--- name: applied-energy description: Use when targeting Applied Energy or deciding whether a systems-level energy manuscript fits this venue. Encodes the journal's fit, the systems-scope-and-quantified-impact bar, modeling and assessment rigor, house style, the systems-vs-single-device routing, official-submission re-check, and desk-reject heuristics. --- # Applied Energy (applied-energy) ## Journal positioning Applied Energy (Elsevier) is a **systems-level** energy research venue: energy conversion and integration, energy-systems modeling and optimization, decarbonization pathways, demand and efficiency, and techno-economic and environmental assessment. Its center of gravity is the **system, not the device** — how technologies, sectors, and markets combine to deliver, store, or save energy, and what the quantified energetic, economic, and environmental consequences are. The single most common misfit is a single-material or single-component study (for example, one electrode or one catalyst) submitted as if it were systems research; such work belongs at a materials or device venue. A paper succeeds when its contribution is a generalizable systems-level insight backed by transparent, validated analysis. This skill is a **fit / venue-selection / re-framing** tool. It does not replace the journal's current official author guidelines. Before submitting, re-check the live Applied Energy Guide for Authors on the Elsevier site. ## When to trigger - The author names Applied Energy for an energy-systems modeling, integration, decarbonization, efficiency, or techno-economic/environmental-assessment manuscript. - A paper must be re-framed from a device/component result into a systems-level question with quantified energy/economic/environmental impact — or re-routed if it is in fact device-level. - The author is deciding between Applied Energy's systems scope and a device venue (`journal-of-power-sources`) or a materials venue (`energy-storage-materials`). - The author needs the journal's systems-scope and assessment rigor bar and desk-reject heuristics. ## Scope & topic fit - Energy-systems modeling and optimization: power, heat, transport, and multi-vector systems; dispatch, planning, and integration of variable renewables and storage. - Energy conversion and integration at the system/process level, including hybrid and sector-coupled configurations and waste-heat/energy recovery. - Decarbonization pathways and scenario analysis: emissions, cost, and feasibility of transitions across technologies, sectors, or regions. - Demand-side, efficiency, buildings, and flexibility: demand response, load modeling, and end-use efficiency with system-level consequences. - Techno-economic analysis (TEA) and life-cycle/environmental assessment (LCA) of energy technologies and systems, with transparent assumptions. - Data-driven and machine-learning methods for energy systems when the contribution is a generalizable systems insight, not a black-box fit to one dataset. ## Method & evidence bar - The central claim is a **systems-level insight**: a result about how a system performs, integrates, or decarbonizes, with quantified energy, economic, and/or environmental outcomes — not a component performance number. - Models must be transparent and validated/benchmarked where possible; assumptions, boundaries (system boundary, time horizon, spatial scope), and data sources stated. - Techno-economic and environmental results require disclosed cost/emission factors, functional units, and uncertainty/sensitivity analysis; point estimates without sensitivity are weak. - Generalizability and scenario robustness must be shown: results should hold or be characterized across cases, not depend on one favorable assumption set. - Comparisons must use a fair baseline/counterfactual; reproducibility requires that data, parameters, and (where applicable) code be sufficiently described. ## Structure & house style - Standard research-article structure (introduction, methods/model, results, discussion); the journal uses highlights and a graphical abstract — re-check current article types and requirements on the live guide. - The introduction frames the energy-systems gap and the decision/insight at stake, not a component novelty; methods state the system boundary, scope, and assumptions explicitly. - Figures are load-bearing: system diagrams, scenario/optimization results, cost and emission breakdowns, and sensitivity/uncertainty plots. - Supporting information carries full model formulations, parameter tables, and data; main-text figures must support the systems claim on their own. ## Official-submission checklist - Before giving submission-ready advice, read `../../resources/source-basis.md` and `../../resources/official-source-map.md`; start from the Elsevier anchors, then cite the current Applied Energy Guide for Authors page you checked. - Search the live site for "Applied Energy guide for authors" and follow the current Elsevier/Editorial Manager version. - Re-check article types, highlights and graphical-abstract requirements, and length/figure expectations. - Confirm data/code-availability expectations and assumption/parameter-reporting norms for TEA/LCA and modeling work. - Re-check competing-interests, funding, author-contribution (CRediT), and AI-use disclosure requirements. - If the live official instructions conflict with this skill, the official instructions win. ## Pre-submission self-check - [ ] The contribution is a systems-level insight with quantified energy/economic/environmental impact, not a single-device result. - [ ] System boundary, time horizon, spatial scope, and key assumptions are stated explicitly. - [ ] Models are transparent and validated/benchmarked; data sources are disclosed. - [ ] TEA/LCA results include functional units, cost/emission factors, and uncertainty/sensitivity analysis. - [ ] Results are shown to be robust across scenarios against a fair baseline/counterfactual. - [ ] Highlights and graphical abstract represent the systems-level advance. ## Common desk-reject triggers - Single-material/single-device study (one electrode, one catalyst) framed as systems research. - TEA/LCA with undisclosed assumptions, no functional unit, or no uncertainty/sensitivity analysis. - Optimization/modeling tuned to one case with no generalizable systems insight. - Black-box machine-learning fit to one dataset with no transferable energy-systems finding. - Results that depend on a single favorable assumption set with no robustness check. - Component-performance paper with system relevance asserted only in the abstract. ## Re-routing decision - Device-level electrochemical power (cells, fuel cells, supercapacitors) → `journal-of-power-sources`. - Electrode/electrolyte materials and mechanism → `energy-storage-materials`. - Applied catalysis/separation process at the unit level → `chemical-engineering-journal`. - Authoritative energy/combustion review synthesis → `progress-in-energy-and-combustion-science`. - Highest-profile cross-cutting energy advance → `nature-energy`, `joule`, or `energy-and-environmental-science` (different selectivity/format; re-check). ## Output format ```text [Fit] High / Medium / Low (one-line reason) [Target] Applied Energy [Topic tags] <2–3 closest energy-systems subtopics> [Systems insight] [Scope/boundary] [Rigor] [Top risk] [Official items to re-check]
[Re-route suggestion] ```