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At least 811 records · Page 45

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DOE OSTI2023

Defect engineering of porous aromatic frameworks via end capping improves dioxane removal from water

Amorphous porous organic polymers show promise for energy-efficient adsorptive separations, but it is difficult to understand or improve their performance through intentional structural modification. Herein, we report the synthesis of porous aromatic frameworks (PAFs) with pore structures tailored by the incorporation of a monofunctionalized end-capping monomer that disrupts framework topology. Combining experimental characterization with molecular simulations, we show that this defect engineering strategy yields less densely crosslinked networks, which leads to pore collapse and the presence of unique adsorption sites. These defect-engineered PAFs exhibit enhanced removal of 1,4-dioxane, an important environmental pollutant, from water. Increasing the concentration of end-capping monomers produces PAFs with narrower pore size distributions and improved 1,4-dioxane uptake. These results illustrate that defect engineering can effectively modulate polymer connectivity and porosity for applications in selective adsorptive separations. In conclusion, this technique avoids post-synthetic treatments and presents another approach to tailor amorphous polymeric adsorbents.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Numerical simulations of membrane distillation systems with actively heated membranes

Membrane distillation (MD) is a thermal desalination process that is gaining attention for treating hypersaline brines. One recent approach uses composite membranes with a thermally conductive layer that delivers heat to the membrane–feed interface, where it drives evaporation. Though this increases single-pass recovery, it comes with the challenge of promoting lateral heat conduction through the thin membrane. Herein, we develop a 3D, computational fluid dynamics (CFD) model that simulates conjugate heat, mass, and momentum transport in the feed channel and composite membrane. We then use the CFD to verify a simpler numerical model that approximates the feed velocity field analytically. We validate the numerical model experimentally, and use it to investigate the impacts of the conductive layer thickness, feed channel geometry, and operating conditions on temperature and concentration polarization, permeate production, and specific energy consumption. Overall, we find that lateral heating increases permeate production at the expense of increased concentration polarization. In extreme cases, the concentration increases more than four-fold along the membrane surface. Furthermore, we show however, that the feed flow rate and conductive layer thickness can be tailored to mitigate concentration polarization, for only a small reduction in permeate production.

42 ENGINEERING↗

DOE OSTI2022

Modeling of linear nanopores in a-SiO 2 tuning pore surface structure

Here, new strategies are presented for the generation of models for linear nanopores in amorphous silica (a-SiO 2 ) with surface structure tuned to match experimental observations. Specifically, the models successfully target not only the overall density of surface silanol groups, but also the proportion of geminal versus mono silanols for which additional experimental NMR data is reported. The latter quantity has not been appropriately described in previous modeling, and in fact has typically not been considered. Strategies include “pore drilling” of bulk a-SiO 2 , and “cylindrical resist” methodology forming a-SiO 2 around a cylindrical exclusion region, followed by dehydroxylation and hydroxylation processes, respectively. However, these latter processes must be judiciously tailored in order to tune the proportion of geminals, in addition to the overall silanol density, to achieve experimental values. Such tailoring has not been incorporated into previous modeling. Another approach considered tunes surface structure of pores obtained by “pore drilling” through mild annealing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

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↗

DOE OSTI2024

Support size regulated ruthenium-sulfoacid-nitrogen sites intensify cellulose hydrogenolysis to 1,2-propylene glycol

Rational design of metal-acid-base multifunctional catalysts for upgrading cellulose to 1,2-propylene glycol (1,2-PG) is of great significance for building a sustainable world. However, it is time-consuming and tedious to regulate metal-acid-base sites to balance major reactions to render a high 1,2-PG yield. We herein report support size simultaneously regulated ruthenium-sulfoacid-nitrogen (Ru–SO 3 H–N) sites for cellulose hydrogenolysis to high yield 1,2-PG. Originated from the depolymerization and reassembly of zinc-1,3,5-benzenetricarboxylic acid (ZnBTC) fiber with zeolitic imidazolate framework (ZIF-8) in water, 2-methylimidazole infiltrated nanorod (ZnBTC(mIM)) with a varied aspect ratio was fabricated by varying the feed ratio of ZIF-8/ZnBTC. Upon being pyrolyzed, sulfonated and impregnated with Ru ions, the supported sites were tailored in terms of Ru single-atom/nanocluster ratio, SO 3 H acidity and N basicity. Further, the elaborately fabricated catalyst delivers 32.3% yield of 1,2-PG, corresponding to a high productivity of 67.71 mol h -1 g Ru -1 and a large turnover number of 34193, two and three orders of magnitude higher than those by using other Ru-containing catalytic systems for cellulose hydrogenolysis. The excellent performance can be attributed to optimized electronic and molecular structure of Ru–SO 3 H–N sites that can improve rate-determining cellulose hydrolysis/fructose hydrogenolysis, pivotal glucose isomerization with others to proceed at a matched rate. This study opens a new avenue to facilely tailor the metal-acid-base sites by rational design of size controlled supporting matrix.

1,2-Propylene glycol↗

DOE OSTI2024

Techno-economic analysis of renewable energy generation at the South Pole

Transitioning from fossil-fuel power generation to renewable energy generation and energy storage in remote locations has the potential to reduce both carbon emissions and cost. Here, this study presents a techno-economic analysis for implementation of a hybrid renewable energy system at the South Pole in Antarctica, which currently hosts several high-energy physics experiments with nontrivial power needs. A tailored model of resource availability and economics for solar photovoltaics, wind turbine generators, lithium-ion energy storage, and long-duration energy storage at this site is explored in different combinations with and without existing diesel energy generation. The Renewable Energy Integration and Optimization (REopt) platform is used to determine the optimal system component sizing and the associated system economics and environmental benefit. We find that the least-cost system includes all three energy generation sources and lithium-ion energy storage. For an example steady-state load of 170 kW, this hybrid system includes 180 kW-DC of photovoltaic panels, 570 kW of wind turbines, and a 3.4 MWh lithium-ion battery energy storage system. This system reduces diesel consumption by 95% compared to an all -diesel configuration, resulting in approximately 1200 metric tons of carbon footprint avoided annually. Over the course of a 15-year analysis period the reduced diesel usage leads to a net savings of 57 million United States dollars, with a time to payback of approximately two years. All the scenarios modeled show that the transition to renewables is highly cost effective under the unique economics and constraints of this extremely remote site.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Sustainable Seaweed Biotechnology Solutions for Carbon Capture, Composition, and Deconstruction

Seaweeds or macroalgae are attractive candidates for carbon capture, while also supplying a sustainable photosynthetic bioenergy feedstock, thanks to their cultivation potential in offshore marine farms. Seaweed cultivation requires minimal external nutrient requirements and allows for year-round production of biomass. Despite this potential, there remain significant challenges associated with realizing large-scale, sustainable agronomics, as well as in the development of an efficient biomass deconstruction and conversion platform to fuels and products. Recent biotechnology progress in the identification of enzymatic deconstruction pathways, tailored to complex polymers in seaweeds, opens up opportunities for more complete utilization of seaweed biomass components. Effective, scalable, and economically viable conversion processes tailored to seaweed are discussed and gaps are identified for yield and efficiency improvements.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Gaining Perspective on Unconventional Well Design Choices through Play-level Application of Machine Learning Modeling

The recent development of unconventional oil and gas (O&G) reservoirs has led to an abundant hydrocarbon supply, both domestically and globally. However, there is a continued push to develop new and innovative approaches to improve exploration and extraction efficiencies and overall well productivity moving forward. Substantial improvements in unconventional O&G development are expected through optimized well completion and stimulation strategies aimed at maximizing well productivity. Optimizing well designs will require tailoring to the distinctive geologic conditions present for any newly placed well. To better evaluate the impact of well design attributes and their associated interactions on productivity in a major unconventional play, multivariate machine learning-based models that use empirical datasets were developed. A gradient boosted regression tree (GBRT) algorithm was applied. GBRT has been narrowly investigated for O&G applications but enables straightforward parametric importance and influence evaluation, as well as assessment of parameter interaction effects. Models were trained on well design and locational parameters that serve as a proxy for variable geologic conditions to estimate two types of productivity indicator response variables strongly correlated to estimated ultimate recovery (EUR). The dataset utilized consists of over 7,000 well observations that cover the majority of the productive region of the Marcellus Shale. Model performance was evaluated and algorithm parameters tuned by analyzing the goodness-of-fit for simulated results against observed data in a cross-validation approach. Models were found capable of 73–79 percent prediction accuracy on held out testing data of gas equivalent production and can be used to inform future well design and placement decisions for increasing EUR per well and improving overall field-level recovery. Study results indicate that Marcellus well performance improves most with upscaling perforated interval lengths and water and proppant volumes per foot; but relative productivity improvements are spatially dependent across the play. Finally, optimal combinations of water and proppant on well performance were found to vary depending on well location, emphasizing the utility of data-driven models capable of broad application across a play of interest for informing tailored well design approaches prior to their field deployment.

04 OIL SHALES AND TAR SANDS↗

DOE OSTI2020

Efficient Control of Atom Arrangement in Ternary Metal Chalcogenide Nanoparticles Using Precursor Oxidation State

Controlling both the concentration and the distribution of elements in a given material is often crucial to extracting and optimizing synergistic properties of the various constituents. An interesting class of such multielement materials is metal chalcogenide nanoparticles, which exhibit a wide range of composition-dependent optoelectronic properties including both bandgap-mediated processes and localized surface plasmon resonance properties, each of which is useful in applications ranging from energy conversion to sensing. Because metal chalcogenide nanoparticles can support several different metal elements in a variety of chalcogen lattices, this material class has particularly benefited from the ability to control both atom concentration and atom arrangement to tailor final particle properties. The primary method to access complex, multimetallic chalcogenide particles is via a postsynthetic cation exchange strategy. One-pot syntheses have been less explored to access these complex particles, although this route is desirable for economy and scalability. In this work, we compare the composition and morphology outcomes from cation exchange and one-pot preparation approaches using a Cu/Ag/Se system, which is already known to exhibit both binary and ternary metal chalcogenide phases. We show that at similar concentrations of the two metal cations, initial reaction conditions for the one-pot method yield multicomponent nanoparticles, whereas cation exchange yields homogeneous ternary metal chalcogenide structures. We then show that by tuning the precursor oxidation state for the one-pot method, this approach can be used to access homogeneous ternary metal chalcogenide particles that are similar in atom arrangement to the particles obtained using cation exchange. Taken together, our results demonstrate reliable synthetic methods that yield a variety of controlled compositions and composition morphologies in the Cu/Ag/Se system. Importantly, we demonstrate that this entire collection of architectures can all be accessed via a one-pot method simply by modifying metal precursor chemistry. The mechanistic insights gained and the resulting streamlined syntheses outlined indicate pathways to easily scaled, highly tailorable syntheses for rapid translation into downstream technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Clifford Circuit-Based Heuristic Optimization of Fermion-To-Qubit Mappings

Simulation of interacting Fermionic Hamiltonians is one of the most promising applications of quantum computers. However, the feasibility of analyzing Fermionic systems with a quantum computer hinges on the efficiency of Fermion-to-qubit mappings that encode nonlocal Fermionic degrees of freedom in local qubit degrees of freedom. While recent studies have highlighted the importance of designing Fermion-to-qubit mappings that are tailored to specific problem Hamiltonians, the methods proposed so far either are restricted to a narrow class of mappings or they use computationally expensive and unscalable brute-force search algorithms. Here, in this work, we address this challenge by designing a heuristic numerical optimization framework for Fermion-to-qubit mappings. To this end, we first translate the Fermion-to-qubit mapping problem to a Clifford circuit optimization problem and then use simulated annealing to optimize the average Pauli weight of the problem Hamiltonian. For all Fermionic Hamiltonians we have considered, the numerically optimized mappings outperform their conventional counterparts, including ternary-tree-based mappings that are known to be optimal for single creation and annihilation operators. We find that our optimized mappings yield between 15% and 40% improvements on the average Pauli weight when the simulation Hamiltonian has an intermediate level of complexity. Most remarkably, the optimized mappings improve the average Pauli weight for 6 × 6 nearest-neighbor hopping and Hubbard models by more than 40% and 20%, respectively. Surprisingly, we also find specific interaction Hamiltonians for which the optimized mapping outperforms any ternary-tree-based mapping. Our results establish heuristic numerical optimization as an effective method for obtaining mappings tailored for specific Fermionic Hamiltonian.

Hamiltonians↗

DOE OSTI2021

Controlling the Schottky Barrier at the Pt/TiO 2 Interface by Intercalation of a Self-Assembled Monolayer with Oriented Dipole Moments

Interfacial Schottky barriers can impact the catalytic function of Pt on TiO 2 . Since the electronic structure is characteristic of each material, it may be advantageous to tailor the interfacial Schottky barrier by the addition of adsorbed layers. Here, we show that the Schottky barrier in Pt/TiO 2 can be mitigated by the insertion of self-assembled monolayers (SAM) of carboranethiols that possess an oriented dipole moment. A Pt substrate with the SAM on which TiO 2 nanoparticles are deposited is used to that effect. Kelvin Probe Force Microscopy shows thatm-9-carboranethiolate SAM with perpendicular dipole moments decreases the potential difference between TiO 2 and Pt by ~0.3 eV due to the interfacial electric field of the SAM. Furthermore, our findings open new opportunities for tailoring interfacial electronic structures not only in the metal-semiconductor junction, but also the semiconductor heterojunctions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Toward Lithium Recovery Using Modular (and Membraneless) Phase Separation and Extraction (MPSE) Technology with Ionic Liquid (IL) Solvents: Effect of Coatings

In this work, a single-channel slope-plate Modular and Membrane-less Phase Separation and Extraction (MPSE) device was fabricated using 3D printing. The slope-plate was designed with an insertable glass slide to enable surface modification with coatings. Self-assembled monolayers (SAMs) and perfluoropolyether (Zdol) coatings were applied to tailor surface wettability and enhance phase separation. Using a model biphasic system of water and hexadecane, both coatings significantly improved the separation efficiency compared to the uncoated device by promoting selective wetting. Building on these results, lithium extraction from a simulated saline solution was investigated using 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][NTf₂]) as the ionic liquid (IL) extractant. The IL effectively extracted Li⁺ from the aqueous phase in bulk extraction, demonstrating its potential for lithium recovery. However, the low interfacial tension between the IL and aqueous phases posed challenges for phase separation. The application of SAM and Zdol coatings effectively mitigated this issue. Overall, integrating tailored surface chemistry with the slope-plate MPSE design shows great promise as an efficient and scalable platform for studying liquid–liquid separation and optimizing ionic liquid–based extraction processes for lithium recovery from saline sources.

3D printing↗

DOE OSTI2022

Designing Stress-Adaptive Dense Suspensions Using Dynamic Covalent Chemistry

The non-Newtonian behaviors of dense suspensions are central to their use in technological and industrial applications and arise from a network of particle–particle contacts that dynamically adapt to imposed shear. Reported herein are studies aimed at exploring how dynamic covalent chemistry between particles and the polymeric solvent can be used to tailor such stress-adaptive contact networks, leading to their unusual rheological behaviors. Specifically, a room temperature dynamic thia-Michael bond is employed to rationally tune the equilibrium constant (K eq ) of the polymeric solvent to the particle interface. It is demonstrated that low Keq leads to shear thinning, while high K eq produces antithixotropy, a rare phenomenon where the viscosity increases with shearing time. It is proposed that an increase in K eq increases the polymer graft density at the particle surface and that antithixotropy primarily arises from partial debonding of the polymeric graft/solvent from the particle surface and the formation of polymer bridges between particles. Thus, the implementation of dynamic covalent chemistry provides a new molecular handle with which to tailor the macroscopic rheology of suspensions by introducing programmable time dependence. These studies open the door to energy-absorbing materials that not only sense mechanical inputs and adjust their dissipation as a function of time or shear rate but also can switch between these two modalities on demand.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Quaternized Polynorbornene Random Copolymers for Fuel Cell Devices

Quaternized polymers are critical components for various energy devices. Vinyl-addition polynorbornenes provide high mechanical strength, high ion conductivity, and chemical stability in a wide range of pH environments due to the all-C–C bond backbone. In this paper, we present the synthesis of a series of quaternized polynorbornene random copolymers via vinyl addition polymerization and elucidate the impact of polymer composition on their properties. The quaternary ammonium alkyl tether length and the ratio of n-hexylnorbornene to unsubstituted norbornene are systemically tailored. A copolymer of 5-(3-bromopropyl)-2-norbornene and norbornene with pendant trimethylammonium groups achieved hydroxide conductivity of 109 mS/cm at 80 °C with a modest water uptake of 72%. The addition of n-hexylnorbornene to the copolymer, to make a terpolymer, allows for the polymer composition to be tailored for properties, including a decrease in water uptake and higher processability, despite a slightly decreased hydroxide conductivity. Moreover, the developed membranes are chemically robust and highly mechanically stable, enabling thin membranes to be easily fabricated. This study provides insight into important design parameters for quaternized polynorbornenes for a variety of energy storage and conversion devices, especially fuel cells.

25 ENERGY STORAGE↗

DOE OSTI2021

Insights into Spontaneous Solid Electrolyte Interphase Formation at Magnesium Metal Anode Surface from Ab Initio Molecular Dynamics Simulations

Spontaneous chemical reactivity at multivalent (Mg, Ca, Zn, Al) electrode surfaces is critical to solid electrolyte interphase (SEI) formation, and hence, directly affects the longevity of batteries. Here, we report an investigation of the reactivity of 0.5 M Mg(TFSI)2 in 1,2-dimethoxyethane (DME) solvent at a Mg(0001) surface using ab initio molecular dynamics (AIMD) simulations and detailed Bader charge analysis. Based on the simulations, the initial degradation reactions of the electrolyte strongly depend on the structure of the Mg(TFSI)2 species near the anode surface. At the surface, the dissociation of Mg(TFSI)2 species occurs via cleavage of the N-S bond for the solvent separated ion pair (SSIP) and via cleavage of the C-S bond for the contact ion pair (CIP) configuration. In the case of the CIP, both TFSI anions undergo spontaneous bond dissociation reactions to form atomic O, C, S, F, and N species adsorbed on the surface of the Mg anode. These products indicate that the initial SEI layer formed on the surface of the pristine Mg anode consists of a complex mixture of multiple components such as oxides, carbides, sulfides, fluorides, and nitrides. We believe that the atomic level insights gained from these simulations will lay the groundwork for the rational design of tailored and functional interphases that are critical for the success of multivalent battery technology.

Agarwal, Garvit↗

DOE OSTI2022

Programmable Photoluminescence via Intrinsic and DNA-Fluorophore Association in a Mixed Cluster Heterometallic MOF

In this report a rapid and facile design strategy to create a highly complex optical tag with programmable, multimodal photoluminescent properties is described. This was achieved via intrinsic and DNA-fluorophore hidden signatures. As a first covert feature of the tag, an intricate novel heterometallic near-infrared (NIR)-emitting mesoporous metal–organic framework (MOF) was designed and synthesized. The material is constructed from two chemically distinct, homometallic hexanuclear clusters based on Nd and Yb. Uniquely, the Nd-based cluster is observed here for the first time in a MOF and consists of two staggered Nd μ3-oxo trimers. To generate controlled, multimodal, and tailorable emission with difficult to counterfeit features, the NIR-emissive MOF was post-synthetically modified via a fluorescent DNA oligo labeling design strategy. The surface attachment of several distinct fluorophores, including the simultaneous attachment of up to three distinct fluorescently labeled oligos was achieved, with excitation and emission properties across the visible spectrum (480-800 nm). The DNA inclusion as a secondary covert element in the tag was demonstrated via the detection of SYBR Gold dye association. Importantly, the approach implemented here serves as a rapid and tailorable way to encrypt distinct information in a facile and modular fashion and provides an innovative technology in the quest toward complex optical tags.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Tunable Solid Acid Catalyst Thin Films Prepared by Atomic Layer Deposition

Solid acid catalysts, including zeolites and amorphous silica-aluminas (ASAs), are industrially important materials widely used in the fuel and petrochemical industries. The versatility of zeolites is due to the Brønsted acidity of the bridging hydroxyl and shape selectivity that can be tailored during and after synthesis. This is in contrast to amorphous silica-alumina, where tailoring acidity is a major challenge as the Brønsted acid structure in ASA is still debated. In both cases, however, the pore size and acidity cannot be tuned independently, and this is particularly limiting in the application of biomass conversion, where zeolite pores are too small for the molecules of interest. Herein, we present a method using atomic layer deposition (ALD) to prepare thin films of solid acid materials where the ratio of Brønsted to Lewis acid sites can be tuned precisely. This capability, combined with the sub-nm pore size control afforded by ALD yields a powerful and flexible method for synthesizing solid acid catalysts inside virtually any mesoporous host. We demonstrate the utility of these materials in two acid-catalyzed reactions relevant to biomass conversion: (1) Meerwein–Ponndorf–Verley–Oppenauer (MPVO) reaction and dehydration of fructose and (2) cascade reaction of glucose to 5-hydroxymethylfurfural. Finally, we propose a plausible structure for the Brønsted acid sites in our materials based on infrared spectroscopy and solid-state nuclear magnetic resonance measurements and density functional theory calculations and argue that this same structure might apply to conventional ASAs as well.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Multicaloric Cryocooling Using Heavy Rare-Earth Free La(Fe,Si) 13 -Based Compounds

The transition toward a carbon-neutral society based on renewable energies goes hand in hand with the availability of energy-efficient technologies. Here, magnetocaloric cooling is a very promising refrigeration technology to fulfill this role regarding cryogenic gas liquefaction. However, the current reliance on highly resource critical, heavy rare-earth-based compounds as magnetocaloric material makes global usage unsustainable. Here, we aim to mitigate this limitation through the utilization of a multicaloric cooling concept, which uses the external stimuli of isotropic pressure and magnetic field to tailor and induce magnetostructural phase transitions associated with large caloric effects. In this study, La 0.7 Ce 0.3 Fe 11.6 Si 1.4 is used as a nontoxic, low-cost, low-criticality multiferroic material to explore the potential, challenges, and peculiarities of multicaloric cryocooling, achieving maximum isothermal entropy changes up to −28 J (kg K) −1 in the temperature range from 190 K down to 30 K. Thus, the multicaloric cooling approach offers an additional degree of freedom to tailor the phase transition properties and may lead to energy-efficient and environmentally friendly gas liquefaction based on designed-for-purpose, noncritical multiferroic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗