Award-Winning Physical Chemistry Tutors
serving Buffalo, NY

Garrett's biology degree means he already thinks in terms of systems — enzyme kinetics, membrane potentials, metabolic energy flow — which gives him a concrete anchor for the abstract math that makes p-chem so intimidating. He teaches thermodynamic and kinetic concepts by connecting derivations to the biological and chemical phenomena they describe, so something like a Gibbs free energy calculation feels like a tool rather than an exercise in symbol-pushing.

Thermodynamic state functions, quantum mechanical models, and kinetic rate laws all converge in Physical Chemistry, and most students need someone who can bridge the math and the chemistry simultaneously. Abismael's chemical engineering training put him through the full gauntlet — partial differential equations applied to heat transfer, Gibbs free energy calculations for phase equilibria, statistical mechanics. He explains each derivation from multiple angles and tests understanding with problems designed to be harder than what shows up on the exam.

An applied mathematics degree plus active graduate math coursework gives Drisana the calculus fluency that p-chem demands — she's comfortable with the differential equations, multivariable integrals, and linear algebra that show up in everything from quantum mechanical wave functions to statistical thermodynamics. Where many chemistry students struggle because the math outpaces them, she tackles derivations from the opposite direction, building physical meaning onto mathematical structures she already knows cold. Rated 5.0 by students.

I am a public school teacher (Chemistry and Living Environment) but can tutor most sciences. I truly believe in differentiated learning and once I know the learning style of a student, I tailor my teaching style for optimum time usage. I love to utilize stories from my real life experiences in labs to help students understand the implications of their science education.

Computational linguistics might seem far from p-chem, but Justin's SAT-level math chops and his chemistry coursework give him enough quantitative grounding to tackle the foundational concepts — working through state functions, basic thermodynamic relationships, and the algebra behind equilibrium expressions. He's strongest at slowing down the notation-heavy steps that lose students early in a p-chem sequence, making sure each symbol maps to something physically real before moving forward.

A PhD in chemistry means Justin didn't just pass p-chem — he lived in its formalism for years, from quantum mechanical models to statistical thermodynamics, and then kept using it through doctoral research. That depth shows when he teaches: he can trace a concept like chemical potential or a Maxwell relation back to the physical picture driving the math, catching the exact step where a student's understanding breaks down. Rated 5.0 by students.

Before switching to economics at Columbia, Damani was on the pre-med track — which means he's recently sat through the same thermodynamics, kinetics, and calculus-intensive chemistry coursework that p-chem demands, and remembers exactly where the conceptual gaps tend to open up. He approaches topics like enthalpy, equilibrium constants, and rate laws by reconstructing the reasoning behind each equation rather than just presenting the final derivation. Rated 5.0 by students.

Neuroscience at the undergraduate level means Amy has already tangled with the thermodynamics and kinetics that p-chem formalizes — Nernst equation derivations, membrane energetics, and the statistical behavior of ion channels all demand that same calculus-heavy reasoning. She uses those biological touchpoints to make abstract topics like entropy and equilibrium constants feel grounded in systems students can actually picture. Rated 5.0 by students.

Six years of pharmacy doctoral training saturates you in the applied side of p-chem — drug solubility curves governed by thermodynamic principles, pharmacokinetic rate equations, and the free energy calculations behind formulation stability — so Zachary knows these derivations from the inside out. He teaches topics like chemical potential, phase diagrams, and equilibrium constants by tying each one back to the pharmaceutical systems where they actually determine outcomes. Rated 4.9 by students.

A PhD in physics means Muhammed has spent years inside the quantum mechanics, statistical mechanics, and thermodynamics that p-chem courses formalize — solving Schrödinger equations, working through partition functions, and deriving equations of state weren't side topics but the core of his training. He approaches p-chem derivations as a physicist would, emphasizing the physical reasoning behind each mathematical step so that concepts like chemical potential or phase transitions feel like natural consequences rather than memorized formulas.

I am currently a graduate student in Chemical Engineering at the University of Delaware. I am working on using magnetic and flow fields to create advanced materials by directing the self-assembly process of nanoparticles . I have tutored students in Chemistry, Physics and Math all throughout undergraduate and graduate work. I truly enjoy breaking material down into its core components that allows the students to understand complicated information.

This is Jacob's home turf. He earned his Ph.D. in Physical Chemistry from UC Berkeley and now conducts research at Northwestern, so topics like quantum mechanics, statistical thermodynamics, and spectroscopy are part of his everyday work. He walks students through the math-heavy derivations that make p-chem notoriously difficult, connecting each equation back to the physical picture it describes.

Two chemistry degrees — bachelor's and master's — mean Chad has gone through the full p-chem gauntlet himself, from quantum mechanical models and statistical thermodynamics to the calculus-dense derivations of chemical kinetics. He teaches the subject by zeroing in on where the math and the molecular picture disconnect for each student, whether that's a tricky partial derivative in a thermodynamic identity or the logic behind a partition function. Rated 4.8 by students.

Mechanical engineering at Rice means Aleksey has been solving thermodynamic cycles, heat transfer problems, and differential equations for years — the exact mathematical toolkit that p-chem throws at students in a chemistry wrapper. He breaks down topics like entropy, enthalpy, and phase equilibria by treating them as engineering problems first, then layering in the molecular-level chemistry that gives each variable its meaning. Rated 5.0 by students.

Biology research through the American Museum of Natural History and pre-med coursework at Cornell gave Krishna hands-on exposure to the thermodynamic and kinetic principles that p-chem formalizes — energy changes in biological systems, reaction rates, equilibrium behavior. She uses that life-science grounding to make topics like Gibbs free energy and rate laws feel like descriptions of real molecular events rather than pure derivation exercises.

Environmental statistics at Rice required Alex to work extensively with the same calculus-heavy quantitative methods — differential equations, statistical modeling, multivariable analysis — that students encounter in thermodynamics and kinetics derivations throughout a p-chem sequence. His geography background adds a surprising edge: understanding energy balances and phase transitions in Earth systems translates directly to making sense of state functions and equilibrium in a chemistry context.

A physics degree means Eitan spent years inside the quantum mechanics, statistical mechanics, and thermodynamics that p-chem courses formalize on the chemistry side — Schrödinger's equation, Boltzmann statistics, and state functions are native territory rather than new abstractions. He teaches the derivations by clarifying the physical picture each equation encodes, so a student wrestling with a partition function or a Carnot cycle can see the molecular behavior driving every calculus step. Holds a 5.0 rating.

Thermodynamics, kinetics, and quantum mechanics all converge in physical chemistry — and that's exactly where Monika's biochemistry and molecular biology training intersects. She breaks down intimidating topics like Gibbs free energy calculations and reaction rate laws by tying them to real chemical systems she studied during her PhD research. Rated 4.8 by students.

Pre-med coursework at Rutgers — graduating summa cum laude with a 4.0 — put Sam through the gauntlet of thermodynamics, kinetics, and quantum chemistry that p-chem demands, all while building the calculus fluency needed to survive dense derivations. He approaches topics like enthalpy, entropy, and rate laws by stripping each equation back to the physical scenario it models, making the leap from math to molecular meaning less painful.

Genetics PhD work is surprisingly calculus-intensive — population dynamics, statistical mechanics of molecular interactions, and the thermodynamic stability of nucleic acid structures all demand the same quantitative reasoning that drives p-chem. Nicholas brings that background to topics like free energy calculations and kinetic modeling, where his comfort with both the math and the molecular biology underneath it keeps derivations grounded in actual chemical behavior. Rated 4.8 by students.

As an MD/PhD student at Northwestern with a chemistry PhD focus and a B.S. in Chemical Science from Michigan, Austin has gone deep on the thermodynamics and quantum mechanics that form p-chem's backbone — and he's still actively working through advanced coursework in these areas. He tackles derivations by building chemical intuition first, so when a student hits a wall at, say, a Legendre transform connecting internal energy to Gibbs free energy, the math follows naturally from understanding what each variable physically represents.

Two biomedical engineering degrees mean Allyson has been doing the calculus-heavy thermodynamics and kinetics work that p-chem formalizes — modeling energy transfer in biological systems, working through rate equations for physiological processes — since undergrad. She zeroes in on the specific mathematical step where a derivation goes from followable to opaque, whether that's a tricky partial derivative in a Maxwell relation or the statistical reasoning inside a Boltzmann distribution. Rated 4.9 by students.