EEE 3394 Electronic Materials is the course that supplies the physics underneath everything else in an electrical engineering degree. Circuits courses take it on faith that a resistor resists, a capacitor stores charge and a semiconductor can be made to conduct on command. This course explains why — in terms of atomic structure, bonding, band theory and quantum mechanics — and it is the reason a graduate can reason about a new material rather than only about the devices already made from familiar ones.
The Statewide Course Numbering System titles it Electronic Materials and describes it as a course that “provides electrical engineering students with a background in material science and quantum physics as these apply to electrical/electronic material properties.” The statewide prerequisites are CHM 2045 and PHY 2049 — general chemistry and the second semester of calculus-based physics.
Two Florida institutions carry it, both at 3 credits and both under a nearly identical title: Florida International University and the University of South Florida each call it Electrical Engineering Science I — Electronic Materials. The agreement between them is close, and this guide can be reasonably definite about the content.
⚠ The “I” in the institutional title signals a sequence. Both institutions position this as the first of a series of engineering science courses, with device physics and semiconductor devices following. That framing matters: this course is deliberately foundational and somewhat abstract, and its payoff arrives in the courses that follow it rather than within the term.
⚠ A warning about what kind of course this is. Despite the EEE prefix and the electrical engineering department, this is a physics and materials-science course. Students expecting circuit analysis are routinely surprised. The difficulty is not algebraic manipulation of circuits — it is quantum mechanics, crystal structure and statistical distributions, taught quickly and applied immediately.
The most useful thing to know before registering is what the course actually demands. The mathematics is not the obstacle — there is little beyond calculus and some differential equations. The obstacle is that the reasoning is physical rather than procedural: you are asked to explain why a material behaves as it does, and there is no formula that answers that question.
Students who succeed in circuits courses by becoming fluent at solving a class of problems often struggle here, because the problems do not fall into classes. Conversely, students who found circuits mechanical frequently enjoy this course. Expect the first three weeks — quantum mechanics and band theory — to feel like a different subject from the rest of the degree, because they are.
The statewide requirements are CHM 2045 (general chemistry) and PHY 2049 (calculus-based physics II, covering electricity and magnetism). Both are substantive rather than nominal: bonding and crystal structure build directly on the chemistry, and the treatment of fields, polarisation and magnetism assumes the physics.
⚠ Chemistry is the requirement most often deferred and most often a problem. Electrical engineering students sometimes postpone CHM 2045 as the least obviously relevant requirement in the degree, and then find it gating this course. If you intend to take EEE 3394 — and at FIU and USF it sits early in the electrical engineering sequence — clear chemistry in the first two years.
The other unnamed requirement is comfort with exponentials and logarithms. Carrier concentration, the Fermi function and scattering rates are all exponential in temperature or energy, and students who are not fluent with exponential reasoning find the quantitative work harder than it should be.
EEE 3394 is the first of an engineering science sequence at both institutions and sits early in the upper-division electrical engineering curriculum. It is the foundation for semiconductor device courses — at FIU, EEE 3396 Introduction to Solid State Devices, and onward to EEE 4314 and EEE 4421C Introduction to Nanofabrication; at USF, EEE 4351C Semiconductor Devices and EEE 4314C Integrated Circuit Technology. Everything in the microelectronics and photonics electives assumes it.
Only FIU and USF carry EEE 3394. Other Florida institutions cover comparable material differently — sometimes inside a semiconductor devices course (EEE 3396 at UF and UWF, EEE 3350 at UCF), sometimes in a materials science department under an EMA prefix, and sometimes in physics. This is a case where the same subject is genuinely distributed across prefixes, and a transfer student should expect to argue equivalence from a syllabus rather than a number.
SCNS equivalency does not cross course numbers, and it does not cross prefixes. A student transferring in with an EMA-prefixed materials course, or a physics solid-state course, may well have covered the content — but a receiving programme naming its prerequisite as EEE 3394 will not match it automatically. Raise the substitution with an advisor in the term you transfer.
This course is generally regarded as conceptually demanding rather than laborious. Plan on eight to ten hours a week outside class. The most effective preparation is to work the derivations rather than memorise the results — the Fermi function, the density of states and the intrinsic carrier concentration are each short derivations, and a student who can reproduce them has the course, while a student who has memorised the final expressions has very little.
SCNS records EEE 3394 as guaranteed to transfer to an institution offering the same course. With only two Florida institutions carrying the number, the guarantee has limited reach, though both carry it at 3 credits and describe it almost identically. The course is upper-division and carries no general-education or Gordon Rule designation.
The NCEES Fundamentals of Engineering (Electrical and Computer) exam includes semiconductor materials and devices within its Electronics topic area, covering band gaps, doping, carrier concentration and conduction mechanisms. This course covers that material more deeply than the exam requires, which makes it comfortable preparation rather than a burden — but the FE tests application rather than derivation, so a focused review of the numerical relationships is still worthwhile.
This course sits in a field where machine learning has become a genuine research method, which makes the discussion substantive rather than merely cautionary.
Where AI is genuinely used in the discipline. Materials discovery is one of the clearest success stories for machine learning in the physical sciences: models trained on databases such as the Materials Project now screen candidate compounds for band gap, stability and dielectric properties far faster than experiment or first-principles calculation alone. Machine-learned interatomic potentials have made molecular dynamics practical at scales that were previously out of reach. A student going on to research in this area will encounter these methods immediately, and it is worth knowing they exist.
Where a general-purpose assistant helps in coursework. Explaining band formation or the physical meaning of the Fermi level in different words than the textbook; walking through a carrier-concentration calculation step by step; generating plotting scripts for the Fermi–Dirac distribution or a band diagram; and summarising the properties of an unfamiliar material as a starting point for checking.
⚠ Where it fails, and why the failure coincides with the course’s subject. The characteristic error of an AI tool asked a materials question is to state a property value with confidence and without conditions — a band gap, a mobility, a permittivity — when the whole content of this course is that those values are conditional. Band gap depends on temperature. Mobility depends on doping concentration, temperature and which scattering mechanism dominates. Permittivity depends on frequency. A number without its conditions is precisely the misunderstanding the course exists to remove, and it is what a confident generated answer supplies.
A second failure is more specific: models frequently conflate the Fermi level with the highest occupied state, which is true only at absolute zero, and reason from that error to wrong conclusions about doped semiconductors at room temperature. This is a known conceptual trap for students too, which makes a generated answer that repeats it especially convincing and especially unhelpful.
The engineer’s responsibility. A material property quoted in a design is a claim about behaviour under stated conditions, and the engineer signs for the conditions as much as the number. The habit worth forming here is to ask, of every property value: at what temperature, at what frequency, at what doping, and measured how? A datasheet or a reference database answers those questions; a generated number usually does not.
Academic integrity. FIU and USF each maintain academic integrity policies covering AI-generated work, and practice varies by instructor. Derivations and conceptual explanations are normally expected to be your own even where computational and plotting assistance is permitted. Ask before you rely on a tool, and disclose its use where the syllabus requires it.
Generated September 9, 2026 · Updated September 9, 2026