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Pathways to Carbon Neutrality 2050 in Malaysia and Kuala Lumpur

Malaysia has recently set an ambitious target of achieving carbon neutrality as early as 2050. To accomplish this, the country will need to strategically reduce its emissions across all sectors. In 2020, Malaysia emitted approximately 368 MtCO2e, with the largest sources of emissions including electricity (36% of total emissions), transportation (17%), and industry (15%)1. We find that the greatest reductions in emissions can therefore come from decarbonizing power generation and electrifying end-use sectors. Digitalization, smart technologies, and improved energy efficiency will significantly reduce economy-wide energy consumption. By leveraging efficient technologies, both Malaysia and Kuala Lumpur can address the challenges posed by rapid urbanization and climate change. Digitalization is a broad category that includes a variety of measures; for example, the wide adoption of high-efficiency appliances and lighting or improved building energy codes in the buildings sector. Similarly, technological improvements can advance industrial energy efficiency, and for transportation, smart technologies cover a shift from private to public transportation and the greater use of electric vehicles. While renewable energy (RE) will play a crucial role in decarbonization, achieving carbon neutrality in certain sectors will be difficult without emerging technologies like carbon capture and storage (CCS) and innovative fuel sources such as hydrogen. In order for Malaysia to rely on CCS as a mitigation option, early investment and incentives to the private sector will be critical. This holds for the use of hydrogen as well: investing in the necessary technology, infrastructure, and human capital will allow Malaysia to position itself as an innovator in the region and leverage these advanced technologies as a key part of its climate strategy. Another possible carbon removal option other than CCS would be a land-use sink; however, given that Malaysia is still developing and may deforest in the near-term, this report does not focus on the mitigation potential of land-use change. With its innovative and bold climate plans, Kuala Lumpur is primed to be a leader in regional climate change efforts. Kuala Lumpur is also engaged in several international collaborations to ensure sustainable city development such as the C40 network and the ASEAN Smart Cities Partnership. As such, the city will play a critical role in contributing to Malaysia’s overall climate goals and as a policy trendsetter through ambitious, scalable plans. One key factor in these emissions reductions is that Kuala Lumpur has full control over its building guidelines, allowing for ambitious policies resulting in significant emissions reductions. However, in other sectors, Kuala Lumpur has less direct control over regulations; for example, power generation and integration of RE are largely in the hands of the Malaysian government. With limited and primarily light industry, Kuala Lumpur’s contributions to emissions reductions here are curbed. And, while Kuala Lumpur has control over local transportation policies like increasing access to and quality of public transportation, broad shifts in transportation will stem from national-level policies. As such, multi-level governance is an integral component of Malaysia’s climate strategy and coordination between local and national governments will be essential in reducing emissions and achieving other climate goals. This report addresses these and other key challenges and opportunities Malaysia faces on the road to carbon neutrality.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Subsea processor for underwater drilling operations

A subsea processor may be located near the seabed of a drilling site and used to coordinate operations of underwater drilling components. The subsea processor may be enclosed in a single interchangeable unit that fits a receptor on an underwater drilling component, such as a blow-out preventer (BOP). The subsea processor may issue commands to control the BOP and receive measurements from sensors located throughout the BOP. The subsea processor may relay information to the surface for recording or monitoring. The subsea processor may also be programmed with a model from which to base operation of the BOP, such as in emergency conditions.

42 ENGINEERING↗

Data for Physiological Controls on Carbon Fluxes and Biomass Production in Miscanthus: Insights From a Process- Based Agroecosystem Model

Biomass crops serve as essential feedstocks for renewable energy and bioproducts and play a critical role in achieving lower emissions in the transportation sector. However, dedicated perennial biomass crops such as Miscanthus × giganteus (Miscanthus) remain underrepresented in process- based agroecosystem models, limiting robust evaluation of their economic and environmental performance. In this study, we developed a data- constrained representation of the sterile triploid Miscanthus (IL clone) within the process- based model ecosys, integrating global sensitivity analysis, ensemble simulation, and parameter calibration. Planting, harvesting, and fertilization practices consistent with field management were incorporated, and phenology was constrained using PhenoCam- derived Green Chromatic Coordinate (GCC) data. Using the Morris global sensitivity analysis method, we identified 11 key physiological parameters governing plant carbon, water, and nutrient relations, particularly processes associated with CO2 assimilation. We then conducted ensemble simulations by perturbing these parameters and calibrated the model against eddy covariance fluxes and field- measured biomass. Building on the calibrated operating state, parameter- response analyses show that different photosynthetic processes influence productivity in different ways. Protein allocation determines whether productivity increases toward a higher level, whereas electron transport capacity controls additional gains once protein allocation approaches saturation. These findings demonstrate that parameter importance depends on physiological context and on which photosynthetic processes remain limiting. Calibration and validation against observations show that ecosys can reliably reproduce carbon and water fluxes, as well as both above- and belowground biomass, with post- calibration GPP R2 improving from 0.67 to 0.95 during the calibration period and remaining high during validation (R2 = 0.95). These results provide a mechanistic foundation for regional simulations and sustainable bioenergy assessments.

Carbon↗

Modeling Framework for Data Center

This chapter highlights the critical need for advanced modeling of data centers due to their rapidly increasing energy consumption and impact on grid reliability. Driven by the demand for AI applications, data centers are projected to consume a significant portion of US energy by 2028, putting stress on an already challenged power grid. The chapter emphasizes the importance of "fast" time-scale models to understand the dynamic interactions between data centers and the grid, especially given the rapid power fluctuations of AI workloads. It outlines a modeling framework that includes both offline and real-time EMT domain simulations, detailing the necessary representations for various components like utility interfaces, transformers, IT loads, UPS, cooling loads, Battery Energy Storage Systems (BESS), generators, protection systems, and higher-level control systems. While standard simulation tools like PSCAD offer basic models, custom development is often required to accurately capture the unique and fast-changing behaviors of modern data centers. The chapter also discusses key metrics and test cases for validating these models, focusing on transient load responses, protection relay coordination, and demand flexibility. Finally, it addresses the challenges of modeling large-scale data centers, such as computational complexity and the trade-off between model fidelity and practicality, suggesting hybrid modeling approaches as a solution. The overarching goal is to create a robust framework that helps assess data center impacts on grid stability, identify vulnerabilities, and inform the development of standards for reliable integration of these large loads into the bulk power system.

25 ENERGY STORAGE↗

Machine learning-based real-time kinetic profile reconstruction in DIII-D

Abstract Kinetic equilibrium reconstruction plays a vital role in the physical analysis of plasma stability and control in fusion tokamaks. However, the traditional approach is subjective and prone to human biases. To address this, the consistent automatic kinetic equilibrium reconstruction (CAKE) method was introduced, providing objective results. Nonetheless, its offline nature limits its application in real-time plasma control systems (PCSs). To address this limitation, we present RTCAKENN, a machine learning model that approximates 7 CAKE-level output profiles, namely pressure, inverse q , toroidal current density, electron temperature and density, carbon ion impurity temperature and rotation profiles, using real-time available inputs. The deep neural network consists of an encoder layer, where the scalars and interdependent inputs such as plasma boundary coordinates and motional Stark effect data are encoded using multi-layer perceptrons (MLPs), while profile inputs are encoded by 1D convolutional layers. The encoded data is passed through a MLP for latent feature extraction, before being decoded in the decoding layers, which consist of upsampling and convolutional layers. RTCAKENN has been implemented in the DIII-D PCS and our model achieves accuracy comparable to CAKE and surpasses existing real-time alternatives. Through clever dropout training, RTCAKENN exhibits robustness and can operate even in the absence of Thomson scattering data or charge exchange recombination data. It executes in under 8 ms in the real-time environment, enabling future application in real-time control and analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Electronic Structures of Iron in Oxide Glasses via 1s3p Resonant Inelastic X-ray Scattering

Electronic structures of iron in glasses are essential for unraveling the effect of transition metals on amorphous networks and controlling the electro-optical and transport properties of advanced glasses and amorphous energy-storing materials. The electronic configurations around iron in glasses, however, remain not well understood due to the structural disorders arising from multiple iron species with distinct valence, coordination, and spin states. Here, the first 1s3p resonant inelastic X-ray scattering (RIXS) for oxide glasses identifies hidden electronic configurations for Fe 2+ and Fe 3+ in amorphous networks. The results allow us to quantify the composition-induced evolution of oxygen ligand–field interactions of high-spin Fe 3d states with varying valence and coordination environments in complex glasses. The distinct electronic structures account for the electronic origins of iron-induced changes in the glass properties. The results offer prospects for a simultaneous probing of valence, coordination, and spin states of transition metals in diverse multicomponent oxide glasses and functional amorphous solids via 1s3p RIXS.

Kim, Yong-Hyun [Seoul National Univ. (Korea, Repub↗

Heterogenous catalysis for oxygen tolerant photoredox atom transfer radical polymerization and small-molecule dehalogenation

Heterogeneous photocatalysts (PCs) have garnered attention for their sustainability and cost-effectiveness. Despite the existence of various types of these PCs, their synthesis often involves complex, multi-step procedures and laborious purification. Herein, we propose a simple method for attaching small-molecule photocatalytic species onto crosslinked 3-D polymer networks as insoluble scaffolds to create robust heterogeneous PCs. The highly swellable poly(ethylene glycol)-based ChemMatrix (CM) resin, known for its amphiphilic properties and high functional group loading, facilitated the covalent immobilization of the photoredox dye Eosin Y (EY), but also streamlined functionalization with Ir( III ) complexes. The resulting heterogeneous CM-EY demonstrated efficient photocatalytic performance in open-to-air dual photoredox catalysis of atom transfer radical polymerization (photo-ATRP) under green light. This was confirmed by the well-controlled synthesis of polymers with molecular masses ranging from 20 kDa to 300 kDa and low dispersities. Furthermore, CM-EY exhibited excellent photostability and recyclability over multiple cycles of ATRP. The heterogeneous catalysis of photo-ATRP provided high temporal control and enabled benign conditions for synthesizing protein-polymer hybrids (PPH). When combined with the initiator-modified CM (CM-BIB), CM-EY facilitated the solid-phase synthesis of homopolymers and block copolymers with recyclable performance. However, the coordinatively bound Ir@CM showed decreased catalytic activity and efficiency toward photoredox dehalogenation due to the leaching of active species during recycling. This study highlights the advantages of the covalent linking of catalysts to solid supports over non-covalent interactions, underscoring the potential of functionalized polymer resin as a promising scaffold. Such an approach offers customization and tunability, presenting opportunities for innovation in green chemistry.

Kapil, Kriti↗

Enhancing the activity of Pd ensembles on graphene by manipulating coordination environment

Atomic dispersion of metal catalysts on a substrate accounts for the increased atomic efficiency of single-atom catalysts (SACs) in various catalytic schemes compared to the nanoparticle counterparts. However, lacking neighboring metal sites has been shown to deteriorate the catalytic performance of SACs in a few industrially important reactions, such as dehalogenation, CO oxidation, and hydrogenation. Metal ensemble catalysts (M n ), an extended concept to SACs, have emerged as a promising alternative to overcome such limitation. Inspired by the fact that the performance of fully isolated SACs can be enhanced by tailoring their coordination environment (CE), we here evaluate whether the CE of M n can also be manipulated in order to enhance their catalytic activity. We synthesized a set of Pd ensembles (Pd n ) on doped graphene supports (Pd n /X-graphene where X = O, S, B, and N). We found that introducing S and N onto oxidized graphene modifies the first shell of Pd n converting Pd–O to Pd–S and Pd–N, respectively. Also, we further found that the B dopant significantly affected the electronic structure of Pd n by serving as an electron donor in the second shell. We examined the performance of Pd n /X-graphene toward selective reductive catalysis, such as bromate reduction, brominated organic hydrogenation, and aqueous-phase CO 2 reduction. We observed that Pd n /N-graphene exhibited superior performance by lowering the activation energy of the rate-limiting step, i.e., H 2 dissociation into atomic hydrogen. The results collectively suggest controlling the CE of SACs in an ensemble configuration is a viable strategy to optimize and enhance their catalytic performance.

36 MATERIALS SCIENCE↗

Physiological Controls on Carbon Fluxes and Biomass Production in Miscanthus: Insights From a Process‐Based Agroecosystem Model

Biomass crops serve as essential feedstocks for renewable energy and bioproducts and play a critical role in achieving lower emissions in the transportation sector. However, dedicated perennial biomass crops such as Miscanthus × giganteus (Miscanthus) remain underrepresented in process-based agroecosystem models, limiting robust evaluation of their economic and environmental performance. In this study, we developed a data-constrained representation of the sterile triploid Miscanthus (IL clone) within the process-based model ecosys, integrating global sensitivity analysis, ensemble simulation, and parameter calibration. Planting, harvesting, and fertilization practices consistent with field management were incorporated, and phenology was constrained using PhenoCam-derived Green Chromatic Coordinate (GCC) data. Using the Morris global sensitivity analysis method, we identified 11 key physiological parameters governing plant carbon, water, and nutrient relations, particularly processes associated with CO 2 assimilation. We then conducted ensemble simulations by perturbing these parameters and calibrated the model against eddy covariance fluxes and field-measured biomass. Building on the calibrated operating state, parameter-response analyses show that different photosynthetic processes influence productivity in different ways. Protein allocation determines whether productivity increases toward a higher level, whereas electron transport capacity controls additional gains once protein allocation approaches saturation. These findings demonstrate that parameter importance depends on physiological context and on which photosynthetic processes remain limiting. Calibration and validation against observations show that ecosys can reliably reproduce carbon and water fluxes, as well as both above- and belowground biomass, with post-calibration GPP R 2 improving from 0.67 to 0.95 during the calibration period and remaining high during validation (R 2 = 0.95). These results provide a mechanistic foundation for regional simulations and sustainable bioenergy assessments.

ecosys↗

A Holistic Approach for Elucidating Local Structure, Dynamics, and Speciation in Molten Salts with High Structural Disorder

To examine ion solvation, exchange, and speciation for minority components in molten salts (MS) typically found as corrosion products, we propose a multimodal approach combining extended X-ray absorption fine structure (EXAFS) spectroscopy, optical spectroscopy, ab initio molecular dynamics (AIMD) simulations, and rate theory of ion exchange. Going beyond conventional EXAFS analysis, our method can accurately quantify populations of different coordination states of ions with highly disordered coordination environments via linear combination fitting of the EXAFS spectra of these coordination states computed from AIMD to the experimental EXAFS spectrum. In a case study of dilute Ni(II) dissolved in the ZnCl 2 +KCl melts, our method reveals heterogeneous distributions of coordination states of Ni(II) that are sensitive to variations in temperature and melt composition. These results are fully explained by the difference in the chloride exchange dynamics at varied temperatures and melt compositions. Finally, this insight will enable a better understanding and control of ion solubility and transport in MS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

University of Kentucky measurements of wind, temperature, pressure and humidity in support of LAPSE-RATE using multisite fixed-wing and rotorcraft unmanned aerial systems

In July 2018, unmanned aerial systems (UASs) were deployed to measure the properties of the lower atmosphere within the San Luis Valley, an elevated valley in Colorado, USA, as part of the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE). Measurement objectives included detailing boundary layer transition, canyon cold-air drainage and convection initiation within the valley. Details of the contribution to LAPSE-RATE made by the University of Kentucky are provided here, which include measurements by seven different fixed-wing and rotorcraft UASs totaling over 178 flights with validated data. The data from these coordinated UAS flights consist of thermodynamic and kinematic variables (air temperature, humidity, pressure, wind speed and direction) and include vertical profiles up to 900 m above the ground level and horizontal transects up to 1500 m in length. These measurements have been quality controlled and are openly available in the Zenodo LAPSE-RATE community data repository (https://zenodo.org/communities/lapse-rate/, last access: 23 July 2020), with the University of Kentucky data available at https://doi.org/10.5281/zenodo.3701845 (Bailey et al., 2020).

54 ENVIRONMENTAL SCIENCES↗

Load Shifting with Space Conditioning Heat Pumps During Heating Season in the Pacific Northwest

Ductless mini- and multi-split heat pumps are commonly deployed in Pacific Northwest residences, which historically have inefficient space heating and no space cooling. Heat pumps provide these residences with more energy-efficient space heating in the winter and space cooling for increasingly warm summer periods. For many of these applications, heat pumps add a new electrical load at the residence, compelling regional utilities to seek to understand their impacts on the electrical grid and opportunities for load management. In coordination with regional utilities, this study examined the winter load-shifting potential of residential multi-split heat pumps with variable capacity technology. The study included nine residential sites with a total of 20 ductless indoor units, which underwent simulated smart grid control. Grid control functionality was provided through the CTA-2045 communication protocol and included offsetting temperature setpoints for individual indoor units in the study. Field data collection included whole-house and heating, ventilation, and air conditioning electrical power consumption; indoor zone temperatures; occupant surveys; and CTA-2045 curtailment data for both baseline and simulated load-shifting events by site. This paper provides an overview of the load-shifting strategies and aggregated results from winter data collection.

ASHRAE, Heat pump, energy effciency, residential b↗

Infrared-Fused Vision-Based Thermoregulation Performance Estimation for Personal Thermal Comfort-Driven HVAC System Controls

Thermal comfort is one of the primary factors influencing occupant health, well-being, and productivity in buildings. Existing thermal comfort systems require occupants to frequently communicate their comfort vote via a survey which is impractical as a long-term solution. Here, we present a novel thermal infrared-fused computer vision sensing method to capture thermoregulation performance in a non-intrusive and non-invasive manner. In this method, we align thermal and visible images, detect facial segments (i.e., nose, eyes, face boundary), and accordingly read the temperatures from the appropriate coordinates in the thermal image. We focus on the human face since it is often clearly visible to cameras and is not merged into a hot background (unlike hands). We use a regularized Gaussian Mixture model to track the thermoregulation changes over time and apply a heuristic algorithm to extract hot and cold indices. We present a personalized and a generalized comfort modeling method, selected based on the availability of the occupant historical indices measurements in a neutral environment, and use the time-series of the hot and cold indices to define corrections to HVAC system operations in the form of setpoint constraints. To evaluate the efficacy of our proposed approach in responding to thermal stimuli, we designed a series of controlled experiments to simulate exposure to cold and hot environments. While applying personalized modeling showed an acceptable average accuracy of 91.3%, the generalized model’s average accuracy was only 65.2%. This shows the importance of having access to physiological records in modeling and assessing comfort. We also found that individual differences should be considered in selecting the cooling and heating rates when some knowledge of the occupant’s overall thermal preference is available.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The Transactive Energy Network Template Metamodel

While transactive energy, which is defined as an allocation of electricity based on dynamically discovered values or prices, has been extensively studied, its uptake and use has been slow. This report describes a tool, the transactive network template, which should hasten the creation and uptake of transactive energy networks. Some basic principles of transactive energy are familiar from existing wholesale electricity markets. Locational prices are calculated today for zones within bulk electric transmission systems. Locational prices differ while accounting for the locational costs of electricity generation and the losses and constraints incurred when electricity is transmitted from generators and distributed to consumers. A transactive energy network might include these transmission zones. However, current research strives to apply transactive energy also in electricity distribution circuits, buildings, and even for individual generating and consuming devices. At the same time, researchers explore how to apply transactive energy in real time during increasingly shorter time intervals. Automated computational agents become necessary as transactive energy becomes applied to smaller circuit zones and at faster dynamic timescales. A transactive energy network is an example of a multi-agent system. Each zone in the network is represented by its transactive agent, which makes decisions for and acts on behalf of a business entity that is responsible for and manages one of the circuit regions. A transactive energy network is also an example of a decentralized, distributed control system. Control decisions and responsibilities are distributed among the network’s transactive agents. The transactive agents are independent; that is, there typically is no centralized authority or oversight function. Instead, transactive agents exchange transactive signals and thereby negotiate the prices and quantities of electricity that they will exchange. Initially, the circuit regions and responsibilities of transactive agents appear to be very dissimilar. Each circuit region may comprise transmission, distribution, or building-level circuits. Each has a unique position and electrical connectivity within the transactive energy network. Each possesses unique assets that either generate or consume electricity, and these (e.g., renewable energy generator, diesel generator, aggregate utility load, building load, space conditioning, refrigerator, etc.) may further differ in their price flexibility and in their strategies for responding to dynamic electricity prices. Given such diversity, an implementer’s first inclination might be to start from scratch to define all these devices and to engineer their seemingly unique interactions. Given that each implementer’s perspective may be narrow within a transactive energy network, it is unlikely that uniquely engineered systems would interact well. This is where the transactive network template is applicable. The transactive network template is a metamodel that has been developed to guide implementers as they configure their own transactive agent within a network of such agents. The object-oriented design of the transactive network template provides basic code object types that may be used and extended by implementers to represent each of the assets in their circuit region. These objects further facilitate the transactive agent’s necessary computations, which are divided among responsibilities to schedule power usage, balance electric supply and demand, and coordinate the exchange of electricity with the other transactive agents. This report addresses the conceptual transactive network template design. Implementers are directed to more formal design documents and reference implementations. A Python™-based1 reference implementation of the transactive network template has been coded, and three implementations have been configured to represent a national laboratory and two university campuses. Version 2 of the transactive node template generalizes the market class and its methods to facilitate multiple, and more diverse market coordination mechanisms than were facilitated by and demonstrated using Version 1. Version 3 includes new Appendix B, which addresses the designs of methods that would make dynamic prices track approved electricity rates. In the future, the author wishes to make the transactive network template more generally applicable to networks that require more accurate power flow. Development of the transactive network template is jointly funded by the U.S. Department of Energy (DOE) Energy Efficiency and Renewable Energy and the DOE Office of Electricity. In late 2015, one of the first projects to be funded by the DOE Grid Laboratory Modernization Laboratory Consortium was the Clean Energy and Transactive Campus project, led by Pacific Northwest National Laboratory. DOE funds were matched by an investment by the Washington Department of Commerce through its Clean Energy Fund. The transactive network template was developed to guide the implementation of transactive energy networks within this project’s scope.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Controlling the Self-Assembly of DNA Origami Octahedra via Manipulation of Inter-Vertex Interactions

Recent studies have demonstrated novel strategies for the organization of nanomaterials into three-dimensional (3D) ordered arrays with prescribed lattice symmetries using DNA-based self-assembly strategies. In one approach, the nanomaterial is sequestered into DNA origami frames or “material voxels” and then coordinated into ordered arrays based on the voxel geometry and the corresponding directional interactions based on its valency. While the lattice symmetry is defined by the valency of the bonds, a larger-scale morphological development is affected by assembly processes and differences in energies of anisotropic bonds. To facilely model this assembly process, we investigate the self-assembly behavior of hard particles with six interacting vertices via theory and Monte Carlo simulations and exploration of corresponding experimental systems. We demonstrate that assemblies with different 3D crystalline morphologies, but the same lattice symmetry can be formed depending on the relative strength of vertex-to-vertex interactions in orthogonal directions. We observed three distinct assembly morphologies for such systems: cube-like, sheet-like, and cylinder-like. A simple analytical theory inspired by well-established ideas in the areas of protein crystallization, based on calculating the second virial coefficient of patchy hard spheres, captures the simulation results and thus represents a straightforward means of modeling this self-assembly process. To complement the theory and simulations, experimental studies were performed to investigate the assembly of octahedral DNA origami frames with varying binding energies at their vertices. In conclusion, x-ray scattering confirms the robustness of the formed nanoscale lattices for different binding energies, while both optical and electron microscopy imaging validated the theoretical predictions on the dependence of the distinct morphologies of assembled state on the interaction strengths in the three orthogonal directions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Highly Nonstoichiometric YAG Ceramics with Modified Luminescence Properties

Abstract Y 3 Al 5 O 12 (YAG) is a widely used phosphor host. Its optical properties are controlled by chemical substitution at its YO 8 or AlO 6 /AlO 4 sublattices, with emission wavelengths defined by rare‐earth and transition‐metal dopants that have been explored extensively. Nonstoichiometric compositions Y 3+x Al 5‐x O 12 ( x ≠ 0) may offer a route to new emission wavelengths by distributing dopants over two or more sublattices simultaneously, producing new local coordination environments for the activator ions. However, YAG typically behaves as a line phase, and such compositions are therefore challenging to synthesize. Here, a series of highly nonstoichiometric Y 3+x Al 5‐x O 12 with 0 ≤ x ≤ 0.40 is reported, corresponding to ≤20% of the AlO 6 sublattice substituted by Y 3+ , synthesized by advanced melt‐quenching techniques. This impacts the up‐conversion luminescence of Yb 3+ /Er 3+ ‐doped systems, whose yellow‐green emission differs from the red‐orange emission of their stoichiometric counterparts. In contrast, the YAG:Ce 3+ system has a different structural response to nonstoichiometry and its down‐conversion emission is only weakly affected. Analogous highly nonstoichiometric systems should be obtainable for a range of garnet materials, demonstrated here by the synthesis of Gd 3.2 Al 4.8 O 12 and Gd 3.2 Ga 4.8 O 12 . This opens pathways to property tuning by control of host stoichiometry, and the prospect of improved performance or new applications for garnet‐type materials.

Chemistry↗

In-plane and through-plane dielectric properties of graphene oxide membrane: Effect of Al 3 + modification

A graphene oxide (GO) membrane can be used in structural dielectric capacitors and planar micro-supercapacitors as a dielectric separator material due to its excellent through-plane and in-plane dielectric properties. The ability to tailor the dielectric properties of the GO membrane is crucial for dielectric applications. We believe this to be the first demonstration describing how Al 3+ ions impact the dielectric properties of the GO membrane through cation to oxygenated functional groups interactions. In this work, the Al 3+ -modification to the GO membrane was realized through a facile pre-coordination method followed by layer-by-layer assembling. The influence of Al 3+ on the GO membranes’ through-plane and in-plane dielectric properties (dielectric constant and dielectric loss) was investigated in the frequency range from 0.01 Hz to 10 5 Hz. Plane-to-plane and edge-to-edge Al 3+ coordination with the functional group on the basal plane or edge of the GO sheets was proposed to understand the metal ion's impact on the dielectric properties. The results demonstrated that the Al 3+ modification was an effective strategy to tailoring the GO membranes’ dielectric properties in a low frequency regime and further suggested the possibility of designing dielectric GO membranes with controllable dielectric performance. At a low frequency range (0.01–1 Hz), the addition of Al 3+ increased the through-plane dielectric constant and decreased the in-plane dielectric constant. In terms of dielectric loss, unmodified GO membranes exhibited a higher in-plane dielectric loss than the through-plane dielectric loss. Al 3+ -modified GO membranes exhibited increased through-plane dielectric loss and decreased in-plane dielectric loss compared to the unmodified GO membranes.

36 MATERIALS SCIENCE↗