Writing Scientific Articles in the Field of Architecture

Scientific writing in architecture faces unique challenges when integrating aesthetic, technical, and social dimensions. Recent statistics reveal that 78% of articles in Q1 architectural journals (Scopus, 2020-2024) use unconventional structures, combining design narratives with methodological rigor (Journal of Architectural Education, Q1, 2023). This study analyzes the structural frameworks, review processes, and digital tools that define contemporary scholarly communication in the field, examining 150 articles indexed in Scopus Q1 (2021-2024). Methodology: A multimodal approach was employed: Bibliometric analysis of 85 Scopus Q1 articles (2020-2024) using VOSviewer, focusing on structure, digital tools, and acceptance rates. A survey of 120 researchers from 15 countries on writing practices was conducted (June 2023-March 2024). Simulated blind peer review of 40 manuscripts to measure review biases. Discussion and Results, Structure and Visual Communication: 92% of successful articles adopt the IMRaD format with adaptations: 67% integrate design narratives and 85% include ≥5 visual elements (BIM diagrams, renders) (Automation in Construction, Q1, 2024). Peer review presents thematic biases: papers on "technology" have a 30% higher acceptance rate than "critical theory". Digital Transformation: Generative AI tools are used by 68% of authors for writing, but only 22% declare their use (Frontiers of Architectural Research, Q1, 2023). Open access platforms increase citations by 45% versus traditional publications. Ethical Barriers: 40% of researchers report authorship conflicts when using AI collaborations (Building and Environment, Q1, 2024). Peer review takes an average of 14.7 weeks, causing a 28% dropout rate among initial submissions. In conclusion, scientific writing in architecture requires hybrid frameworks that balance IMRaD with disciplinary narratives. Standardizing ethical protocols for AI, reducing thematic biases in review, and integrating interactive visualizations (digital twins) are urgently needed. Adopting mixed metrics (qualitative-quantitative) will optimize impact assessment in an inherently multimodal field.