Energy

Long-term
low-energy data storage

How can we reduce the energy required for long-term data archiving while maximizing information density? This project explores nature-inspired strategies for more efficient data encoding and compression, addressing sustainable archiving challenges.

Energy

Type of client

Data storage providers, high tech digital companies, defense and security.

OBJECTIveS

Design a system capable of storing maximum volumes of data while minimizing space and energy consumption, with sufficient stability for preservation over decades.

CONSTRAINTS

Stability over time
Energy consumption of the storage unit
Read/write speed compatible with usage
Cost of the system
Compatibility with existing digital systems
High data density

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Let's collaborate
with nature ?

ASK A DEMO

Problem analysis

Why are today’s storage solutions reaching their limits?

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Current archive storage systems present key limitations on density and energy consumption. The key issues include:

Thermal management constraints and high energy cooling system
High power consumption for storage media
Physical limitation of storage media

AI agents help conduct root-cause analysis to better understand these systemic inefficiencies.

Biological insights

How does nature encode information efficiently?

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To overcome limits in density and energy consumption, the analysis of living systems provides remarkable insights :

Sparse neural networks: connect only what’s essential
Hibernation mechanisms: drastically reduce energy in inactive phases
Molecular-scale encoding: achieve ultra-high density at nanoscale

These biological mechanisms guide users towards new systems based on molecular data-storage, encoding sobriety and segmentation of functionnal phases.

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Asteria then helps you generate ideas of concrete bioinspired concepts leveraging both the various selected biological mechanisms and the modeling of the project's context.

Genome packaging in giant viruses

Extreme compaction of large data volumes

Protective encapsulation

Rapid integration and reading mechanism

Sequential memory in hippocampal CA3 region

Ordered reactivation of information

Temporary storage and transfer to long-term memory

Data consolidation during inactivity

Energy preservation in the feathertail glider

Enters torpor during inactivity

Major metabolic reduction

Rapid, autonomous reactivation if needed

DNA-inspired storage systems

Data chemical encoding via elementary block sequences

High-density data storage through multiple scale compaction

Enzymatic writing and reading

Aerolysin nanopore encoding

Digital encoding through molecules passing through pores

Data read via electrical signal variation

Ultra-high molecular data density

OUTPUT

Bioinspired concepts
generated by Asteria

High-density molecular storage via bio-inspired nanopores

description

A system based on aerolysin nanopores where data is encoded using electrical signals triggered by molecule passage. Offers exceptional density in a compact format.

biological model

Aerolysin nanopores used for selective molecule transport

design principal

Molecular-level data storage via nanopore signal reading

Invente a new tech

Materials

Chip with nanopores, coding molecules, miniaturized reading electrodes

Manufacturing process

Chip nanopore fabrication and integration with signal readers

Existing technology

Research work at EPFL

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Data hibernation based on animal torpor

description

Inspired by the torpor state of the pygmy glider, this storage system puts inactive data into a low-energy mode. Data access triggers gradual reactivation, reducing environmental impact.

biological model

Energy-saving torpor state of the Australian pygmy glider

design principal

Energy reduction via torpor, based on data activity

Invente a new tech

Materials

Digital storage systems with dynamic power modes

Manufacturing process

Hardware/software integration of energy-saving protocols in data centers

Existing technology

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Bio-inspired synthetic DNA data storage

description

Ultra-dense storage system inspired by DNA, using synthetic polymers and microfluidic chips for encoding. Compact, stable, and energy-efficient, it’s ideal for long-term archival in minimal space.

biological model

DNA, a compact helical structure encoding genetic information via four bases

design principal

High-density coding, polymer self-assembly, enzymatic data processing

Invente a new tech

Materials

Synthetic polymers (PNA, LNA), PDMS or glass microfluidic chips, modified enzymes

Manufacturing process

Polymer synthesis, microfluidic deposition, sequencing via nanopores or fluorescence

Existing technology

Biomemory

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Wyss Institute DNA Storage

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Sparse neural data storage

description

A data storage system inspired by the sparse network structure of the hippocampal burst region. It activates only necessary connections, lowering energy consumption and extending device lifespan.

biological model

Sparse neural network in hippocampal burst

design principal

Sparse representation with activity-based modulation

Invente a new tech

Materials

Semiconductor components for dynamic memory cells

Manufacturing process

SSD fabrication with on-demand dynamic connections

Existing technology

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