Results for “CPM”

DOE OSTI2020

Roles of Alkali Metals and Ionic Networks in Directing the Formation of Anionic Metal–Organic Frameworks

Integrating different types of fundamental chemical interactions to direct the self-assembly processes and to control the dimension of the network formed by each type of interactions is a promising strategy to develop advanced functional materials. Here, the ionic interaction of alkali metals (Na, K, Cs) towards multi-functional 2,2’-disulfo-4,4’-oxydibenzoic acid is utilized in two solvent systems, aqueous-amide and uro-amide, to synthesize six novel anionic framework materials with dramatically different features and dimensionalities: (Na 3 [Zn 4 O(L 4- ) 3 (e-murea)(H 2 O) 3 ](H 2 N(CH 3 ) 2 +) 3 (CPM-s1), [Zn 4 O(L 4- ) 3 (DMF)]((NH 2 (CH 3 ) 2 +) 6 ) (CPM-s2), Na 6 [(Zn 2 OH 2 ) 3 (L 3- ) 6 ](H 2 O) 3 (CPM-s3), K 3 [Zn 2 (L 4- ) 2 ](H 2 N(CH 3 ) 2 +)(e-murea) 2 (H 2 O) 3 (CPM-s4), K 4 [Zn(L 3- ) 2 ](H 2 O) 2 (CPM-s5), and Cs 6 [Zn(L 4- ) 2 ](H 2 O) 2 (CPM-s6), L 4- = 2,2’-disulfo-4,4’-oxydibenzoate, DMF = N,N-dimethylformamide, e-murea = 1,3-dimethyl-1-2-imidazolidinone). In CPM-s1 to CPM-s6, the alkali-sulfonate ionic bonding networks transformed from 0D clusters with Na + to 1D chains and 2D sheets with K + , and 3D network with Cs + . These vastly differing ionic domains influenced the coordination modes and spatial arrangements of the metal-carboxylate linkers, which consequently, directed the dimensionality of the coordination networks from 3D with Na + to 1D with Cs + . CPM-s1 and CPM-s2, made from tetrameric Zn 4 O clusters are rare examples of anionic MOF-5-type structures. CPM-s3 features an unprecedented hexameric Zn 6 cluster. Even though a large portion of the charge-balancing cations in these materials would hamper hydrogen bonding networks, some of them still exhibit very high ionic conductivity (e.g. 1.25 x 10 -3 S cm -1 in CPM-s3), suggesting the potential of these materials as solid-state electrolytes.

36 MATERIALS SCIENCE↗

DOE OSTI2021

A Distinct Atmospheric Mode for California Precipitation

The hydrologic cycle in California is strongly influenced by wet-season (November–April) precipitation. Here, we demonstrate the existence of an influential mode of North Pacific atmospheric pressure variability that regulates wet-season precipitation variability over both northern and southern California. This mode, named as the “California precipitation mode” (CPM), is statistically distinct from other well-known modes of pressure variability such as the Pacific-North American pattern. In addition to controlling wet-season mean precipitation, positive days of the CPM coincide with up to 90% of the extreme (>99th percentile) precipitation days and 76% of detected atmospheric rivers (ARs) days, while the negative days correspond with 60% of the dry days. CMIP6 models capture the CPM remarkably well, including its statistical separation from the other well-known modes of pressure variability. The models also reproduce the CPM's strong association with California wet-season precipitation, giving confidence in the models’ dynamics relating to regional hydrologic extremes. However, the models also exhibit biases in regional hydrologic extremes. The CPM is a useful way to understand the origins of those biases and select the more credible models for further analysis: Models with unrealistically strong gradients in the CPM pressure pattern generally oversimulate larger wet extremes and produce excessively long dry intervals in the historical period. Thus the hydrologic biases can be traced to the particular aspects of North Pacific atmospheric dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Efficacy of the Cell Perturbation Method in Large-Eddy Simulations of Boundary Layer Flow over Complex Terrain

A challenge to simulating turbulent flow in multiscale atmospheric applications is the efficient generation of resolved turbulence motions over an area of interest. One approach is to apply small perturbations to flow variables near the inflow planes of turbulence-resolving simulation domains nested within larger mesoscale domains. While this approach has been examined in numerous idealized and simple terrain cases, its efficacy in complex terrain environments has not yet been fully explored. Here, we examine the benefits of the stochastic cell perturbation method (CPM) over real complex terrain using data from the 2017 Perdigão field campaign, conducted in an approximately 2-km wide valley situated between two nearly parallel ridges. Following a typical configuration for multiscale simulation using nested domains within the Weather Research and Forecasting (WRF) model to downscale from the mesoscale to a large-eddy simulation (LES), we apply the CPM on a domain with horizontal grid spacing of 150 m. At this resolution, spurious coherent structures are often observed under unstable atmospheric conditions with moderate mean wind speeds. Results from such an intermediate resolution grid are often nested down for finer, more detailed LES, where these spurious structures adversely affect the development of turbulence on the subsequent finer grid nest. We therefore examine the impacts of the CPM on the representation of turbulence within the nested LES domain under moderate mean flow conditions in three different stability regimes: weakly convective, strongly convective, and weakly stable. In addition, two different resolutions of the underlying terrain are used to explore the role of the complex topography itself in generating turbulent structures. We demonstrate that the CPM improves the representation of turbulence within the LES domain, relative to the use of high-resolution complex terrain alone. During the convective conditions, the CPM improves the rate at which smaller-scales of turbulence form, while also accelerating the attenuation of the spurious numerically generated roll structures near the inflow boundary. During stable conditions, the coarse mesh spacing of the intermediate LES domain used herein was insufficient to maintain resolved turbulence using CPM as the flow develops downstream, highlighting the need for yet higher resolution under even weakly stable conditions, and the importance of accurate representation of flow on intermediate LES grids.

17 WIND ENERGY↗

DOE OSTI2025

Surrogate modeling of Cellular-Potts agent-based models as a segmentation task using the U-Net neural network architecture

The Cellular-Potts model is a powerful and ubiquitous framework for developing computational models for simulating complex multicellular biological systems. Cellular-Potts models (CPMs) are often computationally expensive due to the explicit modeling of interactions among large numbers of individual model agents and diffusive fields described by partial differential equations (PDEs). In this work, we develop a convolutional neural network (CNN) surrogate model using a U-Net architecture that accounts for periodic boundary conditions. We use this model to accelerate the evaluation of a mechanistic CPM previously used to investigate in vitro vasculogenesis. The surrogate model was trained to predict 100 computational steps ahead (Monte-Carlo steps, MCS), accelerating simulation evaluations by a factor of 562 times compared to single-core CPM code execution on CPU. Over short timescales of up to 3 recursive evaluations, or 300 MCS, our model captures the emergent behaviors demonstrated by the original Cellular-Potts model such as vessel sprouting, extension and anastomosis, and contraction of vascular lacunae. This approach demonstrates the potential for deep learning to serve as a step toward efficient surrogate models for CPM simulations, enabling faster evaluation of computationally expensive CPM simulations of biological processes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

ORNLERASE - EPA COUNTS PER MINUTE CALCULATOR CONVERSION FACTORS

This database is used in the EPA's Superfund Counts Per Minute (CPM) Calculator (https://epa-cpm.ornl.gov/index.html). This database contains conversion factors used in the calculator that help users estimate the expected radiation detector reading, in counts per minute (CPM), corresponding to a measured radioactivity level reported in either pCi/cm² or pCi/g. Because surface contamination and volumetric contamination behave differently, the tool uses separate conversion processes, each based on Monte Carlo N-Particle (MCNP)–derived conversion factors. The CPM Calculator supports conversions for a range of common environmental media—including soil, steel, glass, drywall, concrete, and wood—to generate detector-ready CPM values. The primary goal of this tool is to enable more efficient, real-time field measurements, reducing reliance on laboratory analyses and ultimately saving both time and money during Superfund assessments.

Dolislager, Fred [ORNL] (ORCID:0009000325477921)↗

DOE OSTI2020

A Strategy for Constructing Pore‐Space‐Partitioned MOFs with High Uptake Capacity for C 2 Hydrocarbons and CO 2

Abstract Introduction of pore partition agents into hexagonal channels of MIL‐88 type (acs topology) endows materials with high tunability in gas sorption. Here, we report a strategy to partition acs framework into pacs (partitioned acs) crystalline porous materials (CPM). This strategy is based on insertion of in situ synthesized 4,4′‐dipyridylsulfide (dps) ligands. One third of open metal sites in the acs net are retained in pacs MOFs; two thirds are used for pore‐space partition. The Co 2 V‐pacs MOFs exhibit near or at record high uptake capacities for C 2 H 2 , C 2 H 4 , C 2 H 6 , and CO 2 among MOFs. The storage capacity of C 2 H 2 is 234 cm 3 g −1 (298 K) and 330 cm 3 g −1 (273 K) at 1 atm for CPM‐733‐dps (the Co 2 V‐BDC form, BDC=1,4‐benzenedicarboxylate). These high uptake capacities are accomplished with low heat of adsorption, a feature desirable for low‐energy‐cost adsorbent regeneration. CPM‐733‐dps is stable and shows no loss of C 2 H 2 adsorption capacity following multiple adsorption–desorption cycles.

Wang, Yong↗

DOE OSTI2020

A Strategy for Constructing Pore-Space-Partitioned MOFs with High Uptake Capacity for C 2 Hydrocarbons and CO 2

Introduction of pore partition agents into hexagonal channels of MIL-88 type (acs topology) endows materials with high tunability in gas sorption. Here, we report a strategy to partition acs framework into pacs (partitioned acs) crystalline porous materials (CPM). This strategy is based on insertion of in situ synthesized 4, 4'-dipyridylsulfide (dps) ligands. As a result, one third of open metal sites in the parent acs net are retained in pacs MOFs, while two thirds are used for pore space partition. The newly synthesized Co 2 V-pacs MOFs, with optimized pore space and open metal sites, exhibit near or at record high uptake capacities for C 2 H 2 , C 2 H 4 , C 2 H 6 , and CO 2 among MOFs. For example, the storage capacity of C 2 H 2 is 234 cm 3 /g -1 (298 K) and 330 cm 3 /g -1 (273K) at 1 atm for CPM-733-dps (the Co 2 V-BDC form, BDC=1,4-benzenedicarboxylate), higher than benchmark MOFs such as MOF-74 and all other pacs members. These high uptake capacities are accomplished with low heat of adsorption, a feature desirable for low-energy-cost adsorbent regeneration. CPM-733-dps is stable and shows no loss of C 2 H 2 adsorption capacity following multiple adsorption–desorption cycles.

25 ENERGY STORAGE↗

DOE OSTI2022

In Situ Synthesized Homochiral Spiroborate Ester Metal–Organic Framework with Mono–, Di–, and Trivalent Cations

Here we report here a one–step method for synthesizing multi–component and in–situ–formed homochiral spiroborate–ester–based metal–organic framework CPM–B1. This unique material successfully integrates COF fragment spiroborate ester within the MOF and simultaneously incorporate homochirality and helicity. In addition, CPM–B1 is a rare example of framework materials that results from the cooperative assembly of three charge–complementary cations: +1 (lithium), +2 (cobalt), and +3 (boron). The sophistication of the co–assembly is further highlighted by the three structural roles of lithium ions. This unique structure contributes to its multi–functional properties such as ionic conductivity and catalytic activity for oxygen reduction reaction (by CPM–B1 carbonized material) and provides a new path to develop MOF materials with complex secondary building units and multi–functional applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Metal-Mediated Directional Capping of Rod-Packing Metal–Organic Frameworks

We report two new rod-packing metal–organic frameworks (RPMOF) are constructed by regulating the in situ formation of the capping agent. In CPM-s7, carboxylate linkers extend 1D manganese-oxide chains in four additional directions, forming 3D RPMOF. The substitution of Mn 2+ with a stronger Lewis acidic Co 2+ , leads to an acceleration of the hydrolysis-prone sulfonate linker, resulting in presence of sulfate ions to reduce two out of the four carboxylate-extending directions, and thus forming a new 2D rod-packing CPM-s8. Density functional theory calculations and magnetization measurements reveal ferrimagnetic ordering of CPM-s8, signifying the potential of exploring 2D RPMOF for effective low-dimensional magnetic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Generative diffusion model surrogates for mechanistic agent-based biological models

Mechanistic, multicellular, agent-based models are commonly used to investigate tissue, organ, and organism-scale biology at single-cell resolution. The Cellular-Potts Model (CPM) is a powerful and popular framework for developing and interrogating these models. CPMs become computationally expensive at large space- and time- scales making application and investigation of developed models difficult. Surrogate models may allow for the accelerated evaluation of CPMs of complex biological systems. However, the stochastic nature of these models means each set of parameters may give rise to different model configurations, complicating surrogate model development. In this work, we leverage denoising diffusion probabilistic models (DDPMs) to train a generative AI surrogate of a CPM used to investigate in vitro vasculogenesis. We describe the use of an image classifier to learn the characteristics that define unique areas of a 2-dimensional parameter space. We then apply this classifier to aid in surrogate model selection and verification. Our CPM model surrogate generates model configurations 20,000 timesteps ahead of a reference configuration and demonstrates approximately a 22x reduction in computational time as compared to native code execution. Our work represents a step towards the implementation of DDPMs to develop digital twins of stochastic biological systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

The Impacts of Horizontal Grid Spacing and Cumulus Parameterization on Subseasonal Prediction in a Global Convection-Permitting Model

Monthlong simulations targeting four Madden–Julian oscillation events made with several global model configurations are verified against observations to assess the roles of grid spacing and convective parameterization on the representation of tropical convection and midlatitude forecast skill. Specifically, the performance of a global convection-permitting model (CPM) configuration with a uniform 3-km mesh is compared to that of a global 15-km mesh with and without convective parameterization, and of a variable-resolution “channel” simulation using 3-km grid spacing only in the tropics with a scale-aware convection scheme. It is shown that global 3-km simulations produce realistic tropical precipitation statistics, except for an overall wet bias and delayed diurnal cycle. The channel simulation performs similarly, although with an unrealistically higher frequency of heavy rain. The 15-km simulations with and without cumulus schemes produce too much light and heavy tropical precipitation, respectively. Without convection parameterization, the 15-km global model produces unrealistically abundant, short-lived, and intense convection throughout the tropics. Only the global CPM configuration is able to capture eastward-propagating Madden–Julian oscillation events, and the 15-km runs favor stationary or westward-propagating convection organized at the planetary scale. The global 3-km CPM exhibits the highest extratropical forecast skill aloft and at the surface, particularly during week 3 of each hindcast. Although more cases are needed to confirm these results, this study highlights many potential benefits of using global CPMs for subseasonal forecasting. Furthermore, results show that alternatives to global convection-permitting resolution—using coarser or spatially variable resolution—feature compromises that may reduce their predictive performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Performance Testing of a Moving Bed Gasifier Using Coal, Biomass, and Waste Plastic Blends to Generate White Hydrogen

The objective of this DOE-funded project by the Electric Power Research Institute, Inc. (EPRI), Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), is to qualify coal, biomass, and plastic waste blends based on performance testing of selected pellet recipes in a pilot-scale updraft moving-bed gasifier. The testing provides relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of the waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are a focus. The gasifier is Hamilton Mauer International, Inc. (HMI)’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips. However, mixtures of these fuels with plastic wastes had not yet been prepared and gasified together. The feedstocks were prepared by California Pellet Mill (CPM) under contract to HMI. The technical tasks for this research project included: • Feed Procurement and Preparation: Nine different feedstocks were prepared from varying compositions of PRB coal, corn stover biomass, and car fluff waste plastics. Fuel pellets were produced by California Pellet Mill (CPM) and shipped to Sotacarbo’s test facility in Italy. • Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different tests that were run, instrumentation used, extractive samples taken, and relevant figures of merit. • Gasifier Testing: Tests were performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstocks generated from varying mixtures of coal, biomass, and plastic wastes. The testing provides information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design. This task will also included work to reassemble the gasifier at Sotacarbo and perform a baseline 100% coal run. • Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results was reported. The results can be used to specify the range of feedstock blends that can be successfully gasified as well as quantify gasifier outputs based on specific blends. The tri-fuel pelletizing conducted at CPM and gasification testing results from Sotacarbo’s 30mm up draft moving bed gasifier are significant. Providing data for an established gasifier to help accelerate its updated design to be able to accommodate feedstocks composed of coal, biomass, and plastic waste. This should ultimately lead to development and commercialization of a lower cost, white hydrogen generation system.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Performance Testing of a Moving-Bed Gasifier Using Coal, Biomass, and Waste Plastic Blends to Generate White Hydrogen

The objective of this DOE-funded project by the Electric Power Research Institute, Inc. (EPRI), Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), is to qualify coal, biomass, and plastic waste blends based on performance testing of selected pellet recipes in a pilot-scale updraft moving-bed gasifier. The testing provides relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of the waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are a focus. The gasifier is Hamilton Mauer International, Inc. (HMI)’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips. However, mixtures of these fuels with plastic wastes had not yet been prepared and gasified together. The feedstocks were prepared by California Pellet Mill (CPM) under contract to HMI. The technical tasks for this research project included: • Feed Procurement and Preparation: Nine different feedstocks were prepared from varying compositions of PRB coal, corn stover biomass, and car fluff waste plastics. Fuel pellets were produced by California Pellet Mill (CPM) and shipped to Sotacarbo’s test facility in Italy. • Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different tests that were run, instrumentation used, extractive samples taken, and relevant figures of merit. • Gasifier Testing: Tests were performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstocks generated from varying mixtures of coal, biomass, and plastic wastes. The testing provides information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design. This task will also included work to reassemble the gasifier at Sotacarbo and perform a baseline 100% coal run. • Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results was reported. The results can be used to specify the range of feedstock blends that can be successfully gasified as well as quantify gasifier outputs based on specific blends. The tri-fuel pelletizing conducted at CPM and gasification testing results from Sotacarbo’s 30mm up draft moving bed gasifier are significant. Providing data for an established gasifier to help accelerate its updated design to be able to accommodate feedstocks composed of coal, biomass, and plastic waste. This should ultimately lead to development and commercialization of a lower cost, white hydrogen generation system.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2021

Gasification of Mixed Blends of Coal, Biomass, and Plastic Waste

The objective of this DOE-funded project by the Electric Power Research Institute, Inc. (EPRI), Hamilton Maurer International (HMI) and Sotacarbo S.p.A. (Sotacarbo), is to qualify coal, biomass, and plastic waste blends based on performance testing of selected pellet recipes in a pilot-scale updraft moving-bed gasifier. The testing provides relevant data to advance the commercial-scale design of the moving-bed gasifier to be able to successfully use these feedstocks to produce hydrogen. In particular, the effects of the waste plastics on feedstock development (i.e., blending and pelletizing) and the resulting products (i.e., syngas compositions, organic condensate production, and ash characteristics) are a focus. The gasifier is Hamilton Mauer International, Inc. (HMI)’s moving-bed gasifier, which has been proven capable of gasifying nearly all coal ranks. It has also shown the ability in prior testing work to gasify wood chips. However, mixtures of these fuels with plastic wastes had not yet been prepared and gasified together. The feedstocks were prepared by California Pellet Mill (CPM) under contract to HMI. The technical tasks for this research project included: • Feed Procurement and Preparation: Nine different feedstocks were prepared from varying compositions of PRB coal, corn stover biomass, and car fluff waste plastics. Fuel pellets were produced by California Pellet Mill (CPM) and shipped to Sotacarbo’s test facility in Italy. • Test Plan Development: A test plan was created to define the test runs to be performed. The test plan detailed the different tests that were run, instrumentation used, extractive samples taken, and relevant figures of merit. • Gasifier Testing: Tests were performed in the pilot-scale gasifier at Sotacarbo using nine different fuel feedstocks generated from varying mixtures of coal, biomass, and plastic wastes. The testing provides information on gasification reaction efficiency/performance, yielding relevant data for models used to scale up the gasifier design. This task will also included work to reassemble the gasifier at Sotacarbo and perform a baseline 100% coal run. • Data Analysis and Reporting: Review of the data, determination of figures of merit, and interpretation of the results was reported. The results can be used to specify the range of feedstock blends that can be successfully gasified as well as quantify gasifier outputs based on specific blends. The tri-fuel pelletizing conducted at CPM and gasification testing results from Sotacarbo’s 30mm up draft moving bed gasifier are significant. Providing data for an established gasifier to help accelerate its updated design to be able to accommodate feedstocks composed of coal, biomass, and plastic waste. This should ultimately lead to development and commercialization of a lower cost, white hydrogen generation system.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2025

The Impacts of Rotational Mixing on the Precipitation Simulated by a Convection Permitting Model

With increased availability of computational resources, regional and global scale convection-permitting model (CPM, Δx ~ 1–10 km) simulations are becoming more common. CPMs have improved accuracy in their representation of deep convection and mesoscale convective systems (MCSs) compared to coarser resolution models. However, CPMs still exhibit convective cloud and precipitation biases relative to observations, notably a lesser frequency of light precipitation rates and greater frequency of heavy precipitation rates. In this work we hypothesize that these CPM biases are related to under-resolved mixing between convective updrafts and their surrounding environment. To test this hypothesis, we introduce a parameterization to the Weather Research and Forecasting model (WRF) that adds a small angular rotation of the grid-scale flow about the axis perpendicular to the plane of convective drafts. This rotated flow is then allowed to alter advection of moisture and hydrometeors. The effects of such mixing on precipitation characteristics are evaluated in month-long 4-km grid spacing simulations over the Amazon. The enhanced mixing transports moisture and condensate from convective cores to other areas including downdrafts. This increases the frequency of low-precipitable water and light precipitation. It also decreases the frequency of intense precipitation from isolated deep convection and MCSs, increases cloud top temperatures, reduces radar echo-top heights, and increases overall precipitation by altering the relationship of precipitation with precipitable water, in better agreement with observations. The results suggest when optimized using multiple observations, such an approach may provide a path toward more accurate representation of convection and precipitation statistics in convection-permitting simulations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

An Optimized Parameterization of Sub‐Grid Scale Advection for Convection Permitting Models

Convection‐permitting models (CPMs) explicitly resolve deep convection yet under‐resolve the organized lateral exchanges among drafts and their environment that control entrainment/detrainment, precipitation efficiency, and mesoscale structure. In this work, we introduce the Optimized Advection Scheme (OAS), which introduces a small rotation of the Cartesian frame of reference for the horizontal winds relative to other variables used in advection that induces cross‐gradient transport to mimic under‐resolved convective mixing. The rotation angle is selected to minimize the Kullback–Leibler divergence between the simulated and satellite observed precipitation intensity distributions, yielding a physically consistent perturbation that is computationally inexpensive and portable. Optimized Advection Scheme is implemented in WRF and evaluated over Amazon (April 2014). It shifts precipitation–precipitable‐water joint distributions toward lighter rain, reduces overly intense rates, and improves mesoscale convective system (MCS) lifetime and propagation. Mechanistically, the added cross‐gradient transport promotes convective detrainment and environmental mixing, which cools and moistens the mid‐troposphere, weakens downward momentum transport, alleviates excessive downwelling shortwave biases, and warms the surface temperature. The optimized rotation angle yields comparable improvements at 4‐km and 1‐km grid spacing, demonstrating resolution‐independent benefits across the CPM gray zone. By targeting the dynamical root of under‐mixed convective circulations, rather than tuning model microphysics or closures, OAS delivers robust, scale‐aware improvements in precipitation statistics, cloud vertical structure, and characteristics of MCS (MCSs), offering a practical pathway to more reliable CPM simulations for weather and climate applications.

CPM↗

DOE OSTI2020

Tunable Metal–Organic Frameworks Based on 8-Connected Metal Trimers for High Ethane Uptake

Metal trimers [M 3 (O/OH)](OOCR) 6 are among the most important structural building blocks. From these trimers, a great success has been achieved in the design of 6- or 9-connected framework materials with various topological features and outstanding gas-sorption properties. In comparison, 8-connected trimer-based MOFs are rare. Given multiple competitive pathways for the formation of 6- or 9-connected frameworks, it remains challenging to identify synthetic or structural parameters that can be used to direct self-assembly process towards trimer-based 8-connected materials. Here, we reveal a viable strategy called angle bending modulation for creating a prototypical MOF type based on 8-connected M 3 (OH)(OOCR) 5 (Py-R) 3 trimers, M = Zn, Co, Fe). As a proof of concept, we synthesized six members in this family using three types of ligands (CPM-80, -81, and -82). These materials do not possess open-metal sites and show excellent uptake capacity for various hydrocarbon gas molecules and inverse C 2 H 6 /C 2 H 4 selectivity. CPM-81-Co, made from 2,5-furandicarboxylate and isonicotinate, features selectivity of 1.80 with high uptake capacity for ethane (123 cm 3 /g -1 ) and ethylene (113 cm 3 /g -1 ) at 298 K and 1 bar.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Simultaneous Control of Flexibility and Rigidity in Pore-Space-Partitioned Metal–Organic Frameworks

Flexi-MOFs are typically limited to low-connected (< 9) frameworks. Here we report a platform-wide approach capable of creating a family of high-connected materials (collectively called CPM-220) that integrate exceptional framework flexibility with high rigidity. We show that the multi-module nature of the pore-space-partitioned pacs (partitioned acs net) platform allows us to introduce flexibility as well as to simultaneously impose high rigidity in a tunable module-specific fashion. The inter-modular synergy has remarkable macro-morphological and sub-nanometer structural impacts. A prominent manifestation at both length scales is the retention of X-ray-quality single crystallinity despite huge hexagonal c-axial contraction (≈ 30%) and harsh sample treatment such as degassing and sorption cycles. CPM-220 sets multiple precedents and benchmarks on the pacs platform in both structural and sorption properties. Furthermore, they possess exceptionally high benzene/cyclohexane selectivity, unusual C 3 H 6 and C 3 H 8 isotherms, and promising separation performance for small gas molecules such as C 2 H 2 /CO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗