Read this first. Not because it is graded — it is not — but because almost nothing else in the lab makes sense until you have it.
This is the surface. Every section ends with the course that goes deep, and those courses are where you actually learn this material. What follows is the map, not the territory.
Societies thrive or struggle on the infrastructure they build, and that infrastructure is never only physical. It spans three inseparable layers:
This is the single most useful idea in the lab, and it is a claim, not a taxonomy. The claim is that a study which addresses only one layer gets the answer wrong. A battery recovery process that works at the bench and has no reverse-logistics network is not a solution. A capacity expansion model that ignores who is permitted to build is not a forecast. A tracking system nobody is required to use produces no data.
When your work stalls, it is very often because it has quietly become single-layer.
Everything the lab does sits somewhere in this grid.
| Physical systems, hardware, experiments |
Digital models, analytics, decision tools |
Institutional policy, programs, deployment |
|
|---|---|---|---|
| Energy systems | shipboard power and HESM · NAVSEA land-based testing · microgrids from repurposed EV batteries and solar | ReEDS and GCAM · data-centre and AI load growth · transmission expansion under renewable buildout · surrogate optimisation and DACE | Green Warriors weatherization in South Dallas · energy burden and DERs · Powerhouse Texas EPAC · cited in IPCC AR6 WGIII |
| Critical minerals | 500+ kWh of recovered EV batteries and motors · shred, grind, sieve · electrical, chemical and powder analysis · 3R-BET | global lithium supply chain optimisation · centralized vs. decentralized black mass · reverse logistics and recycling network design | trade and tariff policy · domestic supply chain security · NAATBatt Track and Trace · geothermal on tribal lands and HUBZones |
| RFID and asset tracking | antennas, readers, printers · real-time location systems · circular conveyor and robotic arm · operational hospital beds | plant-level inventory systems · asset performance analytics · set-cover optimisation for reader placement · blockchain provenance | battery track-and-trace standards · community naloxone distribution · pharmaceutical anti-diversion · health asset management |
Find the cell your project sits in. Then find the two cells in your row that it does not address, and be able to say why that is acceptable.
The system that keeps the lights on, and the system this lab models most.
The short version. Electricity cannot be stored at scale cheaply, so supply must match demand continuously, second by second. Everything difficult about power systems follows from that one constraint. Generation has to be dispatched, transmission has to carry it, and somebody has to decide who pays for the capacity that sits idle most of the year waiting for the peak.
What makes Texas unusual, and why the lab is here: ERCOT covers most of Texas and is not synchronously connected to the rest of the country, which means Texas largely regulates its own grid. It is an energy-only market — generators are paid for energy produced, not for capacity held in reserve — which is a live and contested design choice, not a technical fact. Texas is first in the country in electricity production, and first in both wind and utility solar.
Where the lab works. Dense, islanded, high-power loads — shipboard plants through to data centres. Macro energy-system modelling with ReEDS and GCAM-USA. And the institutional layer through weatherization, energy burden, and state policy.
Goes deep: REE 4301 Energy Systems Modeling, with its open-access textbook. Take it.
End to end and back. This phrase is the lab’s central intellectual claim and it is worth understanding precisely.
The chain runs mine → processing → manufacturing → deployment → monitoring → remanufacturing and reuse → recycling — and then back to materials, closing the loop. Most research cuts the chain somewhere and studies a segment. The claim here is that the segments are coupled tightly enough that studying one in isolation produces answers that do not survive contact with the others.
What makes a mineral “critical.” Not rarity. A mineral is critical when it is economically essential and its supply is vulnerable to disruption — which makes criticality a political and economic judgement, published in lists that governments revise. Lithium, cobalt, nickel, graphite and the rare earths are the usual battery-relevant names.
The bottleneck the lab works on physically is end-of-life recovery: black mass production and hydrometallurgical recovery of metals from retired lithium-ion batteries. The lab has scaled from a junkyard Nissan Leaf pack to nineteen retired Workhorse EV batteries.
Goes deep: IE 6301 Critical Mineral Supply Chain Modeling.
What cannot be tracked cannot be managed, or improved.
The short version. RFID tags carry an identifier that a reader can interrogate without line of sight. That single property — no line of sight — is what separates it from a barcode and is the reason it works for pallets, hospital beds, and battery packs moving through a facility.
What to understand before you design anything with it. Passive tags have no battery and are powered by the reader’s field, so read range is bounded by physics rather than by engineering effort. Metal and liquid detune and absorb. Read rates in a real facility are not the read rates on a spec sheet, and the gap between them is where most deployments fail. Reader placement is a coverage problem, which is why it shows up here as set-cover optimisation.
Why it belongs next to the other two. A traceable battery is what makes a circular supply chain auditable rather than aspirational — which is why battery track-and-trace standards are an active institutional fight, and why the lab sits on the NAATBatt committee for it.
Goes deep: ask about current projects; this area is taught through the work rather than a single course.
Order-of-magnitude anchors for energy work. Not for precision — for catching a result that is wrong by a factor of a thousand, which is the failure that survives code review.
| 1 Quad | 1015 BTU |
| 1 kWh | 3,412 BTU |
| One US house | ~104 kWh/year |
| Homes per Quad | ~108 |
| Car travel | ~3,500 BTU per vehicle-mile |
This is the same habit as sanity checks in M1 — predict the magnitude before you run, then check the units.
The supply chains here cross a dozen jurisdictions with different rules, different data conventions, and genuinely different ideas about what a deadline means. The lab collaborates internationally and most of its students trained somewhere other than the United States.
This is learned by paying attention rather than by reading, which is exactly why it is not a graded skill. But it is not optional, and assuming your own conventions are the default is a reliable way to lose six weeks.
| Course | Covers |
|---|---|
| REE 4301 Energy Systems Modeling | dispatch, capacity expansion, LP and MILP formulations of the grid — with an open-access textbook |
| IE 6301 Critical Mineral Supply Chain Modeling | the supply chain as an optimisation problem, end to end |
| IE 5301 Advanced Operations Research | the optimisation methods everything above is built on |
| IE 3315 Operations Research I | if you have never formulated an LP |
If a section above raised a question this page does not answer, that is the page working correctly. Go to the course, or ask.
See also Engineering Research Domain Knowledge — the questions that sit behind the methods rather than inside them. Read that one later, when this page has stopped feeling new.