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At least 793 records · Page 44

Spatial distribution of internal heat gains: A probabilistic representation and evaluation of its influence on cooling equipment sizing in large office buildings

Internal heat gains from occupants, lighting, and plug loads are significant components of the space cooling load in an office building. Internal heat gains vary with time and space. The spatial diversity is significant, even for spaces with the same function in the same building. The stochastic nature of internal heat gains makes determining the peak cooling load to size air-conditioning systems a challenge. The traditional conservative practice of considering the largest internal heat gain among spaces and applying safety factors overestimates the space cooling load, which leads to oversized air-conditioning equipment and chiller plants. In this study, a field investigation of several large office buildings in China led to the development of a new probabilistic approach that represents the spatial diversity of the design internal heat gain of each tenant as a probability distribution function. In a large office building, a central chiller plant serves all air handling units (AHUs), with each AHU serving one or more floors of the building. Therefore, the spatial diversity should be considered differently when the peak cooling loads to size the AHUs and chillers are calculated. Finally, the proposed approach considers two different levels of internal heat gains to calculate the peak cooling loads and size the AHUs and chillers in order to avoid oversizing, improve the overall operating efficiency, and thus reduce energy use.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Spatial-Temporal [{sup 18}F]FDG-PET Features for Predicting Pathologic Response of Esophageal Cancer to Neoadjuvant Chemoradiation Therapy

Purpose: To extract and study comprehensive spatial-temporal {sup 18}F-labeled fluorodeoxyglucose ([{sup 18}F]FDG) positron emission tomography (PET) features for the prediction of pathologic tumor response to neoadjuvant chemoradiation therapy (CRT) in esophageal cancer. Methods and Materials: Twenty patients with esophageal cancer were treated with trimodal therapy (CRT plus surgery) and underwent [{sup 18}F]FDG-PET/CT scans both before (pre-CRT) and after (post-CRT) CRT. The 2 scans were rigidly registered. A tumor volume was semiautomatically delineated using a threshold standardized uptake value (SUV) of ≥2.5, followed by manual editing. Comprehensive features were extracted to characterize SUV intensity distribution, spatial patterns (texture), tumor geometry, and associated changes resulting from CRT. The usefulness of each feature in predicting pathologic tumor response to CRT was evaluated using the area under the receiver operating characteristic curve (AUC) value. Results: The best traditional response measure was decline in maximum SUV (SUV{sub max}; AUC, 0.76). Two new intensity features, decline in mean SUV (SUV{sub mean}) and skewness, and 3 texture features (inertia, correlation, and cluster prominence) were found to be significant predictors with AUC values ≥0.76. According to these features, a tumor was more likely to be a responder when the SUV{sub mean} decline was larger, when there were relatively fewer voxels with higher SUV values pre-CRT, or when [{sup 18}F]FDG uptake post-CRT was relatively homogeneous. All of the most accurate predictive features were extracted from the entire tumor rather than from the most active part of the tumor. For SUV intensity features and tumor size features, changes were more predictive than pre- or post-CRT assessment alone. Conclusion: Spatial-temporal [{sup 18}F]FDG-PET features were found to be useful predictors of pathologic tumor response to neoadjuvant CRT in esophageal cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Spatial Precision in Magnetic Resonance Imaging–Guided Radiation Therapy: The Role of Geometric Distortion

Because magnetic resonance imaging–guided radiation therapy (MRIgRT) offers exquisite soft tissue contrast and the ability to image tissues in arbitrary planes, the interest in this technology has increased dramatically in recent years. However, intrinsic geometric distortion stemming from both the system hardware and the magnetic properties of the patient affects MR images and compromises the spatial integrity of MRI-based radiation treatment planning, given that for real-time MRIgRT, precision within 2 mm is desired. In this article, we discuss the causes of geometric distortion, describe some well-known distortion correction algorithms, and review geometric distortion measurements from 12 studies, while taking into account relevant imaging parameters. Eleven of the studies reported phantom measurements quantifying system-dependent geometric distortion, while 2 studies reported simulation data quantifying magnetic susceptibility–induced geometric distortion. Of the 11 studies investigating system-dependent geometric distortion, 5 reported maximum measurements less than 2 mm. The simulation studies demonstrated that magnetic susceptibility–induced distortion is typically smaller than system-dependent distortion but still nonnegligible, with maximum distortion ranging from 2.1 to 2.6 mm at a field strength of 1.5 T. As expected, anatomic landmarks containing interfaces between air and soft tissue had the largest distortions. The evidence indicates that geometric distortion reduces the spatial integrity of MRI-based radiation treatment planning and likely diminishes the efficacy of MRIgRT. Better phantom measurement techniques and more effective distortion correction algorithms are needed to achieve the desired spatial precision.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Temporal flow variations interact with spatial physical heterogeneity to impact solute transport in managed river corridors

The interactions between surface water and groundwater in river corridors lead to temporal fluctuations in subsurface water fluxes which have a critical role on solute transport dynamics. Here, we develop a framework to analyze the relative impacts of different temporal frequencies of the flow field in a spatially heterogeneous aquifer on solute transport. Our analysis indicates that the advection-dispersion equation behaves as a low-pass filter by wiping out the effect of high-frequency velocity fluctuations on the first two spatial moments of the solute plume, namely its center of mass and spreading. The concepts discussed in the theoretical analysis are then applied to understand solute transport dynamics at the 300 Area of the Hanford site (USA) adjacent to the Columbia River. We examine the temporal behavior of the solute plume's spatial moments for different temporal frequencies utilizing geostatistical parameters estimated in the 300 Area. Due to the proximity to the Columbia river, groundwater fluxes at the Hanford site are highly dynamic resulting in a large range of characteristic temporal frequencies. Nonetheless, similar to the theoretical analysis, our results show that the effect of high-frequency fluctuations is filtered, with most of the solute transport dynamics being controlled by fluctuations characterized by a large characteristic period.

54 ENVIRONMENTAL SCIENCES↗

A mesh partitioning algorithm for preserving spatial locality in arbitrary geometries

Highlights: •An algorithm for partitioning computational meshes is proposed. •The Morton order space-filling curve is modified to achieve improved locality. •A spatial locality metric is defined to compare results with existing approaches. •Results indicate improved performance of the algorithm in complex geometries. -- Abstract: A space-filling curve (SFC) is a proximity preserving linear mapping of any multi-dimensional space and is widely used as a clustering tool. Equi-sized partitioning of an SFC ignores the loss in clustering quality that occurs due to inaccuracies in the mapping. Often, this results in poor locality within partitions, especially for the conceptually simple, Morton order curves. We present a heuristic that improves partition locality in arbitrary geometries by slicing a Morton order curve at points where spatial locality is sacrificed. In addition, we develop algorithms that evenly distribute points to the extent possible while maintaining spatial locality. A metric is defined to estimate relative inter-partition contact as an indicator of communication in parallel computing architectures. Domain partitioning tests have been conducted on geometries relevant to turbulent reactive flow simulations. The results obtained highlight the performance of our method as an unsupervised and computationally inexpensive domain partitioning tool.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Behavioral simulations and experimental evaluations of stress induced spatial nonuniformity of dynamic bulk modulus in additive friction stir deposited AA 6061

Additive friction stir deposition (AFSD) is a rapidly developing solid-state additive manufacturing (AM) technology that enables the fabrication of customized products on a relatively large scale. The unique forge-liked process offers high quality products with refined equiaxed microstructure and exceptional mechanical performance. However, in AFSD, the spatially distributed mechanical properties within a deposited layer have not been established so far, due to the lack of a suitable large-scale mapping method. In the present work, an ultrasonic dynamic-elasticity mapping method was employed to map the distribution of physical properties in a AFSD 6061 Al. Strong spatial asymmetries in elastographies were mainly due to the residual stresses. The origin of the asymmetries was investigated through thermo-mechanical simulations of the AFSD process. It was observed that majority of the asymmetries were associated with the mechanical residual stresses instead of the symmetric thermal residual stresses during linear deposition of the AFSD process. However, the thermal residual stresses can be manipulated to become asymmetric with a 90° turn in the linear deposition path, due to the difference between the levels of cooling along the edges of the inner and outer corners. Hence, the mechanical and thermo-mechanical residual stresses can be additive or subtractive depending on the direction of the turns. Here, such numerically predicted behaviors were also experimentally observed on the AFSD fabricated samples by ultrasonic elastography. Furthermore, additional preliminary studies on multi-layer AFSD fabrications show the asymmetric mechanical stresses generated during the deposition process on different layers generate constructive or destructive interference which results to spatially variable dynamic bulk modulus depending on the deposition orientations of layers.

36 MATERIALS SCIENCE↗

High spatial resolution neutron imaging of lithium-ion batteries: Correlating microstructure and lithium transport

Thick electrodes for lithium-ion batteries can increase the overall energy density, but increasing the electrode thickness introduces charge transport limitations. These limitations may be mitigated through proper electrode structuring. Here, high spatial resolution neutron imaging was used to understand the correlation between microstructure and lithium transport in lithium-ion anodes. Batteries with distinct graphite anode microstructures were produced and studied with high spatial resolution in operando neutron radiography to observe the effects of structure on transport. High spatial resolution neutron computed tomography was performed following in operando neutron radiography. X-ray computed tomography and scanning electron microscopy were used to observe the finer scale anode structure to complement neutron imaging. Solvent-free anodes containing a tightly-packed layered structure confined lithium movement close to the separator. This structure limited capacity, but supported better rate capability. Conversely, a more open pore structure in the wet cast anodes yielded higher capacity with reduced rate capability. Together, these results show that lithium distributions can be controlled by the macroscopic structure of the electrodes, the microstructural pore network, and the microscale active areas that support electrochemical reactions. Furthermore, multimodal imaging applying the complementary strengths of neutron and X-ray methods is shown as a tool for advancing battery design.

25 ENERGY STORAGE↗

Spatially calibrating polycyclic aromatic hydrocarbons (PAHs) as proxies of area burned by vegetation fires: Insights from comparisons of historical data and sedimentary PAH fluxes

Many regions worldwide have experienced increasing wildfire activity in recent years and climate changes are predicted to result in more frequent and severe fires. Reconstruction of past fire activity offers paleoenvironmental context for modern and future burning. Pyrogenic polycyclic aromatic hydrocarbons (PAHs) have been increasingly used as a molecular biomarker for fire occurrence in the paleorecord and offer opportunity for nuanced reconstructions of fire characteristics. A suite of PAHs are produced during combustion, and the emission amount and assemblage is influenced by many variables including fuel type, fire temperature, and oxygen availability. Despite recent advances in understanding the controls and taphonomy of these biomass burning markers, the spatial scale of this proxy is unknown. In this paper, measurements of PAH fluxes preserved in a lake sediment archive from the Sierra Nevada, California were compared with a historical geographic information system dataset of area burned up to 150 km distance from the lake to determine the spatial scales for which these biomarkers are reliable proxies of burning. Comparisons of PAH fluxes with charcoal accumulation rates in the same sediments suggest that pyrogenic particulate transport modulates low to mid-molecular weight PAHs via adsorption. Overall, the results indicate that PAH records integrate a combination of spatial signals of area burned and measurement of individual PAHs may enable cross-scale paleofire reconstructions.

54 ENVIRONMENTAL SCIENCES↗

Harmonizing solar induced fluorescence across spatial scales, instruments, and extraction methods using proximal and airborne remote sensing: A multi-scale study in a soybean field

Solar-induced chlorophyll fluorescence (SIF) has been widely used to track vegetation photosynthesis at different scales ranging from in-situ measurements to satellite products. Airborne platforms sample SIF data at a spatial scale intermediate between in-situ and satellite, matching that of ground measurement (e.g. flux tower footprints and other field sampling), enabling us to explore causes of SIF variation and validate satellite-based SIF products. However, harmonizing SIF across sensors and platforms (correcting for systematic errors to yield a consistent, comparable SIF product) is challenging because SIF can be retrieved in different absorption windows, with different instruments and methods complicating the comparison between different observational levels (i.e., ground, airborne, satellites) and between sites equipped with different instruments with varying optical properties (spectral resolution and sampling intervals, spatial resolution). Additionally, the spatial and temporal variability of atmospheric properties can influence the retrieval of the weak SIF signal. Because of these complications, direct comparisons of airborne and ground SIF across scales are rarely attempted. Here, in this study, we combined airborne SIF data with simultaneous ‘ground truth’ data collected by stationary and mobile platforms in a soybean field in Nebraska, USA. In this effort, we tested several SIF extraction methods, including Fraunhofer Line Discrimination (FLD), improved Fraunhofer Line Discrimination (iFLD), Spectral Fitting Method (SFM), SpecFit, and a Singular Vector Decomposition (SVD) method. The SpecFit method was sensitive to the 715–740 nm water bands and removing the water bands in the fitting process yielded better agreement between the airborne and ground SIF spectra. Accurate estimation of the ground level downwelling irradiance obtained by ground measurements over a calibration target improved agreement between airborne and ground SIF retrievals at the O 2 A band, and allowed us to derive a SIF dataset with improved agreement across platforms and sampling scales. This experimental approach provided a method for generating comparable SIF signals across instruments, methods and platforms, which is critical to understanding the SIF-GPP relationship at different scales and to cross-validate the diversity of platforms used for satellite products calibration and validation.

54 ENVIRONMENTAL SCIENCES↗

Spatial metabolomics and lipidomics in kidney disease

Kidney disease is a global health issue that affects over 850 million people, and early detection is key to preventing severe disease and complications. Kidney diseases are associated with complex dysregulation of lipid metabolism. Spatial metabolomics through mass spectrometry imaging (MSI) enables spatial mapping of the lipids in tissue and includes a variety of techniques that can be used to image lipids. In the kidney MSI studies often seek to resolve individual functional tissue units such as glomeruli and proximal tubules. Several different MSI techniques such as matrix-assisted laser desorption/ionization and desorption electrospray ionization have been used to characterize lipids and small molecules in chronic kidney disease, acute kidney injury, genetic kidney disease, and cancer. In this review we provide several examples of how spatial metabolomics data can provide critical information concerning localization of changes in disease states. Additionally, when combined with pathology, measurements, transcriptomics, or proteomics, the metabolomic changes can illuminate underlying mechanisms and provide new clinical insights.

59 BASIC BIOLOGICAL SCIENCES↗

Non-destructive spatial analysis of phosphatase activity and total protein distribution in the rhizosphere using a root blotting method

Phosphorus (P) is an essential macronutrient for plant growth, but bioavailable P in soils is often limited due to immobilization resulting from pH and geochemical interactions. Understanding the dynamics of P in soils and elucidating the mechanisms by which plants access P from their environment are critical to evaluating productivity, particularly in nutrient poor environments. Phosphorus from organic matter can act as a major source of P for organisms in soil systems. Phosphatases, enzymes that liberate inorganic P from organic sources, are produced by both plants and microbes and are considered one of the most active classes of enzymes in soil. In this work we developed a root blotting method to spatially image phosphatase activity in the rhizosphere. Proteins from the rhizosphere are transferred to a nitrocellulose membrane while retaining their enzymatic activity and two-dimensional spatial distribution. Subsequent application of a fluorogenic phosphatase indicator, DDAO phosphate, enables visualization of the distribution of phosphatase activity in the sample. The proteins can then be fixed to the membrane and treated with a SYPRO® Ruby gel stain, a fluorescent total protein stain, allowing for visualization of total protein distribution. Taken together, the images of phosphatase activity and total protein localization can be mapped back to the root architecture and provide insight into factors affecting the spatial distribution of enzymatic activity and protein accumulation in the rhizosphere. Notably, this method can be applied to plants growing in rhizoboxes containing soil or soilless growth mixtures (e.g., sand or various potting mixes) and, because of the non-destructive nature of this approach, be performed over time to track changes. We anticipate that this fluorescent indicator imaging technique on root blots can be used in diverse plant-microbe-soil systems to better understand the role of phosphatases in P acquisition and soil P cycling.

59 BASIC BIOLOGICAL SCIENCES↗

Spatially localized particle energization by Landau damping in current sheets produced by strong Alfvén wave collisions

Understanding the removal of energy from turbulent fluctuations in a magnetized plasma and the consequent energization of the constituent plasma particles is a major goal of heliophysics and astrophysics. Previous work has shown that nonlinear interactions among counterpropagating Alfvén waves – or Alfvén wave collisions – are the fundamental building block of astrophysical plasma turbulence and naturally generate current sheets in the strongly nonlinear limit. A nonlinear gyrokinetic simulation of a strong Alfvén wave collision is used to examine the damping of the electromagnetic fluctuations and the associated energization of particles that occurs in self-consistently generated current sheets. A simple model explains the flow of energy due to the collisionless damping and the associated particle energization, as well as the subsequent thermalization of the particle energy by collisions. The net particle energization by the parallel electric field is shown to be spatially localized, and the nonlinear evolution is essential in enabling spatial non-uniformity. Using the recently developed field–particle correlation technique, we show that particles resonant with the Alfvén waves in the simulation dominate the energy transfer, demonstrating conclusively that Landau damping plays a key role in the spatially localized damping of the electromagnetic fluctuations and consequent energization of the particles in this strongly nonlinear simulation.

Physics↗

Diffraction of radio frequency waves by spatially modulated interfaces in the plasma edge in tokamaks

We report the use of radio frequency (RF) waves in fusion plasmas for heating, for non-inductive current generation, for profile control and for diagnostics has been well established. The RF waves, excited by antenna structures placed near the wall of a fusion device, have to propagate through density fluctuations at the plasma edge. These fluctuations can modify the properties of the RF waves that propagate towards the core of the plasma. A full-wave electromagnetic computational code ScaRF based on the finite difference frequency domain (FDFD) method has been developed to study the effect of density turbulence on RF waves. The anisotropic plasma permittivity used in the scattering studies is that for a magnetized, cold plasma. The code is used to study the propagation of an RF plane wave through a modulated, spatially periodic density interface. Such an interface could arise in the edge region due to magnetohydrodynamic instability or drift waves. The frequency of the plane wave is taken to be in the range of the electron cyclotron frequency. The scattering analysis is applicable to ITER-like plasmas, as well as to plasmas in medium sized tokamaks such as TCV, ASDEX-U and DIII-D. The effect of different density contrasts across the interface and of different spatial modulations are discussed. While ScaRF is used to study a periodic density fluctuation, the code is general enough to include different varieties of density fluctuations in the edge region – such as blobs and filaments, and spatially random fluctuations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

OpenMSI Arrayed Analysis Toolkit: Analyzing Spatially Defined Samples Using Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) has primarily been applied in localizing biomolecules within biological matrices. Although well-suited, the application of MSI for comparing thousands of spatially defined spotted samples has been limited. One reason for this is a lack of suitable and accessible data processing tools for the analysis of large arrayed MSI sample sets. In this paper, the OpenMSI Arrayed Analysis Toolkit (OMAAT) is a software package that addresses the challenges of analyzing spatially defined samples in MSI data sets. OMAAT is written in Python and is integrated with OpenMSI (http://openmsi.nersc.gov), a platform for storing, sharing, and analyzing MSI data. By using a web-based python notebook (Jupyter), OMAAT is accessible to anyone without programming experience yet allows experienced users to leverage all features. OMAAT was evaluated by analyzing an MSI data set of a high-throughput glycoside hydrolase activity screen comprising 384 samples arrayed onto a NIMS surface at a 450 μm spacing, decreasing analysis time >100-fold while maintaining robust spot-finding. The utility of OMAAT was demonstrated for screening metabolic activities of different sized soil particles, including hydrolysis of sugars, revealing a pattern of size dependent activities. Finally, these results introduce OMAAT as an effective toolkit for analyzing spatially defined samples in MSI. OMAAT runs on all major operating systems, and the source code can be obtained from the following GitHub repository: https://github.com/biorack/omaat.

47 OTHER INSTRUMENTATION↗

Spatially Resolved Proteome Profiling of <200 Cells from Tomato Fruit Pericarp by Integrating Laser-Capture Microdissection with Nanodroplet Sample Preparation

Due to sensitivity limitations, global proteome measurements generally require large amounts of biological starting material, which masks heterogeneity within the samples and differential protein expression among constituent cell types. Methods for spatially-resolved proteomics are being developed to resolve protein expression for distinct single cell types among highly heterogeneous tissues, but have primarily been applied to mammalian systems. Here we evaluate the performance of cell-type-specific proteome analysis of tomato fruit pericarp tissues by a platform integrating laser capture microdissection (LCM) and a recently developed automated sample preparation system (nanoPOTS, Nanodroplet processing in One pot for Trace Samples). Tomato fruits were cryosectioned prior to LCM, and tissues were dissected and captured directly into nanoPOTS chips for processing. Following processing, samples were analyzed by nanoLC-MS/MS. Approximately 1900 unique peptides and 422 proteins were identified on average from ~0.04 mm2 tissues comprising ~ 8-15 parenchyma cells. Spatially-resolved proteome analyses were performed using cells of outer epidermis, collenchyma, and parenchyma. Using =200 cells, a total of 1,870 protein groups were identified and the various tissues were easily resolved. The results provide spatial and tissue-specific insights into key enzymes and pathways involved in carbohydrate transport and source-sink relationships in tomato fruit. Of note, at the time of fruit ripening studied here, we identified differentially abundant proteins throughout the pericarp related to chlorophyll biogenesis, photosynthesis, and especially transport.

Liang, Yiran↗

Spatial Optimization of Multiscale Biorefinery Deployment for a Diversified Bioeconomy in the United States

Strategic biorefinery siting is critical for a diversified bioeconomy, yet industry, policy, and research often focus on either large-scale biofuel plants or smaller-scale specialty bioproduct facilities, with limited coordination across scales. We address this gap by modeling biorefinery deployment spanning a 28-fold difference in capacity. We developed an open-source, spatially explicit framework integrating techno-economic analysis with logistics and refinery cost surrogate models to evaluate multiscale miscanthus-derived biorefineries across the rainfed U.S. for the production of ethanol, succinic acid, lactic acid, potassium sorbate, and acrylic acid. Overall costs change little as feedstock density increases, while transport distances decrease by ∼30 to 67% (∼100 km) and siting flexibility improves. Specifically, a 5-fold feedstock density increase (2% to 10% of suitable land) reduces minimum selling prices by <10% (e.g., 0.27 USD·gal –1 for ethanol). This limited economic sensitivity suggests dense planting is not required for competitive deployment, particularly for smaller-scale facilities. Representing collection areas as irregular rather than circular expands the feasible space under low-density scenarios. While large-scale refineries anchor regional supply chains, smaller facilities retain spatial flexibility even when large refineries are established. These findings highlight the importance of spatial representation and multiscale coordination for robust, regionally tailored biomanufacturing networks to advance renewable carbon integration without extensive land conversion.

biorefinery siting↗

Complexity Reduction Methods for Large-Scale Spatially Explicit Biofuels Network Design

The size and complexity of energy system optimization models have increased significantly in recent years, driven by the availability of high-resolution spatial data. We present complexity reduction and solution methods that enable us to efficiently represent high-resolution spatial data in the network design of large-scale energy systems. We aim to reduce the size and enhance the computational efficiency of network design models without sacrificing solution accuracy. Specifically, we first present how to aggregate highly granular data into larger resolutions without averaging out their specific properties through a composite-curve-based approach and then develop a method to linearly represent these curves. Second, we utilize a general clustering method to determine groups of geographically proximate biomass fields and establish a single transportation arc for all of them, reducing the number of transportation-related variables while maintaining an accurate representation of the system. Finally, we introduce a two-step algorithm that decomposes large-scale network design problems into two smaller, more manageable subproblems. We demonstrate the application of our methods using a case study of switchgrass-to-biofuels network design in the eight states of the U.S. Midwest, using realistic and highly explicit spatial data.

09 BIOMASS FUELS↗

Solid-State Syntheses, Crystallographic Spatial Disorders, Thermal Behaviors, and Bandgaps of Hybrid Organic-Inorganic Manganese Halides: A2Mn(Cl/Br)4 (A = NH4+, C(NH2)3+, & C3H4N2+)

By systematically optimizing solid-state synthesis via the concerted use of differential scanning calorimetry and in-situ variable-temperature X-ray diffraction, we report the discovery of four new hybrid organic-inorganic manganese halides A2Mn(Cl/Br)4 (A = NH4+, C(NH2)3+, C3H4N2+), with emphasis on how the organic fragment geometry, polarity, and electron-donating properties influence crystallographic spatial disorders, thermal behaviors, and optical band gaps. With a nonpolar tetrahedral cation, as in (NH4)2MnCl4 (P21/c, mP30) or (NH4)2MnBr4 (C2/c, mC180), the direct optical bandgaps (4.36–4.28 eV) are wider than those with an organic nonpolar planar geometry, as in (C(NH2)3)2MnBr4 (P21/c, mP300, 4.07 eV), or an organic polar planar geometry, as in (C3H4N2+)2MnBr4 (I41/a, tI384, 4.05 eV). Furthermore, the organic components affect the spatial arrangement and dimensionality of the resulting inorganic frameworks comprised of Mn(Cl/Br)6 octahedra, with varying distortions, or spatially disordered MnBr4 tetrahedra. These resulting trends, coupled with the systematic investigation into synthesis, and the motivation behind elucidating the nuanced role of the organic cation, altogether expand upon the phase-space of hybrid materials beyond perovskites and demonstrate the potential for a rational design of hybrid materials with tailored optoelectronic functionalities for advanced energy applications.

Lee, Shannon J.↗