GOALS&OBJECTIVES: WE SEEK TO UNDERSTAND WHETHER THE 'NANOFLARE HYPOTHESIS CAN EXPLAIN CORONAL HEATING BY ANALYZING NEW HIGH QUALITY EMPIRICAL DATA AND BY UNDERSTANDING THOSE DATA USING BOTH THEORY AND FORWARD MODELING. DESPITE SEVERAL IMPORTANT STUDIES OVER THE PAST TWO DECADES IT IS NOT YET CLEAR WHETHER THE SMALLEST SCALE EVENTS DELIVER MORE OR LESS POWER TO THE CORONA THAN DO SOLAR FLARES THEMSELVES. THE NUMBER VS. ENERGY DISTRIBUTION OF ENERGETIC EVENTS IS A POWER LAW WHOSE EXPONENT IS TANTALIZINGLY CLOSE TO THE CRITICAL VALUE OF -2. EXACTLY WHERE THE EXPONENT LANDS HAS NOT BEEN CONCLUSIVELY DETERMINED HOWEVER AND THE POWER LAW MAY CHANGE AT THE SMALLEST SCALES (HERE NOISE EFFECTS DOMINATE EXISTING STUDIES SO THEORETICAL ESTIMATES HAVE EXTRAPOLATED FROM LARGER SCALES). WE WILL FOCUS ON THE DISTRIBUTIONS OF THE SMALLEST IMPULSIVE EVENTS VISIBLE WITH SDO/AIA WHICH OFFERS GREATLY IMPROVED SENSITIVITY CADENCE TEMPERATURE COVERAGE AND FOV COMPARED TO PRIOR WORK USING TRACE. THE PROPERTIES OF EACH DETECTED EVENT WILL BE CAREFULLY CATALOGUED USING DIFFERENTIAL EMISSION MEASURE (DEM) ANALYSIS TO INFER TEMPERATURES AND ENERGETICS. IN TANDEM WITH THE AIA DATA ANALYSIS WE WILL CARRY OUT 'SYNTHETIC DATA' ANALYSIS EXERCISES AND FORWARD FITTING USING THE EBTEL AND/OR HYDRAD NUMERICAL MODELS TO IDENTIFY AND CORRECT FOR SYSTEMATIC CROSS-SCALE BIAS IN THE DETECTION ALGORITHMS. OUR MODELING COMPONENT IS A CRITICAL INNOVATION BECAUSE IT ALLOWS US TO UNDERSTAND AND CORRECT SYSTEMATIC SAMPLING EFFECTS THAT COULD SKEW THE SMALL-SCALE TAIL OF THE DISTRIBUTION. THESE EFFECTS INCLUDE BOTH SAMPLING BIAS AND PHYSICAL EFFECTS THAT AFFECT DETECTABILITY OF INDIVIDUAL EVENTS.