Samuel O. Ajayi, Tarekegn H. Dolla, Ludwe L. Sikeyi et al. · Materials Today Sustainability · 2024
To review conductive MOF design principles, lithium-ion, lithium-sulfur and lithium-oxygen battery applications, ML/AI-enabled discovery, and industrial perspectives for c-MOF electrodes.
The review’s argument is preserved as a navigable set of section summaries.
Surveys c-MOF use as LIB anodes/cathodes, Li-S cathode hosts, and Li-O2 cathodes, with Table 1 summarising selected secondary performance benchmarks.
Relevance: Core · 8-17 · 4. Application of conductive MOFs as electrodes in lithium-based batteries · Table 1
Compares scalable MOF synthesis approaches and highlights continuous flow, microwave, electrochemical, sonochemical and mechanochemical routes as scale-up concepts.
Relevance: Supporting · 21 · 6. Industrial perspectives of MOFs in lithium batteries · Table 2
Frames lithium-based batteries as high-energy storage systems needing improved electrodes, then positions c-MOFs as a response to the insulating behaviour of conventional MOFs.
Relevance: Core · 1-2 · 1. Introduction
Provides background on LIB, Li-S and Li-O2 operating principles, architectures, advantages and failure modes to contextualise c-MOF electrode roles.
Relevance: Supporting · 5-8 · 3. Fundamentals of lithium batteries · Fig. 3; Fig. 4; Fig. 5
Argues that ML/AI can accelerate c-MOF discovery by predicting conductivity, band gaps, linker effects, synthesis conditions, and battery state or performance.
Relevance: Supporting · 18-20 · 5. Machine learning and artificial intelligence · Fig. 13; Fig. 14
Summarises the review's explicit gaps: ligand cost, scarce Li-S/Li-air c-MOF studies, conductivity standardisation, stability dependence, and cycling-mechanism uncertainty.
Relevance: Core · 24 · 7. Summary and outlook
Explains how metal ions and organic linkers control conductivity, and distinguishes measurement, proton/electron conduction, through-bond/through-space, band and hopping mechanisms.
Relevance: Core · 2-4 · 2. Overview of conductive MOFs · Fig. 1; Fig. 2
Classification systems are attributed to this review and are not treated as a global material registry.
c-MOFs are separated by whether proton motion or electron transport is the dominant conduction function; electron c-MOFs are emphasised for battery electrodes.
Categories: proton c-MOFs · electron c-MOFs
3 · 2.2. Principle and design of conductive MOFs
Electron conduction is organised into chemical routes through covalent metal-ligand overlap or non-covalent pi stacking, and physical descriptions based on delocalised bands or hopping.
Categories: through bond · through space · band theory · hopping theory
3-4 · 2.2. Principle and design of conductive MOFs · Fig. 1
Li-O2 systems are classified by electrolyte design, with different safety, rechargeability and interfacial-resistance implications.
Categories: aprotic · aqueous · hybrid · solid state
7 · 3.3. Li-O2 batteries · Fig. 5
The review classifies linkers by how functional groups and pi systems influence band gaps, electron delocalisation, and metal-ligand charge transfer.
Categories: rigid bidentate/polydentate · aromatic carbonyl · heteroatom-functionalized · pi-conjugated
2 · 2.1. Chemistry of metal ions and organic ligands/linkers
The article structures application evidence around LIBs, LSBs, and LABs, each with distinct c-MOF electrode functions and failure modes.
Categories: Li-ion batteries · Li-S batteries · Li-O2 batteries
5-8 · 3. Fundamentals of lithium batteries
The review distinguishes solvent- or guest-carried proton transport from hydrogen-bond-network proton hopping, while noting pH sensitivity as a practical limitation.
Categories: vehicle mechanism · Grotthuss mechanism
3 · 2.2. Principle and design of conductive MOFs
The review compares batch and continuous methods by energy use, reaction time, product control, limitations and industrial application.
Categories: solvothermal/hydrothermal · sonochemical · microwave-assisted · electrochemical · mechanochemical · continuous flow
21 · 6.1. Industrially scalable synthesis methods · Table 2
Review-defined families retain their representative materials and conduction descriptions.
Sulfur-rich conductive MOFs using benzenehexathiol-type linkers and metal-sulfur kagome or related networks.
Conduction: Pi-d conjugation and sulfur redox activity provide high electronic conductivity and multi-electron storage.
Representative materials: Cu-BHT · rGO/Cu-BHT
Nodes / linkers: Cu · benzenehexathiol · benzenehexathiolate
10 · 4.1. Li-ion batteries · Fig. 8
Conductive MOFs combining two organic linkers to balance coordination, add active sites, and tune conductivity.
Conduction: Dual ligands are presented as a way to improve d-pi conjugation, electrical conductivity and Li-storage performance.
Representative materials: Cu3(HHTP)(THQ) · dual-ligand porous coordination polymer chemiresistor
Nodes / linkers: Cu · HHTP · THQ
9 · 4.1. Li-ion batteries · Fig. 6
Conductive MOF cathodes designed to catalyse oxygen reduction/evolution and manage Li2O2 formation or decomposition.
Conduction: Electronic conductivity, spin-state tuning and bimetallic sites are linked to oxygen redox kinetics and lower overpotential.
Representative materials: Cu-THQ · Ni-NCF · NiRu-HTP · NiCu-BTA
Nodes / linkers: Cu · Ni · Ru · tetrahydroxyquinone · hexaiminotriphenylene · benzenetetramine
15-17 · 4.3. Li-O2 batteries · Fig. 11; Fig. 12; Table 1
c-MOFs comprising central metal ions and catecholate or HHTP-type ligands, including nanorods and nanowires.
Conduction: Catecholate coordination and conjugation are linked to rapid Li diffusion and electronic conductivity.
Representative materials: Ni-CAT NRs · Cu-CAT NWs · Ni-HHTP
Nodes / linkers: Ni · Cu · 2,3,6,7,10,11-hexahydroxytriphenylene · catecholate
9 · 4.1. Li-ion batteries
Layered conductive MOFs built from pi-conjugated ligands and square-planar metal nodes, commonly containing MX4 units.
Conduction: Pi-conjugation and metal-ligand orbital overlap support electronic conductivity and Li-ion storage kinetics.
Representative materials: Ni3(HITP)2 · Cu3(HITP)2 · Cu3(HHTP)2 · 2D Ni-MOF NFs
Nodes / linkers: Ni · Cu · Co · Zn · hexaiminotriphenylene · hexahydroxytriphenylene
9 · 4.1. Li-ion batteries
c-MOFs incorporating quinone, tetrahydroxyquinone, dihydroxybenzoquinone or related redox-active linkers.
Conduction: Redox-active carbonyl linkers and metal nodes support electron migration, hopping behaviour and charge-storage capacity.
Representative materials: Fe-THQ · Cu-THQ · (NBu4)2Fe2(DHBQ)3 · Fe2(DHBQ)3
Nodes / linkers: Fe · Cu · tetrahydroxyquinone · dihydroxybenzoquinone · benzoquinoid
11-12 · 4.1. Li-ion batteries · Fig. 8
Conductive 2D MOF coatings or matrices used to confine silicon nanoparticles and buffer volume expansion.
Conduction: MOF pores and conductive channels are interpreted as improving electrical contact, Li-ion transport and strain accommodation.
Representative materials: Si@Cu3(HITP)2 · Si/Ni3(HITP)2
Nodes / linkers: Cu · Ni · hexaiminotriphenylene
9 · 4.1. Li-ion batteries · Fig. 7
MOFs using TTF-based linkers to create close-range pi-stacked or S-S through-space transport pathways.
Conduction: Non-covalent stacking and close S-S interactions are used to increase orbital overlap and charge mobility.
Representative materials: Zn2(TTFTB) · Cd2(TTFTB)
Nodes / linkers: Zn · Cd · tetrathiafulvalene tetrabenzoate
4 · 2.2. Principle and design of conductive MOFs
Review-level synthesis principles remain separate from primary-study recipes.
Couple conductive MOFs with silicon, CNTs, rGO or related materials to improve conductivity, suppress aggregation, adsorb intermediates, or buffer volume change.
Claimed effects: Improves electrical contact, ion diffusion, volume-change tolerance or Li-polysulfide control.
Controlling variables: composite ratio · MOF coating amount · particle confinement · conductive additive
Representative materials: Si@Cu3(HITP)2 · Si/Ni3(HITP)2 · rGO/Cu-BHT · S@Ni3(HITP)2
Caveat: Primary optimisation of compositions must be checked in original studies; the review provides secondary comparison only.
9-13 · 4.1; 4.2 · Fig. 7; Fig. 9
Combine two ligands in one conductive framework to tune coordination competition, conductivity and lithium-storage reactions.
Claimed effects: Provides a route to overcome constraints of single-ligand 2D c-MOF electrodes.
Controlling variables: ligand ratio · coordination balance · redox-active site distribution · framework order
Representative materials: Cu3(HHTP)(THQ)
Caveat: The strategy is represented by a small number of recent exemplars rather than a broad mature class.
9 · 4.1. Li-ion batteries · Fig. 6
Apply microwave, sonochemical, electrochemical, mechanochemical, solvothermal/hydrothermal or continuous-flow methods for larger-scale MOF production.
Claimed effects: Can improve production rate, product control or environmental profile relative to conventional batch methods.
Controlling variables: reaction time · solvent consumption · energy efficiency · space-time yield · product morphology
Representative materials: HKUST-1 · UiO-66 · NOTT-400 · MIL-53(Al) · ZIF-8
Caveat: Scale-up discussion mostly concerns MOF production generally, not necessarily battery-qualified c-MOF electrodes.
21-24 · 6. Industrial perspectives · Table 2; Fig. 18
Use transition metals and highly conjugated organic linkers to build frameworks with better orbital overlap, carrier concentration and charge transport.
Claimed effects: Improves electronic conductivity compared with conventional insulating MOFs and supports lithium storage.
Controlling variables: metal ion identity and valence · linker conjugation · metal-ligand coordination geometry · band gap
Representative materials: Ni3(HITP)2 · Cu3(HHTP)2 · Cu-BHT
Caveat: The review treats this as a design principle but also notes that conductivity thresholds are not standardised for battery use.
2 · Introduction; 2.1
Use ML models to predict band gaps, conductivity, linker effects, synthesis routes, state of health, or battery performance before costly experiments.
Claimed effects: Reduces computational and experimental search burden and prioritises candidates for DFT or synthesis.
Controlling variables: training dataset · material descriptors · target property · model architecture · validation strategy
Representative materials: CoRE-MOF candidate set · metallic MOFs from multi-model voting · low-band-gap MOFs
Caveat: The review notes ML for c-MOF discovery remains developing, with training-set breadth, band-gap reference accuracy and uncertainty estimates still needing improvement.
18-20 · 5.1; 5.2 · Fig. 13; Fig. 14
Embed quinone, HATN, TQ or related redox-active moieties into conductive frameworks to increase active-site exposure and charge-storage capacity.
Claimed effects: Enhances lithium storage capacity, cycling stability and mass transfer by combining conductivity with redox activity.
Controlling variables: redox-active linker identity · metal node · pore/channel order · active-site density
Representative materials: Cu-HATN · Cu-HHTQ · Cu-THQ
Caveat: Organic redox compounds can suffer low conductivity and dissolution unless immobilised in conductive frameworks.
9 · 4.1. Li-ion batteries · Fig. 7
Select metal-ligand pairs with energetic and spatial orbital overlap so covalent paths enable charge transfer.
Claimed effects: Creates chemical electron-transfer pathways and can raise conductivity when metal centres provide high-energy carriers.
Controlling variables: metal redox state · metal-ligand orbital overlap · unpaired electron availability · coordination structure
Representative materials: Cu[Cu(pdt)2] · Cu[Ni(pdt)2] · Ni-CAT-1
Caveat: Changing the metal centre can reduce conductivity sharply; the review uses Cu/Ni dithiolene substitution as the cautionary example.
3 · 2.2. Principle and design of conductive MOFs · Fig. 1
Use pi-pi stacking, close S-S interactions or redox-active guest molecules to create non-covalent charge-transfer paths.
Claimed effects: Adds pathways for electron movement in porous frameworks without requiring continuous covalent connectivity.
Controlling variables: pi-stacking distance · guest identity · redox activity · pore geometry
Representative materials: Zn2(TTFTB) · TTF-based MOFs
Caveat: The review presents through-space transport conceptually and does not provide broad battery-electrode validation for TTF examples.
4 · 2.2. Principle and design of conductive MOFs
These are the review authors’ synthesis, not newly measured results.
The review identifies 2D c-MOFs with pi-conjugated ligands and MX4 redox sites as a major emerging class for LIB electrodes.
Evidence basis: multi_reference
Caveat: Some highlighted materials are recent and may not yet be broadly reproduced.
9 · 4.1 · Fig. 6; Fig. 7
c-MOFs are framed as effective lithium-battery electrodes because redox sites, surface area, porosity and conductivity support reaction sites and fast electron/ion movement.
Evidence basis: multi_reference
Caveat: The claim is secondary synthesis; individual battery metrics require primary-study confirmation.
4-5 · 2.2
Despite progress, the review concludes that c-MOF electrode commercialisation in lithium-based batteries has not yet been realised.
Evidence basis: review_reasoning
Caveat: Statement reflects the review authors' 2024 outlook.
24 · 7. Summary and outlook
Continuous pi-electron ligands and suitable metal nodes are presented as the main chemical route to intrinsically conductive c-MOFs.
Evidence basis: multi_reference
Caveat: Conductivity also depends on morphology, stacking, defects and measurement protocol.
2 · 2.1
Electron-conductive MOFs are described as having higher intrinsic conductivity than proton-conductive MOFs because of higher carrier concentration and orbital stacking.
Evidence basis: multi_reference
Caveat: The statement is qualitative and framed in the review rather than as a universal quantitative rule.
3 · 2.2
Conventional MOF electrodes based on non-conjugated ligands are portrayed as limited by restricted electronic conductivity, sluggish kinetics and weak redox activity.
Evidence basis: multi_reference
Caveat: The review summarises broad trends rather than comparing every conventional MOF class.
9 · 4.1
For Li-O2 batteries, c-MOF conductivity and catalytic metal centres are presented as routes to improve oxygen redox kinetics, overpotential and cycling stability.
Evidence basis: multi_reference
Caveat: The review states Li-O2 c-MOF applications remain early-stage and not commercialised.
15-17 · 4.3 · Fig. 11; Fig. 12
For Li-S batteries, the review argues that ideal hosts must combine polysulfide adsorption, rapid Li-ion diffusion and sufficient electronic conductivity.
Evidence basis: multi_reference
Caveat: The extent of adsorption-catalysis-conductivity coupling varies by material and should be checked in primary papers.
12-13 · 4.2 · Fig. 9
The review distinguishes resistivity/conductivity definitions and two- versus four-probe methods, noting that two-probe measurements include wires and contacts.
Evidence basis: review_reasoning
Caveat: This is a general measurement caveat; the review does not audit each benchmark's measurement geometry.
3 · 2.2
Changing metal centres can strongly alter conductivity because metal d orbitals, valence states and redox potentials affect carrier density and electron transfer.
Evidence basis: single_reference
Caveat: The Cu/Ni dithiolene comparison is a specific exemplar, not a complete metal-selection rule.
3 · 2.2 · Fig. 1
The review specifically proposes ML/AI for conjugated-linker selection and design because linker chemistry affects conductivity, redox properties, ion transport and stability.
Evidence basis: review_reasoning
Caveat: This is a forward-looking design claim rather than a demonstrated lithium-battery c-MOF workflow in the review.
19-20 · 5.1; 5.2
ML is presented as a way to avoid expensive trial-and-error and high-throughput DFT by predicting band gaps, conductivity and promising candidates.
Evidence basis: multi_reference
Caveat: The review describes ML as promising but not fully realised for c-MOF discovery.
18-20 · 5.1; 5.2 · Fig. 14
Conventional MOFs are attractive for batteries because of porosity and designability, but their low conductivity is a central bottleneck for electrode use.
Evidence basis: multi_reference
Caveat: The review uses broad literature ranges; primary measurements should be used for exact values.
2 · Introduction
Particle morphology and pore openness are described as important for lithium-ion storage kinetics in conductive MOFs.
Evidence basis: single_reference
Caveat: The review cites a Cu3(HHTP)2 morphology example; broader morphology rules need original-study support.
11 · 4.1
Industrial use of MOFs requires control of raw-material cost, reproducibility, product quality, environmental compliance, safety and process efficiency.
Evidence basis: review_reasoning
Caveat: The scale-up discussion is MOF-general and only partly specific to conductive battery MOFs.
21 · 6. Industrial perspectives · Table 2
The review states that conductive/non-conductive categorisation is not standardised solely by conductivity values in lithium-battery contexts.
Evidence basis: review_reasoning
Caveat: Useful as a chapter caveat against treating reported conductivity numbers as directly comparable.
24 · 7. Summary and outlook
Every row remains visibly secondary and links to a primary dossier only where the mapping is verified.
| Material | Property | Reported value | Context and quality | Primary evidence | Review source |
|---|---|---|---|---|---|
| Secondary2D Ni-MOF NFs | Electrical conductivity | 2 S cm^-1 | Review text comparison with holey graphite Text · Exact Reported | No verified corpus mapping | 9 · 4.1 · Fig. 6 |
| SecondaryCu-BHT | Reversible capacity | 175 mAh g^-1 | LIB cathode, 300 mA g^-1, 500 cycles Table · Exact Reported | research_0365 | 17 · 4; Table 1 · Table 1 |
| SecondaryCu-BHT | Electrical conductivity | 1580 S cm^-1 | Reported as high electrical conductivity in review Text · Exact Reported | research_0006 | 10 · 4.1 |
| SecondaryCu-HATN | Reversible capacity | 763 mAh g^-1 | LIB anode, 300 mA g^-1, 600 cycles Table · Exact Reported | research_0336 | 17 · 4; Table 1 · Table 1 |
| SecondaryCu3(HHTP)(THQ) | Reversible capacity | 624.8 mAh g^-1 | LIB anode, 300 mA g^-1, 200 cycles Table · Exact Reported | No verified corpus mapping | 17 · 4; Table 1 · Table 1 |
| SecondaryCu-THQ | Capacity range | 1000-2000 mAh g^-1 | LAB cathode, 100-200 mA g^-1, 100-300 cycles Table · Range | research_0820 | 17 · 4; Table 1 · Table 1 |
| SecondaryCu[Cu(pdt)2] | Electrical conductivity | 6 x 10^-4 S/cm | 300 K Text · Exact Reported | research_0201 | 3 · 2.2 |
| SecondaryCu[Ni(pdt)2] | Electrical conductivity | 1 x 10^-8 S/cm | Room temperature Text · Exact Reported | research_0203 | 3 · 2.2 |
| SecondaryFe-THQ | Electrical conductivity | 3.3 +/- 0.55 mS cm^-1 | 300 K Text · Exact Reported | research_0066 | 4 · 2.2 |
| SecondaryMOF structures from CoRE-MOFs database | ML screening set and metallic hits | 2937 MOFs screened; 6 intrinsic metallic variations identified | ML with multi-voting and ab initio calculations Text · Exact Reported | research_0682 | 18 · 5.1 · Fig. 14 |
| SecondaryConventional MOFs | Typical electrical conductivity | 10^-8 to 10^-10 S/cm, or insulating behavior below 10^-10 S/cm | General MOF conductivity range reported in review introduction Text · Range | No verified corpus mapping | 2 · Introduction |
| SecondaryNi-HHTP | Reversible capacity | 910 mAh g^-1 | LSB cathode, 0.2 C, 200 cycles Table · Exact Reported | research_0021 | 17 · 4; Table 1 · Table 1 |
| SecondaryNi3(HITP)2 | Retained capacity | 848.9 mAh g^-1 | LSB cathode, 0.2 C, 100 cycles Table · Exact Reported | No verified corpus mapping | 17 · 4; Table 1 · Table 1 |
| SecondaryNi-NCF | Capacity | 16800 mAh g^-1 | LAB cathode, 500 mA g^-1, 200 cycles Table · Exact Reported | No verified corpus mapping | 17 · 4; Table 1 · Table 1 |
| SecondaryNiCu-BTA | Capacity | 23,000 mAh g^-1 | LAB cathode, 100 mA g^-1, 113 cycles Table · Exact Reported | No verified corpus mapping | 17 · 4; Table 1 · Table 1 |
| SecondaryNiRu-HTP | Capacity | 15080 mAh g^-1 | LAB cathode, 500 mA g^-1, 200 cycles Table · Exact Reported | research_0613 | 17 · 4; Table 1 · Table 1 |
| SecondarySi@Cu3(HITP)2 | Reversible capacity | 1039 mAh g^-1 | LIB anode, 1C, 1000 cycles Table · Exact Reported | research_0777 | 17 · 4; Table 1 · Table 1 |
| SecondarySi/Ni3(HITP)2 | Reversible capacity | 876 mAh g^-1 | LIB anode, 1C, 1000 cycles Table · Exact Reported | No verified corpus mapping | 17 · 4; Table 1 · Table 1 |
Open questions are presented as review-author priorities, not conclusions from the primary database.
Conductive versus non-conductive MOF classification is not standardised by conductivity values for lithium-based battery applications.
Proposed direction: Standardise conductivity values and reporting protocols for c-MOF industrial scalability in lithium batteries.
24 · 7. Summary and outlook
The mechanisms of c-MOF electrodes during lithium-battery cycling, electrolyte interactions and structural changes remain insufficiently resolved.
Proposed direction: Investigate electrolyte interactions and structural/electrochemical evolution of c-MOF electrodes during cycling.
24 · 7. Summary and outlook
Efficient ion transport is described as crucial for fast charging and optimal performance, but remains inadequately understood for c-MOF LIB electrodes.
Proposed direction: Combine theoretical and experimental methods to elucidate Li-ion storage and transport mechanisms.
12 · 4.1
High costs of sophisticated ligand synthesis restrict c-MOF use in electrochemical devices to laboratory scale.
Proposed direction: Develop cost-effective, scalable and efficient routes to high-quality organic ligands.
24 · 7. Summary and outlook
Li-O2 c-MOF applications are described as early-stage and not commercialised because of high production costs and ligand-design difficulty.
Proposed direction: Reduce c-MOF production cost and simplify organic ligand design for practical Li-O2 cathodes.
17 · 4.3
Few studies have examined c-MOF electrodes in Li-S and Li-air batteries compared with the potential application space.
Proposed direction: Investigate suitability and efficacy of c-MOFs in Li-S and Li-air battery electrode roles.
24 · 7. Summary and outlook
ML has promise for c-MOF discovery, but broader training sets, more precise reference band gaps and better prediction-uncertainty methods are needed.
Proposed direction: Expand datasets, improve reference calculations and develop uncertainty-aware screening tools.
20 · 5.2
c-MOF stability depends on particle size, crystallinity, linker, metal ion, synthesis route, acid/base conditions, pressure and temperature.
Proposed direction: Systematically connect structural attributes and operating environments to electrochemical cycling stability.
24 · 7. Summary and outlook
Mappings show which printed review references have a verified counterpart in the frozen primary corpus.
| Reference | Study | Role and context | Corpus mapping |
|---|---|---|---|
| Ref. 172023 | Conductive metal-organic frameworks for rechargeable lithium batteries | prior_review · battery_contextCited as one of the notable earlier reviews on c-MOF electrode materials for lithium-based batteries. | Unmapped |
| Ref. 182020 | Conductive metal-organic frameworks: mechanisms, design strategies and recent advances | transport_review · conductivity_contextSupports the review's conductivity bottleneck and target-conductivity framing for MOFs. | Unmapped |
| Ref. 202020 | Electrically conductive metal-organic frameworks | transport_review · definition_contextCited for broader conductive-MOF preparation and design context. | Unmapped |
| Ref. 242024 | Synthesis of conductive MOFs and their electrochemical application10.1002/smll.202308264 | synthesis_review · ligand_taxonomySupports the review's classification of ligand types and their influence on c-MOF electronic transport. | Unmapped |
| Ref. 292020 | Valence-dependent electrical conductivity in a 3D tetrahydroxyquinone-based metal-organic framework | transport_benchmark · hopping_transportUsed by the review as a band/hopping transport example and secondary conductivity benchmark. | research_0066 |
| Ref. 422009 | Electroconductive porous coordination polymer Cu [Cu (pdt) 2] composed of donor and acceptor building units | transport_benchmark · through_bondThrough-bond exemplar cited for conductivity and activation energy in a Cu-based dithiolene MOF. | research_0201 |
| Ref. 432010 | Conductivity, doping, and redox chemistry of a microporous dithiolene-based metal-organic framework | transport_benchmark · metal_substitutionUsed for the Cu-to-Ni substitution comparison in dithiolene MOFs and lower conductivity. | research_0203 |
| Ref. 442023 | Synthesis of conductive MOFs and their electrochemical application | figure_source · transport_mechanismsFigure source for the review's four transport mechanism schematics and used for broad c-MOF battery-electrode rationale. | Unmapped |
| Ref. 482015 | A two-dimensional pi-d conjugated coordination polymer with extremely high electrical conductivity and ambipolar transport behaviour | transport_benchmark · conductive_frameworkCited for Cu-BHT's very high conductivity and as background for rGO/Cu-BHT anode enhancement. | research_0006 |
| Ref. 812021 | Graphene analogue metal organic framework with superior capacity and rate capability as an anode for lithium ion batteries | LIB_anode · transport_benchmarkUsed for a 2D Ni-MOF nanofilament conductivity and LIB anode performance discussion. | Unmapped |
| Ref. 852023 | One-step synthesis of dual-ligand 2D conductive metal-organic framework for high-performance lithium storage | LIB_anode · dual_ligandSelected as the dual-ligand 2D c-MOF example for high-performance LIB storage. | Unmapped |
| Ref. 892023 | Stabilizing redox-active hexaazatriphenylene in a 2D conductive metal-organic framework for improved lithium storage performance | LIB_anode · redox_active_ligandSupports the review's redox-active HATN c-MOF performance discussion and Table 1 benchmark. | research_0336 |
| Ref. 912021 | Si nanoparticles confined within a conductive 2D porous Cu-based metal-organic framework (Cu3 (HITP) 2) as potential anodes for high-capacity Li-ion batteries | LIB_anode · composite_benchmarkSelected composite benchmark where a conductive MOF confines silicon nanoparticles. | research_0777 |
| Ref. 952019 | A highly conductive MOF of graphene analogue Ni3 (HITP) 2 as a sulfur host for high-performance lithium-sulfur batteries | LSB_cathode · polysulfide_hostSupports the first experimental Ni3(HITP)2 sulfur-host example and Table 1 LSB benchmark. | Unmapped |
| Ref. 962020 | Coupling of a conductive Ni 3 (2, 3, 6, 7, 10, 11-hexaiminotriphenylene) 2 metal-organic framework with silicon nanoparticles for use in high-capacity lithium-ion batteries | LIB_anode · composite_benchmarkSelected for the Ni3(HITP)2/silicon composite capacity benchmark and conductivity/volume expansion discussion. | Unmapped |
| Ref. 1002019 | Conductive metal-organic framework with redox metal center as cathode for high rate performance lithium ion battery | LIB_cathode · redox_metal_centerUsed for Cu3(HHTP)2 cathode performance and the Cu2+/Cu+ redox-centre discussion. | research_0273 |
| Ref. 1062020 | A redox-active 2D metal-organic framework for efficient lithium storage with extraordinary high capacity | LIB_cathode · redox_active_ligandSupports the review's discussion of Cu-THQ and redox-active ligands in LIB cathodes. | Unmapped |
| Ref. 1142021 | Conductive metal-organic frameworks promoting polysulfides transformation in lithium-sulfur batteries | LSB_cathode · polysulfide_transformationUsed for Ni-HHTP Li-S cathode performance and conductivity/adsorption comparison with Ni-BTC. | research_0021 |
| Ref. 1192022 | Nanostructured conductive metal organic frameworks for sustainable low charge overpotentials in Li-air batteries | LAB_cathode · overpotentialSupports the review's Cu-THQ Li-air cathode discussion and Table 1 LAB benchmark. | research_0820 |
| Ref. 1202022 | Spin-state manipulation of two-dimensional metal-organic framework with enhanced metal-oxygen covalency for lithium-oxygen batteries | LAB_cathode · spin_stateUsed for the spin-state manipulation mechanism and Ni-NCF Li-O2 performance. | Unmapped |
| Ref. 1212022 | Atomic Ruthenium-Riveted metal-organic framework with tunable d-band modulates oxygen redox for lithium-oxygen batteries | LAB_cathode · bimetallic_catalysisSupports the bimetallic NiRu-HTP oxygen-redox kinetics discussion and Table 1 LAB benchmark. | research_0613 |
| Ref. 1222023 | Rechargeable non-aqueous lithium-O2 batteries: novel bimetallic (Ni-Cu) conductive coordination polymer cathodes | LAB_cathode · bimetallic_catalysisUsed for NiCu-BTA Li-O2 ORR/OER and Table 1 high-capacity benchmark. | Unmapped |
| Ref. 1342021 | Computational techniques for characterisation of electrically conductive MOFs: quantum calculations and machine learning approaches10.1039/d1tc02543k | ML_review · computational_screeningSource for the computational approaches flow chart and ML/DFT discussion for conductive MOFs. | Unmapped |
| Ref. 1522018 | Metallic metal-organic frameworks predicted by the combination of machine learning methods and ab initio calculations10.1021/acs.jpclett.8b01707 | ML_screening · metallic_MOF_predictionCited for ML screening of 2937 MOFs and identification of six intrinsic metallic variants. | research_0682 |
| Ref. 1962014 | Versatile, high quality and scalable continuous flow production of metal-organic frameworks10.1038/srep05443 | scaleup · continuous_flowSupports the review's continuous-flow scale-up discussion and Fig. 18. | Unmapped |
| Ref. 762020 | Highly conductive two-dimensional metal-organic frameworks for resilient lithium storage with superb rate capability | LIB_cathode · conductive_frameworkUsed as the Cu-BHT LIB cathode example in Fig. 8 and Table 1. | research_0365 |