APM is a prospective production technology based on guiding the motion of reactive molecules to build progressively larger components and systems. Bottom-up atomic precision can enable production with unprecedented scope (in terms of product materials, components, systems, and performance), while fundamental mechanical scaling laws can enable unprecedented productivity.
Predictive computational modeling of stiff structures
For suitably selected non-biological chemical and mechanical systems, each of these fundamental operations can be analyzed quantitatively.
In doing so, it’s convenient to explore systems built of components that consist of strong, stiff, covalent structures because these are easier to model than biomolecular systems. There are two key features of stiff covalent structures that facilitate modeling: First, these structures are insensitive to small errors in the potential-energy functions that underlie simulations of molecular dynamics; and second, severe conformational restrictions (a consequence of ubiquitous polycyclic structures) avoid the familiar challenge of evaluating the delicately balanced free energies that determine (for example) how proteins fold and interact with ligands in aqueous environments. Computational chemists will immediately see that these characteristics can greatly increase the predictive power and reduce the computational cost of simulations.
Lengthy yet accessible development paths lead from today’s extensive, million-atom scale capabilities for atomically precise fabrication to APM-level technologies of the kind outlined above; incremental development paths are outlined in the post From Self-Assembly to Mechanosynthesis and discussed in more depth in Appendix II of Radical Abundance.
2. Overcoming Bias looks at Eric Drexler explaining the difference between science and engineering.
The essence of science is inquiry; the essence of engineering is design. Scientific inquiry expands the scope of human perception and understanding; engineering design expands the scope of human plans and results. …
• Scientists seek unique, correct theories, and if several theories seem plausible, all but one must be wrong, while engineers seek options for working designs, and if several options will work, success is assured.
• Scientists seek theories that apply across the widest possible range (the Standard Model applies to everything), while engineers seek concepts well-suited to particular domains (liquid-cooled nozzles for engines in liquid-fueled rockets).
• Scientists seek theories that make precise, hence brittle predictions (like Newton’s), while engineers seek designs that provide a robust margin of safety.
• In science a single failed prediction can disprove a theory, no matter how many previous tests it has passed, while in engineering one successful design can validate a concept, no matter how many previous versions have failed.
When faced with imprecise knowledge, a scientist will be inclined to improve it, yet an engineer will routinely accept it. Might predictions be wrong by as much as 10 percent, and for poorly understood reasons? The reasons may pose a difficult scientific puzzle, yet an engineer might see no problem at all. Add a 50 percent margin of safety, and move on.
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