystalline or amorphous hydrous magnesium carbonate/bicarbonate that forms from Mg2+ released by dissolution of the octahedral sheet. The 100% R.H. sample with exchangeable Ca2+ also forms calcite, vaterite and aragonite precipitates. Comparison of these results with those already published in the literature suggest that a high edge site surface area is crucial to this process occurring on a short timescale. In the Pb-exchanged hectorite exposed to scCO2, once a critical humidity threshold is reached, cerussite (PbCO3) rapidly forms concurrent with exchange of interlayer Pb2+ with H3O+ formed by reaction of CO2 with water on the clay surface. Given that such a reaction is not observed on a similar timescale with more common Ca2+ or Na+ in hectorite and other smectites, the low solubility of cerussite appears to be the thermodynamic driving force for this process, meaning that such reactions are expected to occur more slowly in most natural samples. However, the results suggest that both types of CO2-capturing processes could occur on short and/or geological timescales during CO2 flooding of oil and gas reservoirs, in C-sequestration reservoirs, and as the result of fracking using CO2-based fluids.

Bowers, Geoffrey M.↗

Real-Time In Situ Observation of CsPbBr 3 Perovskite Nanoplatelets Transforming into Nanosheets

The manipulation of nano-objects through heating is an effective strategy for inducing structural modifications and therefore changing the optoelectronic properties of semiconducting materials. Despite its potential, the underlying mechanism of the structural transformations remains elusive, largely due to the challenges associated with their in situ observations. To address these issues, we synthesize temperature-sensitive CsPbBr 3 perovskite nanoplatelets and investigate their structural evolution at the nanoscale using in situ heating transmission electron microscopy. We observe the morphological changes that start from the self-assembly of the nanoplatelets into ribbons on a substrate. We identify several paths of merging nanoplates within ribbons that ultimately lead to the formation of nanosheets dispersed randomly on the substrate. These observations are supported by molecular dynamics simulations. We correlate the various paths for merging to the random orientation of the initial ribbons along with the ligand mobility (especially from the edges of the nanoplatelets). This leads to the preferential growth of individual nanosheets and the merging of neighboring ones. These processes enable the creation of structures with tunable emission, ranging from blue to green, all from a single material. Our real-time observations of the transformation of perovskite 2D nanocrystals reveal a route to achieve large-area nanosheets by controlling the initial orientation of the self-assembled objects with potential for large-scale applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗