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At least 199 records · Page 11

Enhancing CO 2 Transport Across a PEEK‐Ionene Membrane and Water‐Lean Solvent Interface

Abstract Efficient direct air capture (DAC) of CO 2 will require strategies to deal with the relatively low concentration in the atmosphere. One such strategy is to employ the combination of a CO 2 ‐selective membrane coupled with a CO 2 capture solvent acting as a draw solution. Here, the interactions between a leading water‐lean carbon‐capture solvent, a polyether ether ketone (PEEK)‐ionene membrane, CO 2 , and combinations were probed using advanced NMR techniques coupled with advanced simulations. We identify the speciation and dynamics of the solvent, membrane, and CO 2 , presenting spectroscopic evidence of CO 2 diffusion through benzylic regions within the PEEK‐ionene membrane, not spaces in the ionic lattice as expected. Our results demonstrate that water‐lean capture solvents provide a thermodynamic and kinetic funnel to draw CO 2 from the air through the membrane and into the bulk solvent, thus enhancing the performance of the membrane. The reaction between the carbon‐capture solvent and CO 2 produces carbamic acid, disrupting interactions between the imidazolium (Im + ) cations and the bistriflimide anions within the PEEK‐ionene membrane, thereby creating structural changes through which CO 2 can diffuse more readily. Consequently, this restructuring results in CO 2 diffusion at the interface that is faster than CO 2 diffusion in the bulk carbon‐capture solvent.

Walter, Eric D.↗

Bulk Layering Effects of Ag and Cu for Tandem CO 2 Electrolysis

The electrochemical reduction of carbon dioxide (CO 2 ) presents an opportunity to close the carbon cycle and obtain sustainably sourced carbon compounds. In recent years, copper has received widespread attention as the only catalyst capable of meaningfully producing multi-carbon (C 2+ ) species. Notably carbon monoxide (CO) can also be reduced to C 2+ compounds on copper, motivating tandem systems that combine copper and CO-producing species, like silver, to enhance overall C 2+ selectivities. In this work, we examine the impact of layered-combinations of bulk Cu and Ag by varying the location and proportion of the CO-producing Ag layer. We report an effective increase in the C 2+ oxygenate selectivity from 23 % with a 100 nm Cu to 38 % for a 100: 15 nm Cu : Ag layer. Notably, however, for all co-catalyst cases there is an overproduction of CO vs Cu alone, even for 5 nm Ag layers. Lastly, due to restructuring and interlayer mobility of the copper layer it is clear that the stability of copper limits the locational advantages of such tandem solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding Discharge‐Driven Growth of Cathode Impedance in Ni‐Rich NMC Cathodes

Degradation of LiNi x Mn y Co 1-x-y O 2 (NMC)-based lithium-ion batteries depends strongly on cut-off voltage ranges. In addition to the high upper cut-off voltage, a high depth of discharge (i.e., lower cut-off voltage) significantly worsens cathode impedance growth and capacity fade during long-term cycling. However, there is currently no consensus on the mechanism behind the negative role of a deep discharge. Here, this phenomenon was investigated in graphite||NMC cells with single-crystal cathodes (LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NMC622) or LiNi 0.76 Co 0.14 Mn 0.10 O 2 (NMC76)) using targeted aging protocols (constant high-voltage holds vs. charge–discharge cycling), while monitoring transition-metal (TM) dissolution, cathode-electrolyte interface (CEI) impedance, and NMC surface composition. We demonstrate a correlation between discharge-driven CEI impedance growth and increased TM dissolution. Furthermore, this degradation pathway is more pronounced in lower-Ni NMC622 than in higher-Ni (NMC76) under comparable delithiation states at charge, with both compositions undergoing the H2→H3 phase transition. X-ray photoelectron spectroscopy (XPS) reveals NMC composition-dependent evolution of surface lattice oxygen and restructured surface layer composition between charged and discharged states. These findings add mechanistic depth to the role of discharge as an active driver of interfacial degradation and provide new insights into its composition dependence.

25 ENERGY STORAGE↗

Operando XAS/SAXS: Guiding Design of Single-Atom and Subnanocluster Catalysts

Single-atom and subnanocluster catalysts (SSCs) represent a highly promising class of low-cost materials with high catalytic activity and high atom-utilization efficiency. However, SSCs are susceptible to undergo restructuring during the reactions. Exploring the active sites of catalysts through in situ characterization techniques plays a critical role in studying reaction mechanism and guiding the design of optimum catalysts. In situ X-ray absorption spectroscopy/small-angle X-ray scattering (XAS/SAXS) is promising and widely used for monitoring electronic structure, atomic configuration, and size changes of SSCs during real-time working conditions. Unfortunately, there is no detailed summary of XAS/SAXS characterization results of SSCs. The recent advances in applying in situ XAS/SAXS to SSCs are thoroughly summarized in this review, including the atomic structure and oxidation state variations under open circuit and realistic reaction conditions. Furthermore, the reversible transformation of single-atom catalysts (SACs) to subnanoclusters/nanoparticles and the application of in situ XAS/SAXS in subnanoclusters are discussed. To conlcude, the outlooks in modulating the SSCs and developing operando XAS/SAXS for SSCs are highlighted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Just-in-Time Compilation and Link-Time Optimization for OpenMP Target Offloading

Following the mass adoption of external accelerators for high performance computing, the overall performance of many applications has become increasingly dependent on relatively small accelerated kernels. As static analysis is fundamentally limited by dynamic values and external definitions, standard ahead-of-time compilation is not always sufficient to achieve the best performance. Furthermore, many users looking to port an existing application to run on an external accelerator will not want to fundamentally restructure their programs. These and other problems can be addressed through both link-time optimization (LTO) and just-in-time (JIT) compilation, but until now had sparse and inconsistent support from the compiler. In this work, we present a new compilation method that enables device-side LTO as well as a transparent JIT compilation tool-chain for OpenMP target offloading. Our contributions include an entirely new device linking and embedding scheme to enable LTO as well as a novel JIT engine to efficiently optimize OpenMP offloading regions at run-time. We also introduce a persistent caching system to improve end-to-end runtime using the JIT engine and minimize kernel launching overheads. We measure the performance of our LTO and JIT implementation via several real-world scientific applications. With our optimizations we observe significant improvements through LTO on large applications as well as significant end-to-end execution time improvement using JIT.

Tian, Shilei↗

Developing Ultrahigh-Resolution E3SM Land Model for GPU Systems

Designing and refactoring complex scientific code, such as the E3SM land model (ELM), for new computing architectures is challenging. This paper presents design strategies and technical approaches to develop a data-oriented, GPU-ready ELM model using compiler directives (OpenACC/OpenMP). We first analyze the datatypes and processes in the original ELM code. Then we present design considerations for ultrahigh-resolution ELM (uELM) development for massive GPU systems. These techniques include the global data-oriented simulation workflow, domain partition, code porting and data copy, memory reduction, parallel loop restructure and flattening, and race condition detection. We implemented the first version of uELM using OpenACC targeting the NVidia GPUs in the Summit supercomputer at Oak Ridge National Laboratory. During the implementation, we developed a software tool (named SPEL) to facilitate code generation, verification, and performance tuning using these techniques. The first uELM implementation for Nvidia GPUs on Summit delivered promising results: 1) over 98% of the ELM code was automatically generated and tuned by scripts. Most ELM modules had better computational performances than the original ELM code for CPUs. The GPU-ready uELM is more scalable than the CPU code on fully-loaded Summit nodes. Example profiling results from several modules are also presented to illustrate the performance improvements and race condition detection. The lessons learned and toolkit developed in the study are also suitable for further uELM deployment using OpenMP on the first US exascale computer, Frontier, equipped with AMD CPUs and GPUs.

Schwartz, Peter↗

Extending OpenSHMEM with Aggregation Support for Improved Message Rate Performance

OpenSHMEM is a highly efficient one-sided communication API that implements the PGAS parallel programming model, and is known for its low latency communication operations that can be mapped efficiently to RDMA capabilities of network interconnects. However, applications that use OpenSHMEM can be sensitive to point-to-point message rates, as many-to-many communication patterns can generate large amounts of small messages which tend to overwhelm network hardware that has predominantly been optimised for bandwidth over message rate. Additionally, many important emerging classes of problems such as data analytics are similarly troublesome for the irregular access patterns they employ. Message aggregation strategies have been proven to significantly enhance network performance, but their implementation often involves complex restructuring of user code, making them unwieldy. This paper shows how to combine the best qualities of message aggregation within the communication model of OpenSHMEM such that applications with small and irregular access patterns can improve network performance while maintaining their algorithmic simplicity. We do this by providing a path to a message aggregation framework called conveyors through a minimally intrusive OpenSHMEM extension introducing aggregation contexts that fit more naturally to the OpenSHMEM atomics, gets, and puts model. We test these extensions using four of the bale 3.0 applications which contain essential many-to-many access patterns to show how they can produce performance improvements of up to 65×.

Welch, Aaron↗

Plant invasion impacts on fungal community structure and function depend on soil warming and nitrogen enrichment

The impacts of invasive species on biodiversity may be mitigated or exacerbated by abiotic environmental changes. Invasive plants can restructure soil fungal communities with important implications for native biodiversity and nutrient cycling, yet fungal responses to invasion may depend on numerous anthropogenic stressors. In this study, we experimentally invaded a long-term soil warming and simulated nitrogen deposition experiment with the widespread invasive plant Alliaria petiolata (garlic mustard) and tested the responses of soil fungal communities to invasion, abiotic factors, and their interaction. We focused on the phytotoxic garlic mustard because it suppresses native mycorrhizae across forests of North America. We found that invasion in combination with warming, but not under ambient conditions or elevated nitrogen, significantly reduced soil fungal biomass and ectomycorrhizal relative abundances and increased relative abundances of general soil saprotrophs and fungal genes encoding for hydrolytic enzymes. These results suggest that warming potentially exacerbates fungal responses to plant invasion. Soils collected from uninvaded and invaded plots across eight forests spanning a 4 °C temperature gradient further demonstrated that the magnitude of fungal responses to invasion was positively correlated with mean annual temperature. Our study is one of the first empirical tests to show that the impacts of invasion on fungal communities depends on additional anthropogenic pressures and were greater in concert with warming than under elevated nitrogen or ambient conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Impact of Mg on Pd-based Methane Oxidation Catalysts for Lean-burn Natural Gas Emissions Control

More efficient lean-burn, natural gas engines are limited by greenhouse gas emissions due to methane oxidation catalysts (MOC) that suffer from water inhibition and high temperature activation. Herein, we report that the addition of Mg to supported 1 wt.% Pd MOCs improved hydrothermal stability even after severe hydrothermal aging. The superior methane oxidation activity compared to the corresponding Mg-free catalyst was attributed to (1) influence of Mg during surface roughening and restructuring at 700 °C on metal-support interaction, (2) reducibility of PdOx sites and (3) preferential stabilization of active Pd (1 0 0) facets in the sample as was evidenced by H 2 TPR and CO TPD characterization experiments. Methane conversion under synthetic exhaust conditions relevant to natural gas, lean-burn engines were investigated. In conclusion, BET, TPR, CO pulse chemisorption followed by TPD provided valuable insights into the surface area, pore volume, reducibility, Pd dispersion and Pd particle size of the selected catalyst samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hollow-structured Ni-N-C catalysts for highly selective CO 2 electroreduction

Atomically dispersed single-atom catalysts have emerged as promising non-precious catalyst alternatives to expensive Ag and Au catalysts for electrochemical CO 2 reduction reaction (CO 2 RR). In particular, nickel-nitrogen-carbon (Ni-N-C) catalysts have demonstrated a high faradaic efficiency (FE) toward CO formation at low overpotentials. Nonetheless, the exact nature of Ni active sites under CO 2 RR remains elusive and conventional Ni-N-C catalysts are limited by microporosity and low density of Ni single atoms, hindering performance in CO 2 electrolyzers. Here, we report the synthesis of hollow-structured Ni-N-C ( hs -Ni-N-C) catalysts via a post-synthesis modification (PSM) strategy using partial ligand exchange of 2-methylimidazole with 3-amino-1,2,4-triazole. This approach enables the formation of a hollow structure, resulting in more than a twofold increase in Ni atom density compared to regular Ni-N-C (r-Ni-N-C). In a zero-gap CO 2 electrolyzer, the optimized hs -Ni-N-C allows for achieving an FE CO of 97% at a current density of > 100 mA cm⁻ 2 , while maintaining high CO selectivity with stable performance over 100 h at 2.5 V. hs-Ni-N-C shows a more than sevenfold increase in the CO partial current density relative to r-Ni-N-C resulting from the combined effects of a higher density of Ni single-atom sites, improved kinetics, and lower transport resistance under the operating conditions, as indicated by electrochemical impedance spectra and distribution of relaxation times analysis. Operando high energy-resolution X-ray absorption spectroscopy (XAS) reveals that atop-bonded CO on Ni single sites induces dynamic transformations of the Ni–N coordination environment, leading to a symmetric coordination structure of hs -Ni-N-C. Under CO 2 RR, the catalysts undergo a more pronounced structural change and form a minor fraction of Ni nanoparticles. Density functional theory calculations are consistent with the XAS results and provide molecular insights showing that the interplay between protonation and CO adsorption leads to adsorbate-induced restructuring of the Ni single atom. This work demonstrates the synergistic role of hollow structure and high-density Ni atoms in governing CO 2 RR selectivity and provides mechanistic insights into the structural dynamics of single-atom catalysts under operating conditions.

36 MATERIALS SCIENCE↗

Power market models for the clean energy transition: State of the art and future research needs

As power systems around the world are rapidly evolving to achieve decarbonization objectives, it is crucial that power system planners and operators use appropriate models and tools to analyze and address the associated challenges. This paper provides a detailed overview of the properties of power market models in the context of the clean energy transition. We review common power market model methodologies, their readiness for low- and zero-carbon grids, and new power market trends. Based on the review, we suggest model improvements and new designs to increase modeling capabilities for future grids. The paper highlights key modeling concepts related to power system flexibility, with a particular focus on hydropower and energy storage, as well as the representation of grid services, price formation, temporal structure, and the importance of uncertainty. We find that a changing resource mix, market restructuring, and growing price uncertainty require more precise modeling techniques to adequately capture the new technology constraints and the dynamics of future power markets. In particular, models must adequately represent resource opportunity costs, multi-horizon flexibility, and energy storage capabilities across the full range of grid services. Moreover, at the system level, it is increasingly important to consider sub-hourly time resolution, enhanced uncertainty representation, and introduce co-optimization for dual market clearing of energy and grid services. Likewise, models should capture interdependencies between multiple energy carriers and demand sectors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Irradiation-induced amorphization of UO 2 films prepared by spraying-assisted combustion synthesis

Spraying-assisted combustion synthesis with uranyl nitrate – acetylacetone – 2-methoxyethanol solutions was used to prepare UO 2 films on an aluminum alloy substrate. The tuning of the spraying parameters and annealing temperatures allowed the preparation of UO 2 films with thicknesses varying from 10–300 nm and 5–10 nm UO 2 grain size. High-resolution electron microscopy and X-ray photoelectron spectroscopy showed that increasing the annealing temperature promotes Mg diffusion from the substrate into the films. The incorporation of Mg reduced the overall crystallinity of the films. The irradiation with Ar 2+ ions (1.7 MeV energy and a fluence of 2 × 10 16 ions/cm 2 ) did not degrade the quality of the films. However, the Mg content significantly influenced the irradiation-induced restructuring of the UO 2 films. Irradiated films with low or no Mg content exhibit high crystallinity, and the UO 2 /Al interfacial layer becomes highly porous. Films with higher Mg content are mostly amorphized after irradiation. The origin of irradiation-induced amorphization was related to the formation of Mg y U 1-y O 2±x solid solutions. Chemically complex, pore-free, and amorphous Mg-Al-O film/substrate interfacial layers enable continuous Mg diffusion during irradiation. As a result, the gradual increase in Mg amounts triggers irradiation-induced precipitation of a crystalline MgO-rich phase within the amorphous films.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

TiO x -supported Na-Mn-W oxides for the oxidative coupling of methane

Supported Na-Mn-W oxides are among the most studied catalysts for the oxidative coupling of methane (OCM) because of their superior thermal stability and relatively high C 2+ product yields. However, because of the structural complexity, the roles of each component in these catalysts have been controversial. In this work, WO x and MnO x sites were supported on titanate nanowires and employed in OCM studies. Compared to the commonly studied silica support, which is subject to severe restructuring due to the Na-induced crystallization, titanate support not only serves as a reservoir for alkali metals (e.g., Na), but also stabilizes isolated MnO x species. The catalytic performance of the titanate-based catalyst is similar to that of reference catalyst, MnO x /Na 2 WO 4 /SiO 2 , with a synergistic effect between MnO x and WO x sites. Further, advanced electron microscopy, X-ray diffraction, infrared spectroscopy, and X-ray absorption near edge structure spectroscopy suggest that the basic NaO x and MnO x species have strong interactions with the acidic WO x and TiO x species, which might contribute to the high selectivity toward C 2+ products and suppressed CO x formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Code modernization strategies for short-range non-bonded molecular dynamics simulations

Modern HPC systems are increasingly relying on greater core counts and wider vector registers. Thus, applications need to be adapted to fully utilize these hardware capabilities. One class of applications that can benefit from this increase in parallelism are molecular dynamics simulations. In this paper, we describe our efforts at modernizing the ESPResSo++ simulation package for molecular dynamics by restructuring its particle data layout for efficient memory accesses and applying vectorization techniques to benefit the calculation of short-range non-bonded forces, which results in an overall three times speedup and serves as a baseline for further optimizations. We also implement fine-grained parallelism for multi-core CPUs through HPX, a C++ runtime system which uses lightweight threads and an asynchronous many-task approach to maximize concurrency. Our goal is to evaluate the performance of an HPX-based approach compared to the bulk-synchronous MPI-based implementation. This requires the introduction of an additional layer to the domain decomposition scheme that defines the task granularity. On spatially inhomogeneous systems, which impose a corresponding load-imbalance in traditional MPI-based approaches, we demonstrate that by choosing an optimal task size, the efficient work-stealing mechanisms of HPX can overcome the overhead of communication resulting in an overall 1.4 times speedup compared to the baseline MPI version.

97 MATHEMATICS AND COMPUTING↗

SPARC: Structural properties associated with residue constraints

SPARC facilitates the generation of plausible hypotheses regarding underlying biochemical mechanisms by structurally characterizing protein sequence constraints. Such constraints appear as residues co-conserved in functionally related subgroups, as subtle pairwise correlations (i.e., direct couplings), and as correlations among these sequence features or with structural features. SPARC performs three types of analyses. First, based on pairwise sequence correlations, it estimates the biological relevance of alternative conformations and of homomeric contacts, as illustrated here for death domains. Second, it estimates the statistical significance of the correspondence between directly coupled residue pairs and interactions at heterodimeric interfaces. Third, given molecular dynamics simulated structures, it characterizes interactions among constrained residues or between such residues and ligands that: (a) are stably maintained during the simulation; (b) undergo correlated formation and/or disruption of interactions with other constrained residues; or (c) switch between alternative interactions. We illustrate this for two homohexameric complexes: the bacterial enhancer binding protein (bEBP) NtrC1, which activates transcription by remodeling RNA polymerase (RNAP) containing σ 54 , and for DnaB helicase, which opens DNA at the bacterial replication fork. Based on the NtrC1 analysis, we hypothesize possible mechanisms for inhibiting ATP hydrolysis until ADP is released from an adjacent subunit and for coupling ATP hydrolysis to restructuring of σ 54 binding loops. Based on the DnaB analysis, we hypothesize that DnaB ‘grabs’ ssDNA by flipping every fourth base and inserting it into cavities between subunits and that flipping of a DnaB-specific glutamine residue triggers ATP hydrolysis.

97 MATHEMATICS AND COMPUTING↗

Mapping thermal energy storage technologies with advanced nuclear reactors

Advanced nuclear power plants (NPPs) will potentially need to operate in environments where power generation flexibility is more highly valued than the stability or baseload generation capability for conventional demand curves. Thermal energy storage (TES) systems would enable NPPs to respond nimbly to market variability and could also position advanced NPPs to participate differently in restructured markets, thus further enhancing their economic competitiveness. TES systems could also benefit the electric grid by eliminating the need for peaking plants, as well as by improving the economic performance of baseload NPPs. While TES technologies afford a unique opportunity to address many of these challenges, the applicability of these systems is also complicated by the fact that various advanced NPPs are designed differently, each with its own temperature range, size, operating fluids, and operating conditions. Hence, TES systems face significant barriers to investment, as more information on their compatibility and performance metrics is needed to quantify the advantages provided by each, as well as the challenges these technologies might face if coupled with a particular type of advanced NPP. This study explores the possibility of integrating a wide variety of TES technologies with various categories of advanced NPPs, based on their operating characteristics. To help decision makers, users and developers decide which TES technology is best suited to a particular category of advanced NPPs, this research present a Phenomena Identification and Ranking Table (PIRT) analysis of 10 TES systems that could potentially be coupled with advanced NPPs, which themselves are divided into nine categories based on their operating conditions. Then, each advanced NPP category is evaluated for compatibility with the 10 TES systems by assembling and discussing a database of information concerning 10 engineering questions, defined herein in as figures of merit (FOMs), such as: technology readiness level (TRL), temperature compatibility, energy density, size, cycle frequency, ramp time, realignment frequency, geographic needs, environmental impact, and interventions. By assembling a database of information concerning the TES technologies' compatibility with various advanced NPP systems, this study can help developers acquaint themselves with a particular TES technology before choosing to build a new integrated installation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Energy System Transitions and Low-Emission Pathways in Australia, Brazil, Canada, China, EU-28, India, Indonesia, Japan, Republic of Korea, Russia, and United States

The Paris Agreement invited Parties to submit long-term, low-emission development strategies. This study presents national low-emission scenarios to inform such strategies for Australia, Brazil, Canada, China, EU, India, Indonesia, Japan, Russia, Republic of Korea and the USA. The study uses country-level energy–economy and integrated assessment models (IAMs) that incorporate detailed and disaggregated representations of the energy demand and supply systems that are difficult to capture in global IAMs. Models were used to explore low-carbon pathways up to 2050, providing insights in their implications for country emissions, energy system restructuring, energy–economy indicators and system costs. The analysis shows that the low-carbon scenarios of most economies studied here are consistent with pathways limiting global warming to below 2 °C.

Fragkos, Panagiotis↗

Belowground cross-trophic networks impact CH4 and CO2 emissions in degraded alpine peatlands

Belowground organisms forming complex cross-trophic ecological networks are essential for maintaining peatland carbon stability and energy flow. However, how peatland degradation affects the biodiversity and cross-trophic ecological networks of soil communities remains poorly understood. Here, we examined the degradation effects on soil prokaryotes (i.e., bacteria, archaea), fungi and nematodes in alpine peatlands on the eastern Tibetan Plateau, characterized by varying water table depths (indicating degradation levels). We found that peatland degradation, accompanied by significant shifts in soil moisture and pH (P < 0.05), reduced the taxonomic richness and phylogenetic diversity of prokaryotes, fungi, and nematodes, particularly in deeper soil layers (20–50 cm). Crucially, peatland degradation weakened potential cross-trophic interactions within bipartite networks of prokaryotes-nematodes and fungi-nematodes, resulting in less than 6.5 %–28.8 % of unchanged modules. Degradation-induced changes in soil moisture and pH were identified as primary drivers of biodiversity loss and network restructuring. Furthermore, such changes of belowground cross-trophic networks (particularly prokaryote-nematode) were significantly correlated with greenhouse gas emissions, such as decreased CO2 emissions, maintained CH4 emissions (leading to a higher CH4/CO2 ratio in deep layers), and reduced temperature sensitivity (Q10) of soil respiration. These findings underscore the critical need to protect soil biodiversity and cross-trophic networks in peatlands, particularly under the threat of climate change, to preserve peatland carbon stocks and maintain ecosystem stability. Our findings highlight that belowground cross-trophic networks are pivotal to decipher soil carbon dynamics of degraded peatlands and project the fate of peatland carbon stocks under future climate change scenarios.

Cross-trophic networks↗