Skip to content
#protein folding Open access

A Vertically Stacked Thin-Layer Cascade Photobioreactor for Space-Efficient Indoor Microalgae Cultivation: Design, Geometric Characterization, and Operational Baseline Across Scales

Oct 2026 · Bioengineering · 44 references
Algal biology and biofuel production

Abstract

Indoor microalgae production under artificial illumination is constrained by facility footprint and energy demand, making biomass output per area the central design objective. Single-layer thin-layer cascade (TLC) systems are geometrically limited to a surface-to-footprint ratio (SF) of at most 1.0 m2 m−2. This study presents a stacked thin-layer cascade (STLC) photobioreactor validated at two scales sharing the same six-channel architecture: a laboratory-scale unit (2 L) and a pilot-scale unit (250 L). Both units achieved an SF well above the single-layer ceiling (3.65 and 4.2 m2 m−2), demonstrating that vertical stacking is an inherent structural solution to the geometric limitation of open thin-layer cascade systems, independent of scale. Both units operated reliably for 11 to 13 days across a 125-fold difference in working volume, converging to comparable transitional Reynolds numbers and confirming that the film hydrodynamics central to the STLC concept remain consistent by design across scale. Footprint-normalized productivity reached 3.41 g DW m−2 d−1 at laboratory scale and 6.11 g DW m−2 d−1 at pilot scale, with pilot-scale protein reaching 42.1% DW prior to nitrogen depletion. Growth kinetics differed between scales, reflecting light/dark cycling regime, initial biomass density, and retention tank geometry as distinct, tunable operational variables. Closing the residual productivity gap requires jointly increasing photon flux density and standing biomass density, since low-density operation causes a large fraction of incident light to pass through the culture unabsorbed regardless of irradiance.

View source

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

Google DeepMind Blog Sep 30, 2026

Introducing SynthID Bio

Proof of concept for watermarking AI-generated proteins while preserving biological function.

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.